{"links":[],"processes":[{"categories":["math > trigonometric"],"description":"Computes the arc cosine of `x`. The arc cosine is the inverse function of the cosine so that *`arccos(cos(x)) = x`*.\n\nWorks on radians only.\nThe no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"x":1},"returns":0}],"id":"arccos","links":[{"href":"http://mathworld.wolfram.com/InverseCosine.html","rel":"about","title":"Inverse cosine explained by Wolfram MathWorld"}],"parameters":[{"description":"A number.","name":"x","schema":{"type":["number","null"]}}],"returns":{"description":"The computed angle in radians.","schema":{"type":["number","null"]}},"summary":"Inverse cosine"},{"categories":["math > trigonometric"],"description":"Computes the inverse hyperbolic cosine of `x`. It is the inverse function of the hyperbolic cosine so that *`arcosh(cosh(x)) = x`*.\n\nWorks on radians only.\nThe no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"x":1},"returns":0}],"id":"arcosh","links":[{"href":"http://mathworld.wolfram.com/InverseHyperbolicCosine.html","rel":"about","title":"Inverse hyperbolic cosine explained by Wolfram MathWorld"}],"parameters":[{"description":"A number.","name":"x","schema":{"type":["number","null"]}}],"returns":{"description":"The computed angle in radians.","schema":{"type":["number","null"]}},"summary":"Inverse hyperbolic cosine"},{"categories":["math","math > exponential & logarithmic"],"description":"Computes the exponentiation for the base `base` raised to the power of `p`.\n\nThe no-data value `null` is passed through and therefore gets propagated if any of the arguments is `null`.","examples":[{"arguments":{"base":0,"p":2},"returns":0},{"arguments":{"base":2.5,"p":0},"returns":1},{"arguments":{"base":3,"p":3},"returns":27},{"arguments":{"base":5,"p":-1},"returns":0.2},{"arguments":{"base":1,"p":0.5},"returns":1},{"arguments":{"base":1,"p":null},"returns":null},{"arguments":{"base":null,"p":2},"returns":null}],"id":"power","links":[{"href":"http://mathworld.wolfram.com/Power.html","rel":"about","title":"Power explained by Wolfram MathWorld"}],"parameters":[{"description":"The numerical base.","name":"base","schema":{"type":["number","null"]}},{"description":"The numerical exponent.","name":"p","schema":{"type":["number","null"]}}],"returns":{"description":"The computed value for `base` raised to the power of `p`.","schema":{"type":["number","null"]}},"summary":"Exponentiation"},{"categories":["arrays","reducer"],"description":"Gives the last element of an array.\n\nAn array without non-`null` elements resolves always with `null`.","examples":[{"arguments":{"data":[1,0,3,2]},"returns":2},{"arguments":{"data":["A","B",null]},"returns":"B"},{"arguments":{"data":[0,1,null],"ignore_nodata":false},"returns":null},{"arguments":{"data":[]},"description":"The input array is empty: return `null`.","returns":null}],"id":"last","parameters":[{"description":"An array with elements of any data type.","name":"data","schema":{"items":{"description":"Any data type is allowed."},"type":"array"}},{"default":true,"description":"Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if the last value is such a value.","name":"ignore_nodata","optional":true,"schema":{"type":"boolean"}}],"returns":{"description":"The last element of the input array.","schema":{"description":"Any data type is allowed."}},"summary":"Last element"},{"categories":["math"],"description":"Subtracts argument `y` from the argument `x` (*`x - y`*) and returns the computed result.\n\nNo-data values are taken into account so that `null` is returned if any element is such a value.\n\nThe computations follow [IEEE Standard 754](https://ieeexplore.ieee.org/document/8766229) whenever the processing environment supports it.","examples":[{"arguments":{"x":5,"y":2.5},"returns":2.5},{"arguments":{"x":-2,"y":4},"returns":-6},{"arguments":{"x":1,"y":null},"returns":null}],"id":"subtract","links":[{"href":"http://mathworld.wolfram.com/Subtraction.html","rel":"about","title":"Subtraction explained by Wolfram MathWorld"},{"href":"https://ieeexplore.ieee.org/document/8766229","rel":"about","title":"IEEE Standard 754-2019 for Floating-Point Arithmetic"}],"parameters":[{"description":"The minuend.","name":"x","schema":{"type":["number","null"]}},{"description":"The subtrahend.","name":"y","schema":{"type":["number","null"]}}],"returns":{"description":"The computed result.","schema":{"type":["number","null"]}},"summary":"Subtraction of two numbers"},{"categories":["logic"],"description":"Inverts a single boolean so that `true` gets `false` and `false` gets `true`.\n\nThe no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"x":null},"returns":null},{"arguments":{"x":false},"returns":true},{"arguments":{"x":true},"returns":false}],"id":"not","parameters":[{"description":"Boolean value to invert.","name":"x","schema":{"type":["boolean","null"]}}],"returns":{"description":"Inverted boolean value.","schema":{"type":["boolean","null"]}},"summary":"Inverting a boolean"},{"categories":["math > trigonometric"],"description":"Computes the hyperbolic cosine of `x`.\n\nWorks on radians only.\nThe no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"x":0},"returns":1}],"id":"cosh","links":[{"href":"http://mathworld.wolfram.com/HyperbolicCosine.html","rel":"about","title":"Hyperbolic cosine explained by Wolfram MathWorld"}],"parameters":[{"description":"An angle in radians.","name":"x","schema":{"type":["number","null"]}}],"returns":{"description":"The computed hyperbolic cosine of `x`.","schema":{"type":["number","null"]}},"summary":"Hyperbolic cosine"},{"categories":["math > trigonometric"],"description":"Computes the inverse hyperbolic tangent of `x`. It is the inverse function of the hyperbolic tangent so that *`artanh(tanh(x)) = x`*.\n\nWorks on radians only.\nThe no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"x":0},"returns":0}],"id":"artanh","links":[{"href":"http://mathworld.wolfram.com/InverseHyperbolicTangent.html","rel":"about","title":"Inverse hyperbolic tangent explained by Wolfram MathWorld"}],"parameters":[{"description":"A number.","name":"x","schema":{"type":["number","null"]}}],"returns":{"description":"The computed angle in radians.","schema":{"type":["number","null"]}},"summary":"Inverse hyperbolic tangent"},{"categories":["comparison"],"description":"Checks whether the specified value `x` is valid. The following values are considered valid:\n\n* Any finite numerical value (integers and floating-point numbers). The definition of finite numbers follows the [IEEE Standard 754](https://ieeexplore.ieee.org/document/4610935) and excludes the special value `NaN` (not a number).\n* Any other value that is not a no-data value according to ``is_nodata()``. Thus all arrays, objects and strings are valid, regardless of their content.","examples":[{"arguments":{"x":1},"returns":true},{"arguments":{"x":"Test"},"returns":true},{"arguments":{"x":null},"returns":false},{"arguments":{"x":[null,null]},"returns":true}],"id":"is_valid","links":[{"href":"https://ieeexplore.ieee.org/document/4610935","rel":"about","title":"IEEE Standard 754-2008 for Floating-Point Arithmetic"}],"parameters":[{"description":"The data to check.","name":"x","schema":{"description":"Any data type is allowed."}}],"returns":{"description":"`true` if the data is valid, otherwise `false`.","schema":{"type":"boolean"}},"summary":"Value is valid data"},{"categories":["arrays","reducer"],"description":"Gives the first element of an array.\n\nAn array without non-`null` elements resolves always with `null`.","examples":[{"arguments":{"data":[1,0,3,2]},"returns":1},{"arguments":{"data":[null,"A","B"]},"returns":"A"},{"arguments":{"data":[null,2,3],"ignore_nodata":false},"returns":null},{"arguments":{"data":[]},"description":"The input array is empty: return `null`.","returns":null}],"id":"first","parameters":[{"description":"An array with elements of any data type.","name":"data","schema":{"items":{"description":"Any data type is allowed."},"type":"array"}},{"default":true,"description":"Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if the first value is such a value.","name":"ignore_nodata","optional":true,"schema":{"type":"boolean"}}],"returns":{"description":"The first element of the input array.","schema":{"description":"Any data type is allowed."}},"summary":"First element"},{"categories":["math > statistics","reducer"],"description":"The statistical median of an array of numbers is the value separating the higher half from the lower half of the data.\n\nAn array without non-`null` elements resolves always with `null`.\n\n**Remarks:**\n\n* For symmetric arrays, the result is equal to the ``mean()``.\n* The median can also be calculated by computing the ``quantiles()`` with a probability of *0.5*.","examples":[{"arguments":{"data":[1,3,3,6,7,8,9]},"returns":6},{"arguments":{"data":[1,2,3,4,5,6,8,9]},"returns":4.5},{"arguments":{"data":[-1,-0.5,null,1]},"returns":-0.5},{"arguments":{"data":[-1,0,null,1],"ignore_nodata":false},"returns":null},{"arguments":{"data":[]},"description":"The input array is empty: return `null`.","returns":null},{"arguments":{"data":[null,null]},"description":"The input array has only `null` elements: return `null`.","returns":null}],"id":"median","links":[{"href":"http://mathworld.wolfram.com/StatisticalMedian.html","rel":"about","title":"Statistical Median explained by Wolfram MathWorld"}],"parameters":[{"description":"An array of numbers.","name":"data","schema":{"items":{"type":["number","null"]},"type":"array"}},{"default":true,"description":"Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value.","name":"ignore_nodata","optional":true,"schema":{"type":"boolean"}}],"process_graph":{"array_element":{"arguments":{"data":{"from_node":"quantiles"},"index":0,"return_nodata":true},"process_id":"array_element","result":true},"quantiles":{"arguments":{"data":{"from_parameter":"data"},"ignore_nodata":{"from_parameter":"ignore_nodata"},"probabilities":[0.5]},"process_id":"quantiles"}},"returns":{"description":"The computed statistical median.","schema":{"type":["number","null"]}},"summary":"Statistical median"},{"categories":["texts","comparison"],"description":"Compares whether `x` is strictly equal to `y`.\n\n**Remarks:**\n\n* Data types MUST be checked strictly. For example, a string with the content *1* is not equal to the number *1*. Nevertheless, an integer *1* is equal to a floating-point number *1.0* as `integer` is a sub-type of `number`.\n* If any operand is `null`, the return value is `null`.\n* Temporal strings are normal strings. To compare temporal strings as dates/times, use ``date_difference()``.","examples":[{"arguments":{"x":1,"y":null},"returns":null},{"arguments":{"x":null,"y":null},"returns":null},{"arguments":{"x":1,"y":1},"returns":true},{"arguments":{"x":1,"y":"1"},"returns":false},{"arguments":{"x":0,"y":false},"returns":false},{"arguments":{"delta":0.01,"x":1.02,"y":1},"returns":false},{"arguments":{"delta":0.01,"x":-1,"y":-1.001},"returns":true},{"arguments":{"delta":10,"x":115,"y":110},"returns":true},{"arguments":{"x":"Test","y":"test"},"returns":false},{"arguments":{"case_sensitive":false,"x":"Test","y":"test"},"returns":true},{"arguments":{"case_sensitive":false,"x":"\u00c4","y":"\u00e4"},"returns":true},{"arguments":{"x":"2018-01-01T00:00:00Z","y":"2018-01-01T00:00:00+00:00"},"returns":false},{"arguments":{"x":null,"y":null},"returns":null}],"id":"eq","parameters":[{"description":"First operand.","name":"x","schema":{"type":["number","boolean","string","null"]}},{"description":"Second operand.","name":"y","schema":{"type":["number","boolean","string","null"]}},{"default":null,"description":"Only applicable for comparing two numbers. If this optional parameter is set to a positive non-zero number the equality of two numbers is checked against a delta value. This is especially useful to circumvent problems with floating-point inaccuracy in machine-based computation.\n\nThis option is basically an alias for the following computation: `lte(abs(minus([x, y]), delta)`","name":"delta","optional":true,"schema":{"type":["number","null"]}},{"default":true,"description":"Only applicable for comparing two strings. Case sensitive comparison can be disabled by setting this parameter to `false`.","name":"case_sensitive","optional":true,"schema":{"type":"boolean"}}],"returns":{"description":"`true` if `x` is equal to `y`, `null` if any operand is `null`, otherwise `false`.","schema":{"type":["boolean","null"]}},"summary":"Equal to comparison"},{"categories":["math"],"description":"Computes the absolute value of a real number `x`, which is the \"unsigned\" portion of x and often denoted as *|x|*.\n\nThe no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"x":0},"returns":0},{"arguments":{"x":3.5},"returns":3.5},{"arguments":{"x":-0.4},"returns":0.4},{"arguments":{"x":-3.5},"returns":3.5}],"id":"absolute","links":[{"href":"http://mathworld.wolfram.com/AbsoluteValue.html","rel":"about","title":"Absolute value explained by Wolfram MathWorld"}],"parameters":[{"description":"A number.","name":"x","schema":{"type":["number","null"]}}],"process_graph":{"if":{"arguments":{"accept":{"from_node":"multiply"},"reject":{"from_parameter":"x"},"value":{"from_node":"lt"}},"process_id":"if","result":true},"lt":{"arguments":{"x":{"from_parameter":"x"},"y":0},"process_id":"lt"},"multiply":{"arguments":{"x":{"from_parameter":"x"},"y":-1},"process_id":"multiply"}},"returns":{"description":"The computed absolute value.","schema":{"minimum":0,"type":["number","null"]}},"summary":"Absolute value"},{"categories":["math > trigonometric"],"description":"Computes the arc tangent of two numbers `x` and `y`. It is similar to calculating the arc tangent of *`y / x`*, except that the signs of both arguments are used to determine the quadrant of the result.\n\nWorks on radians only.\nThe no-data value `null` is passed through and therefore gets propagated if any of the arguments is `null`.","examples":[{"arguments":{"x":0,"y":0},"returns":0},{"arguments":{"x":1.5,"y":null},"returns":null}],"id":"arctan2","links":[{"href":"https://en.wikipedia.org/wiki/Atan2","rel":"about","title":"Two-argument inverse tangent explained by Wikipedia"}],"parameters":[{"description":"A number to be used as the dividend.","name":"y","schema":{"type":["number","null"]}},{"description":"A number to be used as the divisor.","name":"x","schema":{"type":["number","null"]}}],"returns":{"description":"The computed angle in radians.","schema":{"type":["number","null"]}},"summary":"Inverse tangent of two numbers"},{"categories":["arrays"],"description":"Gives all labels for a labeled array or gives all indices for an array without labels. If the array is not labeled, an array with the zero-based indices is returned. The labels or indices have the same order as in the array.","id":"array_labels","parameters":[{"description":"An array.","name":"data","schema":{"type":"array"}}],"returns":{"description":"The labels or indices as array.","schema":{"items":{"type":["number","string"]},"type":"array"}},"summary":"Get the labels for an array"},{"categories":["math"],"description":"Divides argument `x` by the argument `y` (*`x / y`*) and returns the computed result.\n\nNo-data values are taken into account so that `null` is returned if any element is such a value.\n\nThe computations follow [IEEE Standard 754](https://ieeexplore.ieee.org/document/8766229) whenever the processing environment supports it. Therefore, a division by zero results in \u00b1infinity if the processing environment supports it. Otherwise, a `DivisionByZero` exception must the thrown.","examples":[{"arguments":{"x":5,"y":2.5},"returns":2},{"arguments":{"x":-2,"y":4},"returns":-0.5},{"arguments":{"x":1,"y":null},"returns":null}],"exceptions":{"DivisionByZero":{"message":"Division by zero is not supported."}},"id":"divide","links":[{"href":"http://mathworld.wolfram.com/Division.html","rel":"about","title":"Division explained by Wolfram MathWorld"},{"href":"https://ieeexplore.ieee.org/document/8766229","rel":"about","title":"IEEE Standard 754-2019 for Floating-Point Arithmetic"}],"parameters":[{"description":"The dividend.","name":"x","schema":{"type":["number","null"]}},{"description":"The divisor.","name":"y","schema":{"type":["number","null"]}}],"returns":{"description":"The computed result.","schema":{"type":["number","null"]}},"summary":"Division of two numbers"},{"categories":["comparison","math > constants"],"description":"Checks whether the specified value `x` is *not* a number. Numbers are all integers and floating-point numbers, except for the special value `NaN` as defined by the [IEEE Standard 754](https://ieeexplore.ieee.org/document/4610935).","examples":[{"arguments":{"x":1},"returns":false},{"arguments":{"x":"Test"},"returns":true},{"arguments":{"x":null},"returns":true}],"id":"is_nan","links":[{"href":"https://ieeexplore.ieee.org/document/4610935","rel":"about","title":"IEEE Standard 754-2008 for Floating-Point Arithmetic"},{"href":"http://mathworld.wolfram.com/NaN.html","rel":"about","title":"NaN explained by Wolfram MathWorld"}],"parameters":[{"description":"The data to check.","name":"x","schema":{"description":"Any data type is allowed."}}],"returns":{"description":"Returns `true` for `NaN` and all non-numeric data types, otherwise returns `false`.","schema":{"type":"boolean"}},"summary":"Value is not a number"},{"categories":["logic","reducer"],"description":"Checks if **all** of the values in `data` are true. If no value is given (i.e. the array is empty) the process returns `null`.\n\nBy default all no-data values are ignored so that the process returns `null` if all values are no-data, `true` if all values are true and `false` otherwise. Setting the `ignore_nodata` flag to `false` takes no-data values into account and the array values are reduced pairwise according to the following truth table:\n\n```\n      || null  | false | true\n----- || ----- | ----- | -----\nnull  || null  | false | null\nfalse || false | false | false\ntrue  || null  | false | true\n```\n\n**Remark:** The process evaluates all values from the first to the last element and stops once the outcome is unambiguous. A result is ambiguous unless a value is `false` or all values have been taken into account.","examples":[{"arguments":{"data":[false,null]},"returns":false},{"arguments":{"data":[true,null]},"returns":true},{"arguments":{"data":[false,null],"ignore_nodata":false},"returns":false},{"arguments":{"data":[true,null],"ignore_nodata":false},"returns":null},{"arguments":{"data":[true,false,true,false]},"returns":false},{"arguments":{"data":[true,false]},"returns":false},{"arguments":{"data":[true,true]},"returns":true},{"arguments":{"data":[true]},"returns":true},{"arguments":{"data":[null],"ignore_nodata":false},"returns":null},{"arguments":{"data":[]},"returns":null}],"id":"all","parameters":[{"description":"A set of boolean values.","name":"data","schema":{"items":{"type":["boolean","null"]},"type":"array"}},{"default":true,"description":"Indicates whether no-data values are ignored or not and ignores them by default.","name":"ignore_nodata","optional":true,"schema":{"type":"boolean"}}],"returns":{"description":"Boolean result of the logical operation.","schema":{"type":["boolean","null"]}},"summary":"Are all of the values true?"},{"categories":["math > rounding"],"description":"Rounds a real number `x` to specified precision `p`.\n\nIf `x` is halfway between closest numbers of precision `p`, it is rounded to the closest even number of precision `p`.\nThis behavior follows [IEEE Standard 754](https://ieeexplore.ieee.org/document/8766229) and is often called \"round to nearest (even)\" or \"banker's rounding\". It minimizes rounding errors that result from consistently rounding a midpoint value in a single direction.\n\nThe no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"x":0},"returns":0},{"arguments":{"p":1,"x":3.56},"returns":3.6},{"arguments":{"p":2,"x":-0.4444444},"returns":-0.44},{"arguments":{"x":-2.5},"returns":-2},{"arguments":{"x":-3.5},"returns":-4},{"arguments":{"p":1,"x":0.25},"returns":0.2},{"arguments":{"p":1,"x":0.35},"returns":0.4},{"arguments":{"p":-2,"x":1234.5},"returns":1200}],"id":"round","links":[{"href":"http://mathworld.wolfram.com/AbsoluteValue.html","rel":"about","title":"Absolute value explained by Wolfram MathWorld"},{"href":"https://ieeexplore.ieee.org/document/8766229","rel":"about","title":"IEEE Standard 754-2019 for Floating-Point Arithmetic"}],"parameters":[{"description":"A number to round.","name":"x","schema":{"type":["number","null"]}},{"default":0,"description":"A positive number specifies the number of digits after the decimal point to round to. A negative number means rounding to a power of ten, so for example *-2* rounds to the nearest hundred. Defaults to *0*.","name":"p","optional":true,"schema":{"type":"integer"}}],"returns":{"description":"The rounded number.","schema":{"type":["number","null"]}},"summary":"Round to a specified precision"},{"categories":["math","math > statistics","reducer"],"description":"Computes the smallest value of an array of numbers, which is equal to the last element of a sorted (i.e., ordered) version of the array.\n\nAn array without non-`null` elements resolves always with `null`.","examples":[{"arguments":{"data":[1,0,3,2]},"returns":0},{"arguments":{"data":[5,2.5,null,-0.7]},"returns":-0.7},{"arguments":{"data":[1,0,3,null,2],"ignore_nodata":false},"returns":null},{"arguments":{"data":[]},"returns":null}],"id":"min","links":[{"href":"http://mathworld.wolfram.com/Minimum.html","rel":"about","title":"Minimum explained by Wolfram MathWorld"}],"parameters":[{"description":"An array of numbers.","name":"data","schema":{"items":{"type":["number","null"]},"type":"array"}},{"default":true,"description":"Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value.","name":"ignore_nodata","optional":true,"schema":{"type":"boolean"}}],"returns":{"description":"The minimum value.","schema":{"type":["number","null"]}},"summary":"Minimum value"},{"categories":["logic","reducer"],"description":"Checks if **any** (i.e. at least one) value in `data` is `true`. If no value is given (i.e. the array is empty) the process returns `null`.\n\nBy default all no-data values are ignored so that the process returns `null` if all values are no-data, `true` if at least one value is true and `false` otherwise. Setting the `ignore_nodata` flag to `false` takes no-data values into account and the array values are reduced pairwise according to the following truth table:\n\n```\n      || null | false | true\n----- || ---- | ----- | ----\nnull  || null | null  | true\nfalse || null | false | true\ntrue  || true | true  | true\n```\n\n**Remark:** The process evaluates all values from the first to the last element and stops once the outcome is unambiguous. A result is ambiguous unless a value is `true`.","examples":[{"arguments":{"data":[false,null]},"returns":false},{"arguments":{"data":[true,null]},"returns":true},{"arguments":{"data":[false,null],"ignore_nodata":false},"returns":null},{"arguments":{"data":[true,null],"ignore_nodata":false},"returns":true},{"arguments":{"data":[true,false,true,false]},"returns":true},{"arguments":{"data":[true,false]},"returns":true},{"arguments":{"data":[false,false]},"returns":false},{"arguments":{"data":[true]},"returns":true},{"arguments":{"data":[null],"ignore_nodata":false},"returns":null},{"arguments":{"data":[]},"returns":null}],"id":"any","parameters":[{"description":"A set of boolean values.","name":"data","schema":{"items":{"type":["boolean","null"]},"type":"array"}},{"default":true,"description":"Indicates whether no-data values are ignored or not and ignores them by default.","name":"ignore_nodata","optional":true,"schema":{"type":"boolean"}}],"returns":{"description":"Boolean result of the logical operation.","schema":{"type":["boolean","null"]}},"summary":"Is at least one value true?"},{"categories":["comparison"],"description":"Compares whether `x` is greater than or equal to `y`.\n\n**Remarks:**\n\n* If any operand is `null`, the return value is `null`.\n* If the operands are not equal (see process ``eq()``) and any of them is not a `number`, the process returns `false`.\n* Temporal strings are normal strings. To compare temporal strings as dates/times, use ``date_difference()``.","examples":[{"arguments":{"x":1,"y":null},"returns":null},{"arguments":{"x":0,"y":0},"returns":true},{"arguments":{"x":1,"y":2},"returns":false},{"arguments":{"x":-0.5,"y":-0.6},"returns":true},{"arguments":{"x":"2018-01-01T00:00:00Z","y":"2018-01-01T00:00:00+00:00"},"returns":false},{"arguments":{"x":true,"y":false},"returns":false},{"arguments":{"x":null,"y":null},"returns":null}],"id":"gte","parameters":[{"description":"First operand.","name":"x","schema":{"type":["number","boolean","string","null"]}},{"description":"Second operand.","name":"y","schema":{"type":["number","boolean","string","null"]}}],"process_graph":{"eq":{"arguments":{"x":{"from_parameter":"x"},"y":{"from_parameter":"y"}},"process_id":"eq"},"gt":{"arguments":{"x":{"from_parameter":"x"},"y":{"from_parameter":"y"}},"process_id":"gt"},"or":{"arguments":{"x":{"from_node":"gt"},"y":{"from_node":"eq"}},"process_id":"or","result":true}},"returns":{"description":"`true` if `x` is greater than or equal to `y`, `null` if any operand is `null`, otherwise `false`.","schema":{"type":["boolean","null"]}},"summary":"Greater than or equal to comparison"},{"categories":["math > trigonometric"],"description":"Computes the cosine of `x`.\n\nWorks on radians only.\nThe no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"x":0},"returns":1}],"id":"cos","links":[{"href":"http://mathworld.wolfram.com/Cosine.html","rel":"about","title":"Cosine explained by Wolfram MathWorld"}],"parameters":[{"description":"An angle in radians.","name":"x","schema":{"type":["number","null"]}}],"returns":{"description":"The computed cosine of `x`.","schema":{"type":["number","null"]}},"summary":"Cosine"},{"categories":["comparison"],"description":"By default, this process checks whether `x` is greater than or equal to `min` and lower than or equal to `max`, which is the same as computing `and(gte(x, min), lte(x, max))`. Therefore, all definitions from ``and()``, ``gte()`` and ``lte()`` apply here as well.\n\nIf `exclude_max` is set to `true` the upper bound is excluded so that the process checks whether `x` is greater than or equal to `min` and lower than `max`. In this case, the process works the same as computing `and(gte(x, min), lt(x, max))`.\n\nLower and upper bounds are not allowed to be swapped. So `min` MUST be lower than or equal to `max` or otherwise the process always returns `false`.","examples":[{"arguments":{"max":1,"min":0,"x":null},"returns":null},{"arguments":{"max":1,"min":0,"x":1},"returns":true},{"arguments":{"exclude_max":true,"max":1,"min":0,"x":1},"returns":false},{"arguments":{"max":0,"min":1,"x":0.5},"description":"Swapped bounds (min is greater than max) MUST always return `false`.","returns":false},{"arguments":{"max":0,"min":-1,"x":-0.5},"returns":true}],"id":"between","parameters":[{"description":"The value to check.","name":"x","schema":{"description":"Any data type is allowed."}},{"description":"Lower boundary (inclusive) to check against.","name":"min","schema":{"type":"number"}},{"description":"Upper boundary (inclusive) to check against.","name":"max","schema":{"type":"number"}},{"default":false,"description":"Exclude the upper boundary `max` if set to `true`. Defaults to `false`.","name":"exclude_max","optional":true,"schema":{"type":"boolean"}}],"process_graph":{"and":{"arguments":{"x":{"from_node":"gte"},"y":{"from_node":"if"}},"process_id":"and","result":true},"gte":{"arguments":{"x":{"from_parameter":"x"},"y":{"from_parameter":"min"}},"process_id":"gte"},"if":{"arguments":{"accept":{"from_node":"lte"},"reject":{"from_node":"lt"},"value":{"from_parameter":"exclude_max"}},"process_id":"if"},"lt":{"arguments":{"x":{"from_parameter":"x"},"y":{"from_parameter":"max"}},"process_id":"lt"},"lte":{"arguments":{"x":{"from_parameter":"x"},"y":{"from_parameter":"max"}},"process_id":"lte"}},"returns":{"description":"`true` if `x` is between the specified bounds, otherwise `false`.","schema":{"type":["boolean","null"]}},"summary":"Between comparison"},{"categories":["arrays","math > statistics","reducer"],"description":"Gives the number of elements in an array that matches the specified condition.\n\n**Remarks:**\n\n* Counts the number of valid elements by default (`condition` is set to `null`). A valid element is every element for which ``is_valid()`` returns `true`.\n* To count all elements in a list set the `condition` parameter to boolean `true`.","examples":[{"arguments":{"data":[]},"returns":0},{"arguments":{"data":[1,0,3,2]},"returns":4},{"arguments":{"data":["ABC",null]},"returns":1},{"arguments":{"condition":true,"data":[false,null]},"returns":2},{"arguments":{"condition":{"gt":{"arguments":{"x":{"from_parameter":"element"},"y":2},"process_id":"gt","result":true}},"data":[0,1,2,3,4,5,null]},"returns":3}],"id":"count","parameters":[{"description":"An array with elements of any data type.","name":"data","schema":{"items":{"description":"Any data type is allowed."},"type":"array"}},{"default":null,"description":"A condition consists of one or more processes, which in the end return a boolean value. It is evaluated against each element in the array. An element is counted only if the condition returns `true`. Defaults to count valid elements in a list (see ``is_valid()``). Setting this parameter to boolean `true` counts all elements in the list. `false` is not a valid value for this parameter.","name":"condition","optional":true,"schema":[{"description":"A logical expression that is evaluated against each element in the array.","parameters":[{"description":"The value of the current element being processed.","name":"x","schema":{"description":"Any data type."}},{"default":null,"description":"Additional data passed by the user.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"`true` if the element should increase the counter, otherwise `false`.","schema":{"type":"boolean"}},"subtype":"process-graph","title":"Condition","type":"object"},{"const":true,"description":"Boolean `true` counts all elements in the list.","title":"All elements","type":"boolean"},{"description":"`null` counts valid elements in the list.","title":"Valid elements","type":"null"}]},{"default":null,"description":"Additional data to be passed to the condition.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"The counted number of elements.","schema":{"type":"number"}},"summary":"Count the number of elements"},{"categories":["logic"],"description":"Checks if **exactly one** of the values is true. If a component is `null`, the result will be `null` if the outcome is ambiguous.\n\n**Truth table:**\n\n```\na \\ b || null | false | true\n----- || ---- | ----- | -----\nnull  || null | null  | null\nfalse || null | false | true\ntrue  || null | true  | false\n```","examples":[{"arguments":{"x":true,"y":true},"returns":false},{"arguments":{"x":false,"y":false},"returns":false},{"arguments":{"x":true,"y":false},"returns":true},{"arguments":{"x":true,"y":null},"returns":null},{"arguments":{"x":false,"y":null},"returns":null}],"id":"xor","parameters":[{"description":"A boolean value.","name":"x","schema":{"type":["boolean","null"]}},{"description":"A boolean value.","name":"y","schema":{"type":["boolean","null"]}}],"process_graph":{"and1":{"arguments":{"x":{"from_node":"not_x"},"y":{"from_parameter":"y"}},"process_id":"and"},"and2":{"arguments":{"x":{"from_parameter":"x"},"y":{"from_node":"not_y"}},"process_id":"and"},"not_x":{"arguments":{"x":{"from_parameter":"x"}},"process_id":"not"},"not_y":{"arguments":{"x":{"from_parameter":"y"}},"process_id":"not"},"or":{"arguments":{"x":{"from_node":"and1"},"y":{"from_node":"and2"}},"process_id":"or","result":true}},"returns":{"description":"Boolean result of the logical XOR.","schema":{"type":["boolean","null"]}},"summary":"Logical XOR (exclusive or)"},{"categories":["math > statistics"],"description":"Two element array containing the minimum and the maximum values of `data`.\n\nThis process is basically an alias for calling both ``min()`` and ``max()``, but may be implemented more performant by back-ends as it only needs to iterate over the data once instead of twice.","examples":[{"arguments":{"data":[1,0,3,2]},"returns":[0,3]},{"arguments":{"data":[5,2.5,null,-0.7]},"returns":[-0.7,5]},{"arguments":{"data":[1,0,3,null,2],"ignore_nodata":false},"returns":[null,null]},{"arguments":{"data":[]},"description":"The input array is empty: return two `null` values.","returns":[null,null]}],"id":"extrema","parameters":[{"description":"An array of numbers.","name":"data","schema":{"items":{"type":["number","null"]},"type":"array"}},{"default":true,"description":"Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that an array with two `null` values is returned if any value is such a value.","name":"ignore_nodata","optional":true,"schema":{"type":"boolean"}}],"returns":{"description":"An array containing the minimum and maximum values for the specified numbers. The first element is the minimum, the second element is the maximum. If the input array is empty both elements are set to `null`.","schema":[{"items":{"type":"number"},"maxItems":2,"minItems":2,"type":"array"},{"items":{"type":"null"},"maxItems":2,"minItems":2,"type":"array"}]},"summary":"Minimum and maximum values"},{"categories":["logic"],"description":"Checks if **both** values are true.\n\nEvaluates parameter `x` before `y` and stops once the outcome is unambiguous. If any argument is `null`, the result will be `null` if the outcome is ambiguous.\n\n**Truth table:**\n\n```\na \\ b || null  | false | true\n----- || ----- | ----- | -----\nnull  || null  | false | null\nfalse || false | false | false\ntrue  || null  | false | true\n```","examples":[{"arguments":{"x":true,"y":true},"returns":true},{"arguments":{"x":true,"y":false},"returns":false},{"arguments":{"x":false,"y":false},"returns":false},{"arguments":{"x":false,"y":null},"returns":false},{"arguments":{"x":true,"y":null},"returns":null}],"id":"and","parameters":[{"description":"A boolean value.","name":"x","schema":{"type":["boolean","null"]}},{"description":"A boolean value.","name":"y","schema":{"type":["boolean","null"]}}],"process_graph":{"all":{"arguments":{"data":[{"from_parameter":"x"},{"from_parameter":"y"}],"ignore_nodata":false},"process_id":"all","result":true}},"returns":{"description":"Boolean result of the logical AND.","schema":{"type":["boolean","null"]}},"summary":"Logical AND"},{"categories":["math > statistics","reducer"],"description":"Computes the sample variance of an array of numbers by calculating the square of the standard deviation (see ``sd()``). It is defined to be the expectation of the squared deviation of a random variable from its expected value. Basically, it measures how far the numbers in the array are spread out from their average value.\n\nAn array without non-`null` elements resolves always with `null`.","examples":[{"arguments":{"data":[-1,1,3]},"returns":4},{"arguments":{"data":[2,3,3,null,4,4,5]},"returns":1.1},{"arguments":{"data":[-1,1,null,3],"ignore_nodata":false},"returns":null},{"arguments":{"data":[]},"description":"The input array is empty: return `null`.","returns":null}],"id":"variance","links":[{"href":"http://mathworld.wolfram.com/Variance.html","rel":"about","title":"Variance explained by Wolfram MathWorld"}],"parameters":[{"description":"An array of numbers.","name":"data","schema":{"items":{"type":["number","null"]},"type":"array"}},{"default":true,"description":"Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value.","name":"ignore_nodata","optional":true,"schema":{"type":"boolean"}}],"process_graph":{"apply":{"arguments":{"context":{"from_node":"mean"},"data":{"from_parameter":"data"},"process":{"process-graph":{"power":{"arguments":{"base":{"from_node":"subtract"},"p":2},"process_id":"power","result":true},"subtract":{"arguments":{"x":{"from_parameter":"x"},"y":{"from_parameter":"context"}},"process_id":"subtract"}}}},"process_id":"apply"},"mean":{"arguments":{"data":{"from_parameter":"data"}},"process_id":"mean"},"mean2":{"arguments":{"data":{"from_node":"apply"},"ignore_nodata":{"from_parameter":"ignore_nodata"}},"process_id":"mean","result":true}},"returns":{"description":"The computed sample variance.","schema":{"type":["number","null"]}},"summary":"Variance"},{"categories":["logic"],"description":"Checks if **at least one** of the values is true. Evaluates parameter `x` before `y` and stops once the outcome is unambiguous. If a component is `null`, the result will be `null` if the outcome is ambiguous.\n\n**Truth table:**\n\n```\na \\ b || null | false | true\n----- || ---- | ----- | ----\nnull  || null | null  | true\nfalse || null | false | true\ntrue  || true | true  | true\n```","examples":[{"arguments":{"x":true,"y":true},"returns":true},{"arguments":{"x":false,"y":false},"returns":false},{"arguments":{"x":true,"y":null},"returns":true},{"arguments":{"x":null,"y":true},"returns":true},{"arguments":{"x":false,"y":null},"returns":null}],"id":"or","parameters":[{"description":"A boolean value.","name":"x","schema":{"type":["boolean","null"]}},{"description":"A boolean value.","name":"y","schema":{"type":["boolean","null"]}}],"process_graph":{"any":{"arguments":{"data":[{"from_parameter":"x"},{"from_parameter":"y"}],"ignore_nodata":false},"process_id":"any","result":true}},"returns":{"description":"Boolean result of the logical OR.","schema":{"type":["boolean","null"]}},"summary":"Logical OR"},{"categories":["math","reducer"],"description":"Sums up all elements in a sequential array of numbers and returns the computed sum.\n\nBy default no-data values are ignored. Setting `ignore_nodata` to `false` considers no-data values so that `null` is returned if any element is such a value.\n\nThe computations follow [IEEE Standard 754](https://ieeexplore.ieee.org/document/8766229) whenever the processing environment supports it.","examples":[{"arguments":{"data":[5,1]},"returns":6},{"arguments":{"data":[-2,4,2.5]},"returns":4.5},{"arguments":{"data":[1,null],"ignore_nodata":false},"returns":null},{"arguments":{"data":[100]},"returns":100},{"arguments":{"data":[null],"ignore_nodata":false},"returns":null},{"arguments":{"data":[]},"returns":null}],"id":"sum","links":[{"href":"http://mathworld.wolfram.com/Sum.html","rel":"about","title":"Sum explained by Wolfram MathWorld"},{"href":"https://ieeexplore.ieee.org/document/8766229","rel":"about","title":"IEEE Standard 754-2019 for Floating-Point Arithmetic"}],"parameters":[{"description":"An array of numbers.","name":"data","schema":{"items":{"type":["number","null"]},"type":"array"}},{"default":true,"description":"Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value.","name":"ignore_nodata","optional":true,"schema":{"type":"boolean"}}],"returns":{"description":"The computed sum of the sequence of numbers.","schema":{"type":["number","null"]}},"summary":"Compute the sum by adding up numbers"},{"categories":["math > trigonometric"],"description":"Computes the sine of `x`.\n\nWorks on radians only.\nThe no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"x":0},"returns":0}],"id":"sin","links":[{"href":"http://mathworld.wolfram.com/Sine.html","rel":"about","title":"Sine explained by Wolfram MathWorld"}],"parameters":[{"description":"An angle in radians.","name":"x","schema":{"type":["number","null"]}}],"returns":{"description":"The computed sine of `x`.","schema":{"type":["number","null"]}},"summary":"Sine"},{"categories":["math > trigonometric"],"description":"Computes the hyperbolic sine of `x`.\n\nWorks on radians only.\nThe no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"x":0},"returns":0}],"id":"sinh","links":[{"href":"http://mathworld.wolfram.com/HyperbolicSine.html","rel":"about","title":"Hyperbolic sine explained by Wolfram MathWorld"}],"parameters":[{"description":"An angle in radians.","name":"x","schema":{"type":["number","null"]}}],"returns":{"description":"The computed hyperbolic sine of `x`.","schema":{"type":["number","null"]}},"summary":"Hyperbolic sine"},{"categories":["math","reducer"],"description":"Multiplies all elements in a sequential array of numbers and returns the computed product.\n\nBy default no-data values are ignored. Setting `ignore_nodata` to `false` considers no-data values so that `null` is returned if any element is such a value.\n\nThe computations follow [IEEE Standard 754](https://ieeexplore.ieee.org/document/8766229) whenever the processing environment supports it.","examples":[{"arguments":{"data":[5,0]},"returns":0},{"arguments":{"data":[-2,4,2.5]},"returns":-20},{"arguments":{"data":[1,null],"ignore_nodata":false},"returns":null},{"arguments":{"data":[-1]},"returns":-1},{"arguments":{"data":[null],"ignore_nodata":false},"returns":null},{"arguments":{"data":[]},"returns":null}],"id":"product","links":[{"href":"http://mathworld.wolfram.com/Product.html","rel":"about","title":"Product explained by Wolfram MathWorld"},{"href":"https://ieeexplore.ieee.org/document/8766229","rel":"about","title":"IEEE Standard 754-2019 for Floating-Point Arithmetic"}],"parameters":[{"description":"An array of numbers.","name":"data","schema":{"items":{"type":["number","null"]},"type":"array"}},{"default":true,"description":"Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value.","name":"ignore_nodata","optional":true,"schema":{"type":"boolean"}}],"returns":{"description":"The computed product of the sequence of numbers.","schema":{"type":["number","null"]}},"summary":"Compute the product by multiplying numbers"},{"categories":["math > exponential & logarithmic"],"description":"Exponential function to the base *e* raised to the power of `p`.\n\nThe no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"p":0},"returns":1},{"arguments":{"p":null},"returns":null}],"id":"exp","links":[{"href":"http://mathworld.wolfram.com/ExponentialFunction.html","rel":"about","title":"Exponential function explained by Wolfram MathWorld"}],"parameters":[{"description":"The numerical exponent.","name":"p","schema":{"type":["number","null"]}}],"process_graph":{"e":{"arguments":{},"process_id":"e"},"power":{"arguments":{"base":{"from_node":"e"},"p":{"from_parameter":"p"}},"process_id":"power","result":true}},"returns":{"description":"The computed value for *e* raised to the power of `p`.","schema":{"type":["number","null"]}},"summary":"Exponentiation to the base e"},{"categories":["texts","comparison"],"description":"Compares whether `x` is **not** strictly equal to `y`.\n\n**Remarks:**\n\n* Data types MUST be checked strictly. For example, a string with the content *1* is not equal to the number *1*. Nevertheless, an integer *1* is equal to a floating-point number *1.0* as `integer` is a sub-type of `number`.\n* If any operand is `null`, the return value is `null`.\n* Strings are expected to be encoded in UTF-8 by default.\n* Temporal strings are normal strings. To compare temporal strings as dates/times, use ``date_difference()``.","examples":[{"arguments":{"x":1,"y":null},"returns":null},{"arguments":{"x":1,"y":1},"returns":false},{"arguments":{"x":1,"y":"1"},"returns":true},{"arguments":{"x":0,"y":false},"returns":true},{"arguments":{"delta":0.01,"x":1.02,"y":1},"returns":true},{"arguments":{"delta":0.01,"x":-1,"y":-1.001},"returns":false},{"arguments":{"delta":10,"x":115,"y":110},"returns":false},{"arguments":{"x":"Test","y":"test"},"returns":true},{"arguments":{"case_sensitive":false,"x":"Test","y":"test"},"returns":false},{"arguments":{"case_sensitive":false,"x":"\u00c4","y":"\u00e4"},"returns":false},{"arguments":{"x":"2018-01-01T00:00:00Z","y":"2018-01-01T00:00:00+00:00"},"returns":true},{"arguments":{"x":null,"y":null},"returns":null}],"id":"neq","parameters":[{"description":"First operand.","name":"x","schema":{"type":["number","boolean","string","null"]}},{"description":"Second operand.","name":"y","schema":{"type":["number","boolean","string","null"]}},{"default":null,"description":"Only applicable for comparing two numbers. If this optional parameter is set to a positive non-zero number the non-equality of two numbers is checked against a delta value. This is especially useful to circumvent problems with floating-point inaccuracy in machine-based computation.\n\nThis option is basically an alias for the following computation: `gt(abs(minus([x, y]), delta)`","name":"delta","optional":true,"schema":{"type":["number","null"]}},{"default":true,"description":"Only applicable for comparing two strings. Case sensitive comparison can be disabled by setting this parameter to `false`.","name":"case_sensitive","optional":true,"schema":{"type":"boolean"}}],"process_graph":{"eq":{"arguments":{"case_sensitive":{"from_parameter":"case_sensitive"},"delta":{"from_parameter":"delta"},"x":{"from_parameter":"x"},"y":{"from_parameter":"y"}},"process_id":"eq"},"not":{"arguments":{"x":{"from_node":"eq"}},"process_id":"not","result":true}},"returns":{"description":"`true` if `x` is *not* equal to `y`, `null` if any operand is `null`, otherwise `false`.","schema":{"type":["boolean","null"]}},"summary":"Not equal to comparison"},{"categories":["math > statistics","reducer"],"description":"Computes the sample standard deviation, which quantifies the amount of variation of an array of numbers. It is defined to be the square root of the corresponding variance (see ``variance()``).\n\nA low standard deviation indicates that the values tend to be close to the expected value, while a high standard deviation indicates that the values are spread out over a wider range.\n\nAn array without non-`null` elements resolves always with `null`.","examples":[{"arguments":{"data":[-1,1,3,null]},"returns":2},{"arguments":{"data":[-1,1,3,null],"ignore_nodata":false},"returns":null},{"arguments":{"data":[]},"description":"The input array is empty: return `null`.","returns":null}],"id":"sd","links":[{"href":"http://mathworld.wolfram.com/StandardDeviation.html","rel":"about","title":"Standard deviation explained by Wolfram MathWorld"}],"parameters":[{"description":"An array of numbers.","name":"data","schema":{"items":{"type":["number","null"]},"type":"array"}},{"default":true,"description":"Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value.","name":"ignore_nodata","optional":true,"schema":{"type":"boolean"}}],"process_graph":{"power":{"arguments":{"base":{"from_node":"variance"},"p":0.5},"process_id":"power","result":true},"variance":{"arguments":{"data":{"from_parameter":"data"},"ignore_nodata":{"from_parameter":"ignore_nodata"}},"process_id":"variance"}},"returns":{"description":"The computed sample standard deviation.","schema":{"type":["number","null"]}},"summary":"Standard deviation"},{"categories":["arrays","sorting"],"description":"Sorts an array into ascending (default) or descending order.\n\n**Remarks:**\n\n* The ordering of ties is implementation-dependent.\n* Temporal strings can *not* be compared based on their string representation due to the time zone/time-offset representations.","examples":[{"arguments":{"data":[6,-1,2,null,7,4,null,8,3,9,9]},"returns":[-1,2,3,4,6,7,8,9,9]},{"arguments":{"asc":false,"data":[6,-1,2,null,7,4,null,8,3,9,9],"nodata":true},"returns":[9,9,8,7,6,4,3,2,-1,null,null]}],"id":"sort","parameters":[{"description":"An array with data to sort.","name":"data","schema":{"items":{"anyOf":[{"type":"number"},{"type":"null"},{"format":"date-time","subtype":"date-time","type":"string"},{"format":"date","subtype":"date","type":"string"}]},"type":"array"}},{"default":true,"description":"The default sort order is ascending, with smallest values first. To sort in reverse (descending) order, set this parameter to `false`.","name":"asc","optional":true,"schema":{"type":"boolean"}},{"default":null,"description":"Controls the handling of no-data values (`null`). By default, they are removed. If set to `true`, missing values in the data are put last; if set to `false`, they are put first.","name":"nodata","optional":true,"schema":{"type":["boolean","null"]}}],"process_graph":{"order":{"arguments":{"asc":{"from_parameter":"asc"},"data":{"from_parameter":"data"},"nodata":{"from_parameter":"nodata"}},"process_id":"order"},"rearrange":{"arguments":{"data":{"from_parameter":"data"},"order":{"from_node":"order"}},"process_id":"rearrange","result":true}},"returns":{"description":"The sorted array.","schema":{"items":{"anyOf":[{"type":"number"},{"type":"null"},{"format":"date-time","subtype":"date-time","type":"string"},{"format":"date","subtype":"date","type":"string"}]},"type":"array"}},"summary":"Sort data"},{"categories":["math > trigonometric"],"description":"Computes the inverse hyperbolic sine of `x`. It is the inverse function of the hyperbolic sine so that *`arsinh(sinh(x)) = x`*.\n\nWorks on radians only.\nThe no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"x":0},"returns":0}],"id":"arsinh","links":[{"href":"http://mathworld.wolfram.com/InverseHyperbolicSine.html","rel":"about","title":"Inverse hyperbolic sine explained by Wolfram MathWorld"}],"parameters":[{"description":"A number.","name":"x","schema":{"type":["number","null"]}}],"returns":{"description":"The computed angle in radians.","schema":{"type":["number","null"]}},"summary":"Inverse hyperbolic sine"},{"categories":["math","math > rounding"],"description":"The integer part of the real number `x`.\n\nThis process is *not* an alias for the ``floor()`` process as defined by some mathematicians, see the examples for negative numbers in both processes for differences.\n\nThe no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"x":0},"returns":0},{"arguments":{"x":3.5},"returns":3},{"arguments":{"x":-0.4},"returns":0},{"arguments":{"x":-3.5},"returns":-3}],"id":"int","links":[{"href":"http://mathworld.wolfram.com/IntegerPart.html","rel":"about","title":"Integer Part explained by Wolfram MathWorld"}],"parameters":[{"description":"A number.","name":"x","schema":{"type":["number","null"]}}],"returns":{"description":"Integer part of the number.","schema":{"type":["integer","null"]}},"summary":"Integer part of a number"},{"categories":["arrays","sorting"],"description":"Computes the ranked (sorted) element positions in the original list (i.e., a permutation), either in ascending or descending order. The process ``rearrange()`` allows sorting the data based on the computed permutation.\n\n**Remarks:**\n\n* The positions in the result are zero-based.\n* The ordering of ties is implementation-dependent.\n* Temporal strings can *not* be compared based on their string representation due to the time zone/time-offset representations.","examples":[{"arguments":{"data":[6,-1,2,null,7,4,null,8,3,9,9]},"returns":[1,2,8,5,0,4,7,9,10]},{"arguments":{"data":[6,-1,2,null,7,4,null,8,3,9,9],"nodata":true},"returns":[1,2,8,5,0,4,7,9,10,3,6]},{"arguments":{"asc":false,"data":[6,-1,2,null,7,4,null,8,3,9,9],"nodata":true},"returns":[9,10,7,4,0,5,8,2,1,3,6]},{"arguments":{"asc":false,"data":[6,-1,2,null,7,4,null,8,3,9,9],"nodata":false},"returns":[3,6,9,10,7,4,0,5,8,2,1]}],"id":"order","links":[{"href":"http://mathworld.wolfram.com/Permutation.html","rel":"about","title":"Permutation explained by Wolfram MathWorld"}],"parameters":[{"description":"An array to compute the order for.","name":"data","schema":{"items":{"anyOf":[{"type":"number"},{"type":"null"},{"format":"date-time","subtype":"date-time","type":"string"},{"format":"date","subtype":"date","type":"string"}]},"type":"array"}},{"default":true,"description":"The default sort order is ascending, with smallest values first. To sort in reverse (descending) order, set this parameter to `false`.","name":"asc","optional":true,"schema":{"type":"boolean"}},{"default":null,"description":"Controls the handling of no-data values (`null`). By default, they are removed. If set to `true`, missing values in the data are put last; if set to `false`, they are put first.","name":"nodata","optional":true,"schema":{"type":["boolean","null"]}}],"returns":{"description":"The computed permutation.","schema":{"items":{"minimum":0,"type":"integer"},"type":"array"}},"summary":"Get the order of array elements"},{"categories":["arrays","reducer"],"description":"Returns the zero-based index of the first (or last) occurrence of the value specified by `value` in the array specified by `data` or `null` if there is no match. Use the parameter `reverse` to switch from the first to the last match.\n\n**Remarks:**\n\n* Use ``array_contains()`` to check if an array contains a value regardless of the position.\n* Use ``array_find_label()`` to find the index for a label.\n* All definitions for the process ``eq()`` regarding the comparison of values apply here as well. A `null` return value from ``eq()`` is handled exactly as `false` (no match).\n* Data types MUST be checked strictly. For example, a string with the content *1* is not equal to the number *1*.\n* An integer *1* is equal to a floating-point number *1.0* as `integer` is a sub-type of `number`. Still, this process may return unexpectedly `false` when comparing floating-point numbers due to floating-point inaccuracy in machine-based computation.\n* Temporal strings are treated as normal strings and MUST NOT be interpreted.\n* If the specified value is an array, object or null, the process always returns `null`. See the examples for one to find `null` values.","examples":[{"arguments":{"data":[1,2,3,2,3],"value":2},"returns":1},{"arguments":{"data":[1,2,3,2,3],"reverse":true,"value":2},"returns":3},{"arguments":{"data":["A","B","C"],"value":"b"},"returns":null},{"arguments":{"data":[1,2,3],"value":"2"},"returns":null},{"arguments":{"data":[1,null,2,null],"value":null},"returns":null},{"arguments":{"data":[[1,2],[3,4]],"value":[1,2]},"returns":null},{"arguments":{"data":[[1,2],[3,4]],"value":2},"returns":null},{"arguments":{"data":[{"a":"b"},{"c":"d"}],"value":{"a":"b"}},"returns":null}],"id":"array_find","links":[{"href":"https://raw.githubusercontent.com/Open-EO/openeo-community-examples/main/processes/array_find_nodata.json","rel":"example","title":"Find no-data values in arrays","type":"application/json"}],"parameters":[{"description":"List to find the value in.","name":"data","schema":{"items":{"description":"Any data type is allowed."},"type":"array"}},{"description":"Value to find in `data`. If the value is `null`, this process returns always `null`.","name":"value","schema":{"description":"Any data type is allowed."}},{"default":false,"description":"By default, this process finds the index of the first match. To return the index of the last match instead, set this flag to `true`.","name":"reverse","optional":true,"schema":{"type":"boolean"}}],"returns":{"description":"The index of the first element with the specified value. If no element was found, `null` is returned.","schema":[{"type":"null"},{"minimum":0,"type":"integer"}]},"summary":"Get the index for a value in an array"},{"categories":["math","math > exponential & logarithmic"],"description":"Computes the square root of a real number `x`, which is equal to calculating `x` to the power of *0.5*.\n\nA square root of x is a number a such that *`a\u00b2 = x`*. Therefore, the square root is the inverse function of a to the power of 2, but only for *a >= 0*.\n\nThe no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"x":0},"returns":0},{"arguments":{"x":1},"returns":1},{"arguments":{"x":9},"returns":3},{"arguments":{"x":null},"returns":null}],"id":"sqrt","links":[{"href":"http://mathworld.wolfram.com/SquareRoot.html","rel":"about","title":"Square root explained by Wolfram MathWorld"}],"parameters":[{"description":"A number.","name":"x","schema":{"type":["number","null"]}}],"process_graph":{"power":{"arguments":{"base":{"from_parameter":"x"},"p":0.5},"process_id":"power","result":true}},"returns":{"description":"The computed square root.","schema":{"type":["number","null"]}},"summary":"Square root"},{"categories":["math"],"description":"Sums up the two numbers `x` and `y` (*`x + y`*) and returns the computed sum.\n\nNo-data values are taken into account so that `null` is returned if any element is such a value.\n\nThe computations follow [IEEE Standard 754](https://ieeexplore.ieee.org/document/8766229) whenever the processing environment supports it.","examples":[{"arguments":{"x":5,"y":2.5},"returns":7.5},{"arguments":{"x":-2,"y":-4},"returns":-6},{"arguments":{"x":1,"y":null},"returns":null}],"id":"add","links":[{"href":"http://mathworld.wolfram.com/Sum.html","rel":"about","title":"Sum explained by Wolfram MathWorld"},{"href":"https://ieeexplore.ieee.org/document/8766229","rel":"about","title":"IEEE Standard 754-2019 for Floating-Point Arithmetic"}],"parameters":[{"description":"The first summand.","name":"x","schema":{"type":["number","null"]}},{"description":"The second summand.","name":"y","schema":{"type":["number","null"]}}],"process_graph":{"sum":{"arguments":{"data":[{"from_parameter":"x"},{"from_parameter":"y"}],"ignore_nodata":false},"process_id":"sum","result":true}},"returns":{"description":"The computed sum of the two numbers.","schema":{"type":["number","null"]}},"summary":"Addition of two numbers"},{"categories":["math > constants","math > exponential & logarithmic"],"description":"The real number *e* is a mathematical constant that is the base of the natural logarithm such that *`ln(e) = 1`*. The numerical value is approximately *2.71828*.","id":"e","links":[{"href":"http://mathworld.wolfram.com/e.html","rel":"about","title":"Mathematical constant e explained by Wolfram MathWorld"}],"parameters":[],"returns":{"description":"The numerical value of Euler's number.","schema":{"type":"number"}},"summary":"Euler's number (e)"},{"categories":["math > trigonometric"],"description":"Computes the tangent of `x`. The tangent is defined to be the sine of x divided by the cosine of x.\n\nWorks on radians only.\nThe no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"x":0},"returns":0}],"id":"tan","links":[{"href":"http://mathworld.wolfram.com/Tangent.html","rel":"about","title":"Tangent explained by Wolfram MathWorld"}],"parameters":[{"description":"An angle in radians.","name":"x","schema":{"type":["number","null"]}}],"returns":{"description":"The computed tangent of `x`.","schema":{"type":["number","null"]}},"summary":"Tangent"},{"categories":["math > statistics","reducer"],"description":"The arithmetic mean of an array of numbers is the quantity commonly called the average. It is defined as the sum of all elements divided by the number of elements.\n\nAn array without non-`null` elements resolves always with `null`.","examples":[{"arguments":{"data":[1,0,3,2]},"returns":1.5},{"arguments":{"data":[9,2.5,null,-2.5]},"returns":3},{"arguments":{"data":[1,null],"ignore_nodata":false},"returns":null},{"arguments":{"data":[]},"description":"The input array is empty: return `null`.","returns":null},{"arguments":{"data":[null,null]},"description":"The input array has only `null` elements: return `null`.","returns":null}],"id":"mean","links":[{"href":"http://mathworld.wolfram.com/ArithmeticMean.html","rel":"about","title":"Arithmetic mean explained by Wolfram MathWorld"}],"parameters":[{"description":"An array of numbers.","name":"data","schema":{"items":{"type":["number","null"]},"type":"array"}},{"default":true,"description":"Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value.","name":"ignore_nodata","optional":true,"schema":{"type":"boolean"}}],"process_graph":{"count":{"arguments":{"condition":{"from_node":"count_condition"},"data":{"from_parameter":"data"}},"process_id":"count"},"count_condition":{"arguments":{"accept":null,"reject":true,"value":{"from_parameter":"ignore_nodata"}},"process_id":"if"},"divide":{"arguments":{"x":{"from_node":"sum"},"y":{"from_node":"count"}},"process_id":"divide"},"if":{"arguments":{"accept":{"from_node":"divide"},"value":{"from_node":"neq"}},"process_id":"if","result":true},"neq":{"arguments":{"x":{"from_node":"count"},"y":0},"process_id":"neq"},"sum":{"arguments":{"data":{"from_parameter":"data"},"ignore_nodata":{"from_parameter":"ignore_nodata"}},"process_id":"sum"}},"returns":{"description":"The computed arithmetic mean.","schema":{"type":["number","null"]}},"summary":"Arithmetic mean (average)"},{"categories":["arrays","filter"],"description":"Filters the array elements based on a logical expression so that afterwards an array is returned that only contains the values, indices and/or labels conforming to the condition.","id":"array_filter","parameters":[{"description":"An array.","name":"data","schema":{"items":{"description":"Any data type is allowed."},"type":"array"}},{"description":"A condition that is evaluated against each value, index and/or label in the array. Only the array elements for which the condition returns `true` are preserved.","name":"condition","schema":{"parameters":[{"description":"The value of the current element being processed.","name":"x","schema":{"description":"Any data type."}},{"description":"The zero-based index of the current element being processed.","name":"index","schema":{"minimum":0,"type":"integer"}},{"default":null,"description":"The label of the current element being processed. Only populated for labeled arrays.","name":"label","optional":true,"schema":[{"type":"number"},{"type":"string"},{"type":"null"}]},{"default":null,"description":"Additional data passed by the user.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"`true` if the value should be kept in the array, otherwise `false`.","schema":{"type":"boolean"}},"subtype":"process-graph","type":"object"}},{"default":null,"description":"Additional data to be passed to the condition.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"An array filtered by the specified condition. The number of elements are less than or equal compared to the original array.","schema":{"items":{"description":"Any data type is allowed."},"type":"array"}},"summary":"Filter an array based on a condition"},{"categories":["math"],"description":"Remainder after a division of `x` by `y` for both integers and floating-point numbers.\n\nThe result of a modulo operation has the sign of the divisor. The handling regarding the sign of the result [differs between programming languages](https://en.wikipedia.org/wiki/Modulo_operation#In_programming_languages) and needs careful consideration to avoid unexpected results.\n\nThe no-data value `null` is passed through and therefore gets propagated if any of the arguments is `null`. A modulo by zero results in \u00b1infinity if the processing environment supports it. Otherwise, a `DivisionByZero` exception must the thrown.","examples":[{"arguments":{"x":27,"y":5},"returns":2},{"arguments":{"x":-27,"y":5},"returns":3},{"arguments":{"x":3.14,"y":-2},"returns":-0.86},{"arguments":{"x":-27,"y":-5},"returns":-2},{"arguments":{"x":27,"y":null},"returns":null},{"arguments":{"x":null,"y":5},"returns":null}],"exceptions":{"DivisionByZero":{"message":"Division by zero is not supported."}},"id":"mod","links":[{"href":"https://en.wikipedia.org/wiki/Modulo_operation","rel":"about","title":"Modulo explained by Wikipedia"}],"parameters":[{"description":"A number to be used as the dividend.","name":"x","schema":{"type":["number","null"]}},{"description":"A number to be used as the divisor.","name":"y","schema":{"type":["number","null"]}}],"returns":{"description":"The remainder after division.","schema":{"type":["number","null"]}},"summary":"Modulo"},{"categories":["math"],"description":"Multiplies the two numbers `x` and `y` (*`x * y`*) and returns the computed product.\n\nNo-data values are taken into account so that `null` is returned if any element is such a value.\n\nThe computations follow [IEEE Standard 754](https://ieeexplore.ieee.org/document/8766229) whenever the processing environment supports it.","examples":[{"arguments":{"x":5,"y":2.5},"returns":12.5},{"arguments":{"x":-2,"y":-4},"returns":8},{"arguments":{"x":1,"y":null},"returns":null}],"exceptions":{"MultiplicandMissing":{"message":"Multiplication requires at least two numbers."}},"id":"multiply","links":[{"href":"http://mathworld.wolfram.com/Product.html","rel":"about","title":"Product explained by Wolfram MathWorld"},{"href":"https://ieeexplore.ieee.org/document/8766229","rel":"about","title":"IEEE Standard 754-2019 for Floating-Point Arithmetic"}],"parameters":[{"description":"The multiplier.","name":"x","schema":{"type":["number","null"]}},{"description":"The multiplicand.","name":"y","schema":{"type":["number","null"]}}],"process_graph":{"product":{"arguments":{"data":[{"from_parameter":"x"},{"from_parameter":"y"}],"ignore_nodata":false},"process_id":"product","result":true}},"returns":{"description":"The computed product of the two numbers.","schema":{"type":["number","null"]}},"summary":"Multiplication of two numbers"},{"categories":["comparison"],"description":"Compares whether `x` is less than or equal to `y`.\n\n**Remarks:**\n\n* If any operand is `null`, the return value is `null`.\n* If the operands are not equal (see process ``eq()``) and any of them is not a `number`, the process returns `false`.\n* Temporal strings are normal strings. To compare temporal strings as dates/times, use ``date_difference()``.","examples":[{"arguments":{"x":1,"y":null},"returns":null},{"arguments":{"x":0,"y":0},"returns":true},{"arguments":{"x":1,"y":2},"returns":true},{"arguments":{"x":-0.5,"y":-0.6},"returns":false},{"arguments":{"x":"2018-01-01T00:00:00Z","y":"2018-01-01T00:00:00+00:00"},"returns":false},{"arguments":{"x":false,"y":true},"returns":false},{"arguments":{"x":null,"y":null},"returns":null}],"id":"lte","parameters":[{"description":"First operand.","name":"x","schema":{"type":["number","boolean","string","null"]}},{"description":"Second operand.","name":"y","schema":{"type":["number","boolean","string","null"]}}],"process_graph":{"eq":{"arguments":{"x":{"from_parameter":"x"},"y":{"from_parameter":"y"}},"process_id":"eq"},"lt":{"arguments":{"x":{"from_parameter":"x"},"y":{"from_parameter":"y"}},"process_id":"lt"},"or":{"arguments":{"x":{"from_node":"lt"},"y":{"from_node":"eq"}},"process_id":"or","result":true}},"returns":{"description":"`true` if `x` is less than or equal to `y`, `null` if any operand is `null`, otherwise `false`.","schema":{"type":["boolean","null"]}},"summary":"Less than or equal to comparison"},{"categories":["math > constants","math > trigonometric"],"description":"The real number Pi (\u03c0) is a mathematical constant that is the ratio of the circumference of a circle to its diameter. The numerical value is approximately *3.14159*.","id":"pi","links":[{"href":"http://mathworld.wolfram.com/Pi.html","rel":"about","title":"Mathematical constant Pi explained by Wolfram MathWorld"}],"parameters":[],"returns":{"description":"The numerical value of Pi.","schema":{"type":"number"}},"summary":"Pi (\u03c0)"},{"categories":["math > rounding"],"description":"The least integer greater than or equal to the number `x`.\n\nThe no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"x":0},"returns":0},{"arguments":{"x":3.5},"returns":4},{"arguments":{"x":-0.4},"returns":0},{"arguments":{"x":-3.5},"returns":-3}],"id":"ceil","links":[{"href":"http://mathworld.wolfram.com/CeilingFunction.html","rel":"about","title":"Ceiling explained by Wolfram MathWorld"}],"parameters":[{"description":"A number to round up.","name":"x","schema":{"type":["number","null"]}}],"returns":{"description":"The number rounded up.","schema":{"type":["integer","null"]}},"summary":"Round fractions up"},{"categories":["math > trigonometric"],"description":"Computes the hyperbolic tangent of `x`. The tangent is defined to be the hyperbolic sine of x divided by the hyperbolic cosine of x.\n\nWorks on radians only.\nThe no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"x":0},"returns":0}],"id":"tanh","links":[{"href":"http://mathworld.wolfram.com/HyperbolicTangent.html","rel":"about","title":"Hyperbolic tangent explained by Wolfram MathWorld"}],"parameters":[{"description":"An angle in radians.","name":"x","schema":{"type":["number","null"]}}],"returns":{"description":"The computed hyperbolic tangent of `x`.","schema":{"type":["number","null"]}},"summary":"Hyperbolic tangent"},{"categories":["math > trigonometric"],"description":"Computes the arc tangent of `x`. The arc tangent is the inverse function of the tangent so that *`arctan(tan(x)) = x`*.\n\nWorks on radians only.\nThe no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"x":0},"returns":0}],"id":"arctan","links":[{"href":"http://mathworld.wolfram.com/InverseTangent.html","rel":"about","title":"Inverse tangent explained by Wolfram MathWorld"}],"parameters":[{"description":"A number.","name":"x","schema":{"type":["number","null"]}}],"returns":{"description":"The computed angle in radians.","schema":{"type":["number","null"]}},"summary":"Inverse tangent"},{"categories":["math > rounding"],"description":"The greatest integer less than or equal to the number `x`.\n\nThis process is *not* an alias for the ``int()`` process as defined by some mathematicians, see the examples for negative numbers in both processes for differences.\n\nThe no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"x":0},"returns":0},{"arguments":{"x":3.5},"returns":3},{"arguments":{"x":-0.4},"returns":-1},{"arguments":{"x":-3.5},"returns":-4}],"id":"floor","links":[{"href":"http://mathworld.wolfram.com/FloorFunction.html","rel":"about","title":"Floor explained by Wolfram MathWorld"}],"parameters":[{"description":"A number to round down.","name":"x","schema":{"type":["number","null"]}}],"returns":{"description":"The number rounded down.","schema":{"type":["integer","null"]}},"summary":"Round fractions down"},{"categories":["arrays","reducer"],"description":"Gives the element with the specified index or label from the array.\n\nEither the parameter `index` or `label` must be specified, otherwise the `ArrayElementParameterMissing` exception is thrown. If both parameters are set the `ArrayElementParameterConflict` exception is thrown.","examples":[{"arguments":{"data":[9,8,7,6,5],"index":2},"returns":7},{"arguments":{"data":["A","B","C"],"index":0},"returns":"A"},{"arguments":{"data":[],"index":0,"return_nodata":true},"returns":null}],"exceptions":{"ArrayElementNotAvailable":{"message":"The array has no element with the specified index or label."},"ArrayElementParameterConflict":{"message":"The process `array_element` only allows that either the `index` or the `labels` parameter is set."},"ArrayElementParameterMissing":{"message":"The process `array_element` requires either the `index` or `labels` parameter to be set."},"ArrayNotLabeled":{"message":"The array is not a labeled array, but the `label` parameter is set. Use the `index` instead."}},"id":"array_element","parameters":[{"description":"An array.","name":"data","schema":{"items":{"description":"Any data type is allowed."},"type":"array"}},{"description":"The zero-based index of the element to retrieve.","name":"index","optional":true,"schema":{"minimum":0,"type":"integer"}},{"description":"The label of the element to retrieve. Throws an `ArrayNotLabeled` exception, if the given array is not a labeled array and this parameter is set.","name":"label","optional":true,"schema":[{"type":"number"},{"type":"string"}]},{"default":false,"description":"By default this process throws an `ArrayElementNotAvailable` exception if the index or label is invalid. If you want to return `null` instead, set this flag to `true`.","name":"return_nodata","optional":true,"schema":{"type":"boolean"}}],"returns":{"description":"The value of the requested element.","schema":{"description":"Any data type is allowed."}},"summary":"Get an element from an array"},{"categories":["math"],"description":"Clips a number between specified minimum and maximum values. A value larger than the maximum value is set to the maximum value, a value lower than the minimum value is set to the minimum value.\n\nThe no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"max":1,"min":-1,"x":-5},"returns":-1},{"arguments":{"max":10,"min":1,"x":10.001},"returns":10},{"arguments":{"max":0.02,"min":0,"x":1e-06},"returns":1e-06},{"arguments":{"max":1,"min":0,"x":null},"returns":null}],"id":"clip","parameters":[{"description":"A number.","name":"x","schema":{"type":["number","null"]}},{"description":"Minimum value. If the value is lower than this value, the process will return the value of this parameter.","name":"min","schema":{"type":"number"}},{"description":"Maximum value. If the value is greater than this value, the process will return the value of this parameter.","name":"max","schema":{"type":"number"}}],"process_graph":{"max":{"arguments":{"data":[{"from_parameter":"min"},{"from_node":"min"}]},"process_id":"max","result":true},"min":{"arguments":{"data":[{"from_parameter":"max"},{"from_parameter":"x"}]},"process_id":"min"}},"returns":{"description":"The value clipped to the specified range.","schema":{"type":["number","null"]}},"summary":"Clip a value between a minimum and a maximum"},{"categories":["math"],"description":"The signum (also known as *sign*) of `x` is defined as:\n\n* *1* if *x > 0*\n* *0* if *x = 0*\n* *-1* if *x < 0*\n\nThe no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"x":-2},"returns":-1},{"arguments":{"x":3.5},"returns":1},{"arguments":{"x":0},"returns":0},{"arguments":{"x":null},"returns":null}],"id":"sgn","links":[{"href":"http://mathworld.wolfram.com/Sign.html","rel":"about","title":"Sign explained by Wolfram MathWorld"}],"parameters":[{"description":"A number.","name":"x","schema":{"type":["number","null"]}}],"process_graph":{"gt0":{"arguments":{"x":{"from_parameter":"x"},"y":0},"process_id":"gt"},"if_gt0":{"arguments":{"accept":1,"reject":{"from_parameter":"x"},"value":{"from_node":"gt0"}},"process_id":"if"},"if_lt0":{"arguments":{"accept":-1,"reject":{"from_node":"if_gt0"},"value":{"from_node":"lt0"}},"process_id":"if","result":true},"lt0":{"arguments":{"x":{"from_parameter":"x"},"y":0},"process_id":"lt"}},"returns":{"description":"The computed signum value of `x`.","schema":{"type":["number","null"]}},"summary":"Signum"},{"categories":["math > statistics"],"description":"Calculates quantiles, which are cut points dividing the range of a sample distribution into either\n\n1. intervals corresponding to the given probabilities *or*\n2. equal-sized intervals (q-quantiles).\n\nEither the parameter `probabilities` or `q` must be specified, otherwise the `QuantilesParameterMissing` exception is thrown. If both parameters are set the `QuantilesParameterConflict` exception is thrown.\n\nSample quantiles can be computed with several different algorithms. Hyndman and Fan (1996) have concluded on nine different types, which are commonly implemented in statistical software packages. This process is implementing type 7, which is implemented widely and often also the default type (e.g. in Excel, Julia, Python, R and S).","examples":[{"arguments":{"data":[2,4,4,4,5,5,7,9],"probabilities":[0.005,0.01,0.02,0.05,0.1,0.5]},"returns":[2.07,2.14,2.28,2.7,3.4,4.5]},{"arguments":{"data":[2,4,4,4,5,5,7,9],"probabilities":4},"returns":[4,4.5,5.5]},{"arguments":{"data":[-1,-0.5,null,1],"probabilities":2},"returns":[-0.5]},{"arguments":{"data":[-1,-0.5,null,1],"ignore_nodata":false,"probabilities":4},"returns":[null,null,null]},{"arguments":{"data":[],"probabilities":[0.1,0.5]},"returns":[null,null],"title":"Empty array"}],"exceptions":{"AscendingProbabilitiesRequired":{"message":"The values passed for parameter `probabilities` must be sorted in ascending order."},"QuantilesParameterConflict":{"message":"The process `quantiles` only allows that either the `probabilities` or the `q` parameter is set."},"QuantilesParameterMissing":{"message":"The process `quantiles` requires either the `probabilities` or `q` parameter to be set."}},"id":"quantiles","links":[{"href":"https://en.wikipedia.org/wiki/Quantile","rel":"about","title":"Quantiles explained by Wikipedia"},{"href":"https://www.amherst.edu/media/view/129116/original/Sample+Quantiles.pdf","rel":"about","title":"Hyndman and Fan (1996): Sample Quantiles in Statistical Packages","type":"application/pdf"}],"parameters":[{"description":"An array of numbers.","name":"data","schema":{"items":{"type":["number","null"]},"type":"array"}},{"description":"Quantiles to calculate. Either a list of probabilities or the number of intervals:\n\n* Provide an array with a sorted list of probabilities in ascending order to calculate quantiles for. The probabilities must be between 0 and 1 (inclusive). If not sorted in ascending order, an `AscendingProbabilitiesRequired` exception is thrown.\n* Provide an integer to specify the number of intervals to calculate quantiles for. Calculates q-quantiles with equal-sized intervals.","name":"probabilities","optional":true,"schema":[{"items":{"maximum":1,"minimum":0,"type":"number"},"title":"List of probabilities","type":"array","uniqueItems":true},{"minimum":2,"title":"Number of intervals (q-quantiles)","type":"integer"}]},{"deprecated":true,"description":"Number of intervals to calculate quantiles for. Calculates q-quantiles with equal-sized intervals.\n\nThis parameter has been **deprecated**. Please use the parameter `probabilities` instead.","name":"q","optional":true,"schema":{"minimum":2,"type":"integer"}},{"default":true,"description":"Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that an array with `null` values is returned if any element is such a value.","name":"ignore_nodata","optional":true,"schema":{"type":"boolean"}}],"returns":{"description":"An array with the computed quantiles. The list has either\n\n* as many elements as the given list of `probabilities` had or\n* *`q`-1* elements.\n\nIf the input array is empty the resulting array is filled with as many `null` values as required according to the list above. See the 'Empty array' example for an example.","schema":{"items":{"type":["number","null"]},"type":"array"}},"summary":"Quantiles"},{"categories":["math > trigonometric"],"description":"Computes the arc sine of `x`. The arc sine is the inverse function of the sine so that *`arcsin(sin(x)) = x`*.\n\nWorks on radians only.\nThe no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"x":0},"returns":0}],"id":"arcsin","links":[{"href":"http://mathworld.wolfram.com/InverseSine.html","rel":"about","title":"Inverse sine explained by Wolfram MathWorld"}],"parameters":[{"description":"A number.","name":"x","schema":{"type":["number","null"]}}],"returns":{"description":"The computed angle in radians.","schema":{"type":["number","null"]}},"summary":"Inverse sine"},{"categories":["arrays","sorting"],"description":"Rearranges an array based on a ranked list of element positions in the original list (i.e., a permutation). The positions must be zero-based. The process ``order()`` can compute such a permutation.","examples":[{"arguments":{"data":[5,4,3],"order":[2,1,0]},"returns":[3,4,5],"title":"Reverse a list"},{"arguments":{"data":[5,4,3,2],"order":[1,3]},"returns":[4,2],"title":"Remove two elements"},{"arguments":{"data":[5,4,3,2],"order":[0,2,1,3]},"returns":[5,3,4,2],"title":"Swap two elements"}],"id":"rearrange","links":[{"href":"http://mathworld.wolfram.com/Permutation.html","rel":"about","title":"Permutation explained by Wolfram MathWorld"}],"parameters":[{"description":"The array to rearrange.","name":"data","schema":{"items":{"description":"Any data type is allowed."},"type":"array"}},{"description":"The permutation used for rearranging.","name":"order","schema":{"items":{"minimum":0,"type":"integer"},"type":"array"}}],"returns":{"description":"The rearranged array.","schema":{"items":{"description":"Any data type is allowed."},"type":"array"}},"summary":"Sort an array based on a permutation"},{"categories":["arrays","comparison","reducer"],"description":"Checks whether the array specified for `data` contains the value specified in `value`. Returns `true` if there's a match, otherwise `false`.\n\n**Remarks:**\n\n* To get the index or the label of the value found, use ``array_find()``.\n* All definitions for the process ``eq()`` regarding the comparison of values apply here as well. A `null` return value from ``eq()`` is handled exactly as `false` (no match).\n* Data types MUST be checked strictly. For example, a string with the content *1* is not equal to the number *1*.\n* An integer *1* is equal to a floating-point number *1.0* as `integer` is a sub-type of `number`. Still, this process may return unexpectedly `false` when comparing floating-point numbers due to floating-point inaccuracy in machine-based computation.\n* Temporal strings are treated as normal strings and MUST NOT be interpreted.","examples":[{"arguments":{"data":[1,2,3],"value":2},"returns":true},{"arguments":{"data":["A","B","C"],"value":"b"},"returns":false},{"arguments":{"data":[1,2,3],"value":"2"},"returns":false},{"arguments":{"data":[1,2,null],"value":null},"returns":false},{"arguments":{"data":[[1,2],[3,4]],"value":2},"returns":false}],"id":"array_contains","links":[{"href":"https://raw.githubusercontent.com/Open-EO/openeo-community-examples/main/processes/array_contains_nodata.json","rel":"example","title":"Check for no-data values in arrays","type":"application/json"}],"parameters":[{"description":"List to find the value in.","name":"data","schema":{"items":{"description":"Any data type is allowed."},"type":"array"}},{"description":"Value to find in `data`. If the value is `null`, this process returns always `false`.","name":"value","schema":{"type":["number","boolean","string","null"]}}],"process_graph":{"find":{"arguments":{"data":{"from_parameter":"data"},"value":{"from_parameter":"value"}},"process_id":"array_find"},"is_nodata":{"arguments":{"x":{"from_node":"find"}},"process_id":"is_nodata"},"not":{"arguments":{"x":{"from_node":"is_nodata"}},"process_id":"not","result":true}},"returns":{"description":"`true` if the list contains the value, false` otherwise.","schema":{"type":"boolean"}},"summary":"Check whether the array contains a given value"},{"categories":["comparison"],"description":"Checks whether the specified data is missing data, i.e. equals to `null` or any of the no-data values specified in the metadata.\n\nThe special numerical value `NaN` (not a number) as defined by the [IEEE Standard 754](https://ieeexplore.ieee.org/document/4610935) is only considered as no-data value if specified as no-data value in the metadata.","examples":[{"arguments":{"x":1},"returns":false},{"arguments":{"x":"Test"},"returns":false},{"arguments":{"x":null},"returns":true},{"arguments":{"x":[null,null]},"returns":false}],"id":"is_nodata","parameters":[{"description":"The data to check.","name":"x","schema":{"description":"Any data type is allowed."}}],"returns":{"description":"`true` if the data is a no-data value, otherwise `false`.","schema":{"type":"boolean"}},"summary":"Value is a no-data value"},{"categories":["comparison"],"description":"Compares whether `x` is strictly greater than `y`.\n\n**Remarks:**\n\n* If any operand is `null`, the return value is `null`.\n* If any operand is not a `number`, the process returns `false`.\n* Temporal strings are normal strings. To compare temporal strings as dates/times, use ``date_difference()``.","examples":[{"arguments":{"x":1,"y":null},"returns":null},{"arguments":{"x":0,"y":0},"returns":false},{"arguments":{"x":2,"y":1},"returns":true},{"arguments":{"x":-0.5,"y":-0.6},"returns":true},{"arguments":{"x":"2018-01-02T00:00:00Z","y":"2018-01-01T00:00:00Z"},"returns":false},{"arguments":{"x":true,"y":0},"returns":false},{"arguments":{"x":true,"y":false},"returns":false},{"arguments":{"x":null,"y":null},"returns":null}],"id":"gt","parameters":[{"description":"First operand.","name":"x","schema":{"type":["number","boolean","string","null"]}},{"description":"Second operand.","name":"y","schema":{"type":["number","boolean","string","null"]}}],"returns":{"description":"`true` if `x` is strictly greater than `y` or `null` if any operand is `null`, otherwise `false`.","schema":{"type":["boolean","null"]}},"summary":"Greater than comparison"},{"categories":["math > exponential & logarithmic"],"description":"The natural logarithm is the logarithm to the base *e* of the number `x`, which equals to using the *log* process with the base set to *e*. The natural logarithm is the inverse function of taking *e* to the power x.\n\nThe no-data value `null` is passed through.\n\nThe computations follow [IEEE Standard 754](https://ieeexplore.ieee.org/document/8766229) whenever the processing environment supports it. Therefore, *`ln(0)`* results in \u00b1infinity if the processing environment supports it or otherwise an exception is thrown.","examples":[{"arguments":{"x":1},"returns":0}],"id":"ln","links":[{"href":"http://mathworld.wolfram.com/NaturalLogarithm.html","rel":"about","title":"Natural logarithm explained by Wolfram MathWorld"},{"href":"https://ieeexplore.ieee.org/document/8766229","rel":"about","title":"IEEE Standard 754-2019 for Floating-Point Arithmetic"}],"parameters":[{"description":"A number to compute the natural logarithm for.","name":"x","schema":{"type":["number","null"]}}],"process_graph":{"e":{"arguments":{},"process_id":"e"},"log":{"arguments":{"base":{"from_node":"e"},"x":{"from_parameter":"x"}},"process_id":"log","result":true}},"returns":{"description":"The computed natural logarithm.","schema":{"type":["number","null"]}},"summary":"Natural logarithm"},{"categories":["math > exponential & logarithmic"],"description":"Logarithm to the base `base` of the number `x` is defined to be the inverse function of taking b to the power of x.\n\nThe no-data value `null` is passed through and therefore gets propagated if any of the arguments is `null`.\n\nThe computations follow [IEEE Standard 754](https://ieeexplore.ieee.org/document/8766229) whenever the processing environment supports it. Therefore, `log(0, 2)` results in \u00b1infinity if the processing environment supports it or otherwise an exception is thrown.","examples":[{"arguments":{"base":10,"x":10},"returns":1},{"arguments":{"base":2,"x":2},"returns":1},{"arguments":{"base":2,"x":4},"returns":2},{"arguments":{"base":16,"x":1},"returns":0}],"id":"log","links":[{"href":"http://mathworld.wolfram.com/Logarithm.html","rel":"about","title":"Logarithm explained by Wolfram MathWorld"},{"href":"https://ieeexplore.ieee.org/document/8766229","rel":"about","title":"IEEE Standard 754-2019 for Floating-Point Arithmetic"}],"parameters":[{"description":"A number to compute the logarithm for.","name":"x","schema":{"type":["number","null"]}},{"description":"The numerical base.","name":"base","schema":{"type":["number","null"]}}],"returns":{"description":"The computed logarithm.","schema":{"type":["number","null"]}},"summary":"Logarithm to a base"},{"categories":["math","math > statistics","reducer"],"description":"Computes the largest value of an array of numbers, which is equal to the first element of a sorted (i.e., ordered) version of the array.\n\nAn array without non-`null` elements resolves always with `null`.","examples":[{"arguments":{"data":[1,0,3,2]},"returns":3},{"arguments":{"data":[5,2.5,null,-0.7]},"returns":5},{"arguments":{"data":[1,0,3,null,2],"ignore_nodata":false},"returns":null},{"arguments":{"data":[]},"description":"The input array is empty: return `null`.","returns":null}],"id":"max","links":[{"href":"http://mathworld.wolfram.com/Maximum.html","rel":"about","title":"Maximum explained by Wolfram MathWorld"}],"parameters":[{"description":"An array of numbers.","name":"data","schema":{"items":{"type":["number","null"]},"type":"array"}},{"default":true,"description":"Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value.","name":"ignore_nodata","optional":true,"schema":{"type":"boolean"}}],"returns":{"description":"The maximum value.","schema":{"type":["number","null"]}},"summary":"Maximum value"},{"categories":["comparison"],"description":"Compares whether `x` is strictly less than `y`.\n\n**Remarks:**\n\n* If any operand is `null`, the return value is `null`.\n* If any operand is not a `number`, the process returns `false`.\n* Temporal strings are normal strings. To compare temporal strings as dates/times, use ``date_difference()``.","examples":[{"arguments":{"x":1,"y":null},"returns":null},{"arguments":{"x":0,"y":0},"returns":false},{"arguments":{"x":1,"y":2},"returns":true},{"arguments":{"x":-0.5,"y":-0.6},"returns":false},{"arguments":{"x":"2018-01-01T00:00:00Z","y":"2018-01-02T00:00:00Z"},"returns":false},{"arguments":{"x":0,"y":true},"returns":false},{"arguments":{"x":false,"y":true},"returns":false},{"arguments":{"x":null,"y":null},"returns":null}],"id":"lt","parameters":[{"description":"First operand.","name":"x","schema":{"type":["number","boolean","string","null"]}},{"description":"Second operand.","name":"y","schema":{"type":["number","boolean","string","null"]}}],"returns":{"description":"`true` if `x` is strictly less than `y`, `null` if any operand is `null`, otherwise `false`.","schema":{"type":["boolean","null"]}},"summary":"Less than comparison"},{"categories":["cubes","import"],"description":"Loads a collection from the current back-end by its id and returns it as a processable data cube. The data that is added to the data cube can be restricted with the parameters `spatial_extent`, `temporal_extent`, `bands` and `properties`. If no data is available for the given extents, a `NoDataAvailable` exception is thrown.\n\n**Remarks:**\n\n* The bands (and all dimensions that specify nominal dimension labels) are expected to be ordered as specified in the metadata if the `bands` parameter is set to `null`.\n* If no additional parameter is specified this would imply that the whole data set is expected to be loaded. Due to the large size of many data sets, this is not recommended and may be optimized by back-ends to only load the data that is actually required after evaluating subsequent processes such as filters. This means that the values in the data cube should be processed only after the data has been limited to the required extent and as a consequence also to a manageable size.","examples":[{"arguments":{"id":"Sentinel-2","properties":{"eo:cloud_cover":{"process_graph":{"cc":{"arguments":{"max":50,"min":0,"x":{"from_parameter":"value"}},"process_id":"between","result":true}}},"platform":{"process_graph":{"pf":{"arguments":{"case_sensitive":false,"x":{"from_parameter":"value"},"y":"Sentinel-2B"},"process_id":"eq","result":true}}}},"spatial_extent":{"east":16.6,"north":48.6,"south":47.2,"west":16.1},"temporal_extent":["2018-01-01","2019-01-01"]},"description":"Loading `Sentinel-2B` data from a `Sentinel-2` collection for 2018, but only with cloud cover between 0 and 50%."}],"exceptions":{"NoDataAvailable":{"message":"There is no data available for the given extents."},"TemporalExtentEmpty":{"message":"The temporal extent is empty. The second instant in time must always be greater/later than the first instant in time."}},"id":"load_collection","links":[{"href":"https://openeo.org/documentation/1.0/datacubes.html","rel":"about","title":"Data Cubes explained in the openEO documentation"},{"href":"https://proj.org/usage/projections.html","rel":"about","title":"PROJ parameters for cartographic projections"},{"href":"http://www.epsg-registry.org","rel":"about","title":"Official EPSG code registry"},{"href":"http://www.epsg.io","rel":"about","title":"Unofficial EPSG code database"},{"href":"http://www.opengeospatial.org/standards/sfa","rel":"about","title":"Simple Features standard by the OGC"},{"href":"https://github.com/radiantearth/stac-spec/tree/master/extensions/eo#common-band-names","rel":"about","title":"List of common band names as specified by the STAC specification"},{"href":"https://www.rfc-editor.org/rfc/rfc3339.html","rel":"about","title":"RFC3339: Details about formatting temporal strings"}],"parameters":[{"description":"The collection id.","name":"id","schema":{"pattern":"^[\\w\\-\\.~/]+$","subtype":"collection-id","type":"string"}},{"description":"Limits the data to load from the collection to the specified bounding box or polygons.\n\n* For raster data, the process loads the pixel into the data cube if the point at the pixel center intersects with the bounding box or any of the polygons (as defined in the Simple Features standard by the OGC).\n* For vector data, the process loads the geometry into the data cube if the geometry is fully *within* the bounding box or any of the polygons (as defined in the Simple Features standard by the OGC). Empty geometries may only be in the data cube if no spatial extent has been provided.\n\nThe GeoJSON can be one of the following feature types:\n\n* A `Polygon` or `MultiPolygon` geometry,\n* a `Feature` with a `Polygon` or `MultiPolygon` geometry, or\n* a `FeatureCollection` containing at least one `Feature` with `Polygon` or `MultiPolygon` geometries.\n* Empty geometries are ignored.\n\nSet this parameter to `null` to set no limit for the spatial extent. Be careful with this when loading large datasets! It is recommended to use this parameter instead of using ``filter_bbox()`` or ``filter_spatial()`` directly after loading unbounded data.","name":"spatial_extent","schema":[{"properties":{"base":{"default":null,"description":"Base (optional, lower left corner, coordinate axis 3).","type":["number","null"]},"crs":{"anyOf":[{"examples":[3857],"minimum":1000,"subtype":"epsg-code","title":"EPSG Code","type":"integer"},{"subtype":"wkt2-definition","title":"WKT2","type":"string"}],"default":4326,"description":"Coordinate reference system of the extent, specified as as [EPSG code](http://www.epsg-registry.org/) or [WKT2 CRS string](http://docs.opengeospatial.org/is/18-010r7/18-010r7.html). Defaults to `4326` (EPSG code 4326) unless the client explicitly requests a different coordinate reference system."},"east":{"description":"East (upper right corner, coordinate axis 1).","type":"number"},"height":{"default":null,"description":"Height (optional, upper right corner, coordinate axis 3).","type":["number","null"]},"north":{"description":"North (upper right corner, coordinate axis 2).","type":"number"},"south":{"description":"South (lower left corner, coordinate axis 2).","type":"number"},"west":{"description":"West (lower left corner, coordinate axis 1).","type":"number"}},"required":["west","south","east","north"],"subtype":"bounding-box","title":"Bounding Box","type":"object"},{"deprecated":true,"description":"Deprecated in favor of ``load_geojson()``. Limits the data cube to the bounding box of the given geometries. For raster data, all pixels inside the bounding box that do not intersect with any of the polygons will be set to no data (`null`).\n\nThe GeoJSON type `GeometryCollection` is not supported. Empty geometries are ignored.","subtype":"geojson","title":"GeoJSON","type":"object"},{"description":"Limits the data cube to the bounding box of the given geometries in the vector data cube. For raster data, all pixels inside the bounding box that do not intersect with any of the polygons will be set to no data (`null`). Empty geometries are ignored.","dimensions":[{"type":"geometry"}],"subtype":"datacube","title":"Vector data cube","type":"object"},{"description":"Don't filter spatially. All data is included in the data cube.","title":"No filter","type":"null"}]},{"description":"Limits the data to load from the collection to the specified left-closed temporal interval. Applies to all temporal dimensions. The interval has to be specified as an array with exactly two elements:\n\n1. The first element is the start of the temporal interval. The specified time instant is **included** in the interval.\n2. The second element is the end of the temporal interval. The specified time instant is **excluded** from the interval.\n\nThe second element must always be greater/later than the first element. Otherwise, a `TemporalExtentEmpty` exception is thrown.\n\nAlso supports unbounded intervals by setting one of the boundaries to `null`, but never both.\n\nSet this parameter to `null` to set no limit for the temporal extent. Be careful with this when loading large datasets! It is recommended to use this parameter instead of using ``filter_temporal()`` directly after loading unbounded data.","name":"temporal_extent","schema":[{"examples":[["2015-01-01T00:00:00Z","2016-01-01T00:00:00Z"],["2015-01-01","2016-01-01"]],"items":{"anyOf":[{"description":"Date and time with a time zone.","format":"date-time","subtype":"date-time","type":"string"},{"description":"Date only, formatted as `YYYY-MM-DD`. The time zone is UTC. Missing time components are all 0.","format":"date","subtype":"date","type":"string"},{"type":"null"}]},"maxItems":2,"minItems":2,"subtype":"temporal-interval","type":"array","uniqueItems":true},{"description":"Don't filter temporally. All data is included in the data cube.","title":"No filter","type":"null"}]},{"default":null,"description":"Only adds the specified bands into the data cube so that bands that don't match the list of band names are not available. Applies to all dimensions of type `bands`.\n\nEither the unique band name (metadata field `name` in bands) or one of the common band names (metadata field `common_name` in bands) can be specified. If the unique band name and the common name conflict, the unique band name has a higher priority.\n\nThe order of the specified array defines the order of the bands in the data cube. If multiple bands match a common name, all matched bands are included in the original order.\n\nIt is recommended to use this parameter instead of using ``filter_bands()`` directly after loading unbounded data.","name":"bands","optional":true,"schema":[{"items":{"subtype":"band-name","type":"string"},"minItems":1,"type":"array"},{"description":"Don't filter bands. All bands are included in the data cube.","title":"No filter","type":"null"}]},{"default":null,"description":"Limits the data by metadata properties to include only data in the data cube which all given conditions return `true` for (AND operation).\n\nSpecify key-value-pairs with the key being the name of the metadata property, which can be retrieved with the openEO Data Discovery for Collections. The value must be a condition (user-defined process) to be evaluated against the collection metadata, see the example.","name":"properties","optional":true,"schema":[{"additionalProperties":{"parameters":[{"description":"The property value to be checked against.","name":"value","schema":{"description":"Any data type."}}],"returns":{"description":"`true` if the data should be loaded into the data cube, otherwise `false`.","schema":{"type":"boolean"}},"subtype":"process-graph","type":"object"},"description":"A list of filters to check against. Specify key-value-pairs with the key being the name of the metadata property name and the value being a process evaluated against the metadata values.","subtype":"metadata-filter","title":"Filters","type":"object"},{"description":"Don't filter by metadata properties.","title":"No filter","type":"null"}]}],"returns":{"description":"A data cube for further processing. The dimensions and dimension properties (name, type, labels, reference system and resolution) correspond to the collection's metadata, but the dimension labels are restricted as specified in the parameters.","schema":{"subtype":"datacube","type":"object"}},"summary":"Load a collection"},{"categories":["import"],"description":"Queries a STAC to construct a FeatureCollection of STAC Items with the results","examples":[{"arguments":{"spatial_extent":{"east":16.6,"north":48.6,"south":47.2,"west":16.1},"temporal_extent":["2018-01-01","2019-01-01"],"url":"https://example.com/collections/SENTINEL2"},"title":"Load from a STAC API"}],"experimental":true,"id":"query_stac","links":[{"href":"https://proj.org/usage/projections.html","rel":"about","title":"PROJ parameters for cartographic projections"},{"href":"http://www.epsg-registry.org","rel":"about","title":"Official EPSG code registry"},{"href":"http://www.epsg.io","rel":"about","title":"Unofficial EPSG code database"},{"href":"http://www.opengeospatial.org/standards/sfa","rel":"about","title":"Simple Features standard by the OGC"},{"href":"https://www.rfc-editor.org/rfc/rfc3339.html","rel":"about","title":"RFC3339: Details about formatting temporal strings"}],"parameters":[{"description":"The URL to a static STAC Collection","name":"url","schema":{"format":"uri","pattern":"^https?://","subtype":"uri","title":"URL","type":"string"}},{"description":"Limits the data to load to the specified bounding box.","name":"spatial_extent","optional":false,"schema":[{"properties":{"base":{"default":null,"description":"Base (optional, lower left corner, coordinate axis 3).","type":["number","null"]},"crs":{"anyOf":[{"examples":[3857],"minimum":1000,"subtype":"epsg-code","title":"EPSG Code","type":"integer"},{"subtype":"wkt2-definition","title":"WKT2","type":"string"}],"default":4326,"description":"Coordinate reference system of the extent, specified as as [EPSG code](http://www.epsg-registry.org/) or [WKT2 CRS string](http://docs.opengeospatial.org/is/18-010r7/18-010r7.html). Defaults to `4326` (EPSG code 4326) unless the client explicitly requests a different coordinate reference system."},"east":{"description":"East (upper right corner, coordinate axis 1).","type":"number"},"height":{"default":null,"description":"Height (optional, upper right corner, coordinate axis 3).","type":["number","null"]},"north":{"description":"North (upper right corner, coordinate axis 2).","type":"number"},"south":{"description":"South (lower left corner, coordinate axis 2).","type":"number"},"west":{"description":"West (lower left corner, coordinate axis 1).","type":"number"}},"required":["west","south","east","north"],"subtype":"bounding-box","title":"Bounding Box","type":"object"}]},{"description":"Limits the data to load to the specified left-closed temporal interval. Applies to all temporal dimensions. The interval has to be specified as an array with exactly two elements:\n\n1. The first element is the start of the temporal interval. The specified instance in time is **included** in the interval.\n2. The second element is the end of the temporal interval. The specified instance in time is **excluded** from the interval.\n\nThe second element must always be greater/later than the first element. Otherwise, a `TemporalExtentEmpty` exception is thrown.\n\nAlso supports open intervals by setting one of the boundaries to `null`, but never both.","name":"temporal_extent","optional":false,"schema":[{"examples":[["2015-01-01T00:00:00Z","2016-01-01T00:00:00Z"],["2015-01-01","2016-01-01"]],"items":{"anyOf":[{"description":"Date and time with a time zone.","format":"date-time","subtype":"date-time","type":"string"},{"description":"Date only, formatted as `YYYY-MM-DD`. The time zone is UTC. Missing time components are all 0.","format":"date","subtype":"date","type":"string"},{"type":"null"}]},"maxItems":2,"minItems":2,"subtype":"temporal-interval","type":"array","uniqueItems":true}]}],"returns":{"description":"A GeoJSON FeatureCollection ","schema":{"subtype":"geojson","type":"object"}},"summary":"Queries STAC"},{"categories":["cubes","export"],"description":"Makes the processed data available in the given file format to the corresponding medium that is relevant for the context this processes is applied in:\n\n* For **batch jobs** the data is stored on the back-end. STAC-compatible metadata is usually made available with the processed data.\n* For **synchronous processing** the data is sent to the client as a direct response to the request.\n* **Secondary web services** are provided with the processed data so that it can make use of it (e.g., visualize it). Web service may require the data in a certain format. Please refer to the documentation of the individual service types for details.","exceptions":{"DataCubeEmpty":{"message":"The file format doesn't support storing empty data cubes."},"FormatUnsuitable":{"message":"Data can't be transformed into the requested output format."}},"id":"save_result","links":[{"href":"https://gdal.org/drivers/raster/index.html","rel":"about","title":"GDAL Raster Formats"},{"href":"https://gdal.org/drivers/vector/index.html","rel":"about","title":"OGR Vector Formats"}],"parameters":[{"description":"The data to deliver in the given file format.","name":"data","schema":{"subtype":"datacube","type":"object"}},{"description":"The file format to use. It must be one of the values that the server reports as supported output file formats, which usually correspond to the short GDAL/OGR codes. This parameter is *case insensitive*.\n\n* If the data cube is empty and the file format can't store empty data cubes, a `DataCubeEmpty` exception is thrown.\n* If the file format is otherwise not suitable for storing the underlying data structure, a `FormatUnsuitable` exception is thrown.","name":"format","schema":{"subtype":"output-format","type":"string"}},{"default":{},"description":"The file format parameters to be used to create the file(s). Must correspond to the parameters that the server reports as supported parameters for the chosen `format`. The parameter names and valid values usually correspond to the GDAL/OGR format options.","name":"options","optional":true,"schema":{"subtype":"output-format-options","type":"object"}}],"returns":{"description":"Always returns `true` as in case of an error an exception is thrown which aborts the execution of the process.","schema":{"const":true,"type":"boolean"}},"summary":"Save processed data"},{"categories":["machine learning","import"],"description":"Saves a machine learning model as part of a batch job.\n\nThe model will be accompanied by a separate STAC Item that implements the [ml-model extension](https://github.com/stac-extensions/ml-model).","experimental":true,"id":"save_ml_model","links":[{"href":"https://github.com/stac-extensions/ml-model","rel":"about","title":"STAC ml-model extension","type":"text/html"}],"parameters":[{"description":"The data to store as a machine learning model.","name":"data","schema":{"subtype":"ml-model","type":"object"}},{"default":{},"description":"Additional parameters to create the file(s).","name":"options","optional":true,"schema":{"additionalParameters":false,"type":"object"}}],"returns":{"description":"Returns `false` if the process failed to store the model, `true` otherwise.","schema":{"type":"boolean"}},"summary":"Save a ML model"},{"categories":["machine learning","import"],"description":"Loads a machine learning model from a STAC Item.\n\nSuch a model could be trained and saved as part of a previous batch job with processes such as ``fit_random_forest()`` and ``save_ml_model()``.","experimental":true,"id":"load_ml_model","links":[{"href":"https://github.com/stac-extensions/ml-model","rel":"about","title":"STAC ml-model extension","type":"text/html"}],"parameters":[{"description":"The STAC Item to load the machine learning model from. The STAC Item must implement the `ml-model` extension.","name":"id","schema":[{"format":"uri","pattern":"^https?://","subtype":"uri","title":"URL","type":"string"},{"description":"Loading a model by batch job ID is possible only if a single model has been saved by the job. Otherwise, you have to load a specific model from a batch job by URL.","pattern":"^[\\w\\-\\.~]+$","subtype":"job-id","title":"Batch Job ID","type":"string"},{"pattern":"^[^\r\n\\:'\"]+$","subtype":"file-path","title":"User-uploaded Files","type":"string"}]}],"returns":{"description":"A machine learning model to be used with machine learning processes such as ``predict_random_forest()``.","schema":{"subtype":"ml-model","type":"object"}},"summary":"Load a ML model"},{"categories":["cubes","import"],"description":"Loads one or more user-uploaded files from the server-side workspace of the authenticated user and returns them as a single data cube. The files must have been stored by the authenticated user on the back-end currently connected to.","exceptions":{"FormatUnsuitable":{"message":"Data can't be loaded with the requested input format."}},"experimental":true,"id":"load_uploaded_files","parameters":[{"description":"The files to read. Folders can't be specified, specify all files instead. An exception is thrown if a file can't be read.","name":"paths","schema":{"items":{"pattern":"^[^\r\n\\:'\"]+$","subtype":"file-path","type":"string"},"subtype":"file-paths","type":"array"}},{"description":"The file format to read from. It must be one of the values that the server reports as supported input file formats, which usually correspond to the short GDAL/OGR codes. If the format is not suitable for loading the data, a `FormatUnsuitable` exception will be thrown. This parameter is *case insensitive*.","name":"format","schema":{"subtype":"input-format","type":"string"}},{"default":{},"description":"The file format parameters to be used to read the files. Must correspond to the parameters that the server reports as supported parameters for the chosen `format`. The parameter names and valid values usually correspond to the GDAL/OGR format options.","name":"options","optional":true,"schema":{"subtype":"input-format-options","type":"object"}}],"returns":{"description":"A data cube for further processing.","schema":{"subtype":"datacube","type":"object"}},"summary":"Load files from the user workspace"},{"categories":["import","vector"],"description":"Converts GeoJSON data as defined by [RFC 7946](https://www.rfc-editor.org/rfc/rfc7946.html) into a vector data cube. Feature properties are preserved.","experimental":true,"id":"load_geojson","links":[{"href":"https://www.rfc-editor.org/rfc/rfc7946.html","rel":"about","title":"RFC 7946: The GeoJSON Format","type":"text/html"}],"parameters":[{"description":"A GeoJSON object to convert into a vector data cube. The GeoJSON type `GeometryCollection` is not supported. Each geometry in the GeoJSON data results in a dimension label in the `geometries` dimension.","name":"data","schema":{"subtype":"geojson","type":"object"}},{"default":[],"description":"A list of properties from the GeoJSON file to construct an additional dimension from. A new dimension with the name `properties` and type `other` is created if at least one property is provided. Only applies for GeoJSON Features and FeatureCollections. Missing values are generally set to no-data (`null`).\n\nDepending on the number of properties provided, the process creates the dimension differently:\n\n- Single property with scalar values: A single dimension label with the name of the property and a single value per geometry.\n- Single property of type array: The dimension labels correspond to the array indices. There are as many values and labels per geometry as there are for the largest array.\n- Multiple properties with scalar values: The dimension labels correspond to the property names. There are as many values and labels per geometry as there are properties provided here.","name":"properties","optional":true,"schema":{"items":{"type":"string"},"type":"array","uniqueItems":true}}],"returns":{"description":"A vector data cube containing the geometries, either one or two dimensional.","schema":{"dimensions":[{"type":"geometry"}],"subtype":"datacube","type":"object"}},"summary":"Converts GeoJSON into a vector data cube"},{"categories":["cubes","import"],"description":"Loads a file from a URL (supported protocols: HTTP and HTTPS).","exceptions":{"FormatUnsuitable":{"message":"Data can't be loaded with the requested input format."}},"experimental":true,"id":"load_url","parameters":[{"description":"The URL to read from. Authentication details such as API keys or tokens may need to be included in the URL.","name":"url","schema":{"format":"uri","pattern":"^https?://","subtype":"uri","title":"URL","type":"string"}},{"description":"The file format to use when loading the data. It must be one of the values that the server reports as supported input file formats, which usually correspond to the short GDAL/OGR codes. If the format is not suitable for loading the data, a `FormatUnsuitable` exception will be thrown. This parameter is *case insensitive*.","name":"format","schema":{"subtype":"input-format","type":"string"}},{"default":{},"description":"The file format parameters to use when reading the data. Must correspond to the parameters that the server reports as supported parameters for the chosen `format`. The parameter names and valid values usually correspond to the GDAL/OGR format options.","name":"options","optional":true,"schema":{"subtype":"input-format-options","type":"object"}}],"returns":{"description":"A data cube for further processing.","schema":{"subtype":"datacube","type":"object"}},"summary":"Load data from a URL"},{"categories":["cubes","import"],"description":"Loads data from a static STAC catalog or a STAC API Collection and returns the data as a processable data cube. A batch job result can be loaded by providing a reference to it.\n\nIf supported by the underlying metadata and file format, the data that is added to the data cube can be restricted with the parameters `spatial_extent`, `temporal_extent` and `bands`. If no data is available for the given extents, a `NoDataAvailable` exception is thrown.\n\n**Remarks:**\n\n* The bands (and all dimensions that specify nominal dimension labels) are expected to be ordered as specified in the metadata if the `bands` parameter is set to `null`.\n* If no additional parameter is specified this would imply that the whole data set is expected to be loaded. Due to the large size of many data sets, this is not recommended and may be optimized by back-ends to only load the data that is actually required after evaluating subsequent processes such as filters. This means that the values should be processed only after the data has been limited to the required extent and as a consequence also to a manageable size.","examples":[{"arguments":{"url":"https://example.com/api/v1.0/jobs/123/results"},"title":"Load from a static STAC / batch job result"},{"arguments":{"properties":{"eo:cloud_cover":{"process_graph":{"cc":{"arguments":{"max":50,"min":0,"x":{"from_parameter":"value"}},"process_id":"between","result":true}}},"platform":{"process_graph":{"pf":{"arguments":{"case_sensitive":false,"x":{"from_parameter":"value"},"y":"Sentinel-2B"},"process_id":"eq","result":true}}}},"spatial_extent":{"east":16.6,"north":48.6,"south":47.2,"west":16.1},"temporal_extent":["2018-01-01","2019-01-01"],"url":"https://example.com/collections/SENTINEL2"},"title":"Load from a STAC API"}],"exceptions":{"NoDataAvailable":{"message":"There is no data available for the given extents."},"TemporalExtentEmpty":{"message":"The temporal extent is empty. The second instant in time must always be greater/later than the first instant in time."}},"experimental":true,"id":"load_stac","links":[{"href":"https://openeo.org/documentation/1.0/datacubes.html","rel":"about","title":"Data Cubes explained in the openEO documentation"},{"href":"https://proj.org/usage/projections.html","rel":"about","title":"PROJ parameters for cartographic projections"},{"href":"http://www.epsg-registry.org","rel":"about","title":"Official EPSG code registry"},{"href":"http://www.epsg.io","rel":"about","title":"Unofficial EPSG code database"},{"href":"http://www.opengeospatial.org/standards/sfa","rel":"about","title":"Simple Features standard by the OGC"},{"href":"https://github.com/radiantearth/stac-spec/tree/master/extensions/eo#common-band-names","rel":"about","title":"List of common band names as specified by the STAC specification"},{"href":"https://www.rfc-editor.org/rfc/rfc3339.html","rel":"about","title":"RFC3339: Details about formatting temporal strings"}],"parameters":[{"description":"The URL to a static STAC catalog (STAC Item, STAC Collection, or STAC Catalog) or a specific STAC API Collection that allows to filter items and to download assets. This includes batch job results, which itself are compliant to STAC. For external URLs, authentication details such as API keys or tokens may need to be included in the URL.\n\nBatch job results can be specified in two ways:\n\n- For Batch job results at the same back-end, a URL pointing to the corresponding batch job results endpoint should be provided. The URL usually ends with `/jobs/{id}/results` and `{id}` is the corresponding batch job ID.\n- For external results, a signed URL must be provided. Not all back-ends support signed URLs, which are provided as a link with the link relation `canonical` in the batch job result metadata.","name":"url","schema":{"format":"uri","pattern":"^https?://","subtype":"uri","title":"URL","type":"string"}},{"default":null,"description":"Limits the data to load to the specified bounding box or polygons.\n\n* For raster data, the process loads the pixel into the data cube if the point at the pixel center intersects with the bounding box or any of the polygons (as defined in the Simple Features standard by the OGC).\n* For vector data, the process loads the geometry into the data cube if the geometry is fully within the bounding box or any of the polygons (as defined in the Simple Features standard by the OGC). Empty geometries may only be in the data cube if no spatial extent has been provided.\n\nThe GeoJSON can be one of the following feature types:\n\n* A `Polygon` or `MultiPolygon` geometry,\n* a `Feature` with a `Polygon` or `MultiPolygon` geometry, or\n* a `FeatureCollection` containing at least one `Feature` with `Polygon` or `MultiPolygon` geometries.\n\nSet this parameter to `null` to set no limit for the spatial extent. Be careful with this when loading large datasets! It is recommended to use this parameter instead of using ``filter_bbox()`` or ``filter_spatial()`` directly after loading unbounded data.","name":"spatial_extent","optional":true,"schema":[{"properties":{"base":{"default":null,"description":"Base (optional, lower left corner, coordinate axis 3).","type":["number","null"]},"crs":{"anyOf":[{"examples":[3857],"minimum":1000,"subtype":"epsg-code","title":"EPSG Code","type":"integer"},{"subtype":"wkt2-definition","title":"WKT2","type":"string"}],"default":4326,"description":"Coordinate reference system of the extent, specified as as [EPSG code](http://www.epsg-registry.org/) or [WKT2 CRS string](http://docs.opengeospatial.org/is/18-010r7/18-010r7.html). Defaults to `4326` (EPSG code 4326) unless the client explicitly requests a different coordinate reference system."},"east":{"description":"East (upper right corner, coordinate axis 1).","type":"number"},"height":{"default":null,"description":"Height (optional, upper right corner, coordinate axis 3).","type":["number","null"]},"north":{"description":"North (upper right corner, coordinate axis 2).","type":"number"},"south":{"description":"South (lower left corner, coordinate axis 2).","type":"number"},"west":{"description":"West (lower left corner, coordinate axis 1).","type":"number"}},"required":["west","south","east","north"],"subtype":"bounding-box","title":"Bounding Box","type":"object"},{"description":"Limits the data cube to the bounding box of the given geometries. For raster data, all pixels inside the bounding box that do not intersect with any of the polygons will be set to no data (`null`).\n\nThe GeoJSON type `GeometryCollection` is not supported. Empty geometries are ignored.","subtype":"geojson","title":"GeoJSON","type":"object"},{"description":"Limits the data cube to the bounding box of the given geometries in the vector data cube. All pixels inside the bounding box that do not intersect with any of the polygons will be set to no data (`null`). Empty geometries are ignored.","dimensions":[{"type":"geometry"}],"subtype":"datacube","title":"Vector data cube","type":"object"},{"description":"Don't filter spatially. All data is included in the data cube.","title":"No filter","type":"null"}]},{"default":null,"description":"Limits the data to load to the specified left-closed temporal interval. Applies to all temporal dimensions. The interval has to be specified as an array with exactly two elements:\n\n1. The first element is the start of the temporal interval. The specified instance in time is **included** in the interval.\n2. The second element is the end of the temporal interval. The specified instance in time is **excluded** from the interval.\n\nThe second element must always be greater/later than the first element. Otherwise, a `TemporalExtentEmpty` exception is thrown.\n\nAlso supports open intervals by setting one of the boundaries to `null`, but never both.\n\nSet this parameter to `null` to set no limit for the temporal extent. Be careful with this when loading large datasets! It is recommended to use this parameter instead of using ``filter_temporal()`` directly after loading unbounded data.","name":"temporal_extent","optional":true,"schema":[{"examples":[["2015-01-01T00:00:00Z","2016-01-01T00:00:00Z"],["2015-01-01","2016-01-01"]],"items":{"anyOf":[{"description":"Date and time with a time zone.","format":"date-time","subtype":"date-time","type":"string"},{"description":"Date only, formatted as `YYYY-MM-DD`. The time zone is UTC. Missing time components are all 0.","format":"date","subtype":"date","type":"string"},{"type":"null"}]},"maxItems":2,"minItems":2,"subtype":"temporal-interval","type":"array","uniqueItems":true},{"description":"Don't filter temporally. All data is included in the data cube.","title":"No filter","type":"null"}]},{"default":null,"description":"Only adds the specified bands into the data cube so that bands that don't match the list of band names are not available. Applies to all dimensions of type `bands`.\n\nEither the unique band name (metadata field `name` in bands) or one of the common band names (metadata field `common_name` in bands) can be specified. If the unique band name and the common name conflict, the unique band name has a higher priority.\n\nThe order of the specified array defines the order of the bands in the data cube. If multiple bands match a common name, all matched bands are included in the original order.\n\nIt is recommended to use this parameter instead of using ``filter_bands()`` directly after loading unbounded data.","name":"bands","optional":true,"schema":[{"items":{"subtype":"band-name","type":"string"},"minItems":1,"type":"array"},{"description":"Don't filter bands. All bands are included in the data cube.","title":"No filter","type":"null"}]},{"default":null,"description":"Limits the data by metadata properties to include only data in the data cube which all given conditions return `true` for (AND operation).\n\nSpecify key-value-pairs with the key being the name of the metadata property, which can be retrieved with the openEO Data Discovery for Collections. The value must be a condition (user-defined process) to be evaluated against a STAC API. This parameter is not supported for static STAC.","name":"properties","optional":true,"schema":[{"additionalProperties":{"parameters":[{"description":"The property value to be checked against.","name":"value","schema":{"description":"Any data type."}}],"returns":{"description":"`true` if the data should be loaded into the data cube, otherwise `false`.","schema":{"type":"boolean"}},"subtype":"process-graph","type":"object"},"description":"A list of filters to check against. Specify key-value-pairs with the key being the name of the metadata property name and the value being a process evaluated against the metadata values.","subtype":"metadata-filter","title":"Filters","type":"object"},{"description":"Don't filter by metadata properties.","title":"No filter","type":"null"}]}],"returns":{"description":"A data cube for further processing.","schema":{"subtype":"datacube","type":"object"}},"summary":"Loads data from STAC"},{"categories":["export","stac"],"description":"Exports the given processing results made available through a STAC resource (e.g., a STAC Collection) to the given user workspace. The STAC resource itself is exported with all STAC resources and assets underneath.","experimental":true,"id":"export_workspace","parameters":[{"description":"The data to export to the user workspace as a STAC resource.","name":"data","schema":{"subtype":"stac","type":"object"}},{"description":"The identifier of the workspace to export to.","name":"workspace","schema":{"pattern":"^[\\w\\-\\.~]+$","subtype":"workspace-id","type":"string"}},{"default":null,"description":"Provides a cloud-specific path identifier to a STAC resource to merge the given STAC resource into. If not provided, the STAC resource is kept separate from any other STAC resources in the workspace.","name":"merge","optional":true,"schema":{"type":["string","null"]}}],"returns":{"description":"Returns the potentially updated STAC resource.","schema":{"subtype":"stac","type":"object"}},"summary":"Export data to a cloud user workspace"},{"categories":["cubes"],"description":"Applies a process to each value in the data cube (i.e. a local operation). In contrast, the process ``apply_dimension()`` applies a process to all values along a particular dimension.","id":"apply","links":[{"href":"https://openeo.org/documentation/1.0/datacubes.html#apply","rel":"about","title":"Apply explained in the openEO documentation"}],"parameters":[{"description":"A data cube.","name":"data","schema":{"subtype":"datacube","type":"object"}},{"description":"A process that accepts and returns a single value and is applied on each individual value in the data cube. The process may consist of multiple sub-processes and could, for example, consist of processes such as ``absolute()`` or ``linear_scale_range()``.","name":"process","schema":{"parameters":[{"description":"The value to process.","name":"x","schema":{"description":"Any data type."}},{"default":null,"description":"Additional data passed by the user.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"The value to be set in the new data cube.","schema":{"description":"Any data type."}},"subtype":"process-graph","type":"object"}},{"default":null,"description":"Additional data to be passed to the process.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"A data cube with the newly computed values and the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged.","schema":{"subtype":"datacube","type":"object"}},"summary":"Apply a process to each value"},{"categories":["cubes"],"description":"Applies a process to all values along a dimension of a data cube. For example, if the temporal dimension is specified the process will work on the values of a time series.\n\nThe process ``reduce_dimension()`` also applies a process to values along a dimension, but drops the dimension afterwards. The process ``apply()`` applies a process to each value in the data cube.\n\nThe target dimension is the source dimension if not specified otherwise in the `target_dimension` parameter. The values in the target dimension get replaced by the computed values. The name, type and reference system are preserved.\n\nThe dimension labels are preserved when the target dimension is the source dimension and the number of values in the source dimension is equal to the number of values computed by the process. Otherwise, the dimension labels will be incrementing integers starting from zero, which can be changed using ``rename_labels()`` afterwards. The number of labels will be equal to the number of values computed by the process.","exceptions":{"DimensionNotAvailable":{"message":"A dimension with the specified name does not exist."}},"id":"apply_dimension","links":[{"href":"https://openeo.org/documentation/1.0/datacubes.html#apply","rel":"about","title":"Apply explained in the openEO documentation"}],"parameters":[{"description":"A data cube.","name":"data","schema":{"subtype":"datacube","type":"object"}},{"description":"Process to be applied on all values along the given dimension. The specified process needs to accept an array and must return an array with at least one element. A process may consist of multiple sub-processes.","name":"process","schema":{"parameters":[{"description":"A labeled array with elements of any type.","name":"data","schema":{"items":{"description":"Any data type."},"subtype":"labeled-array","type":"array"}},{"default":null,"description":"Additional data passed by the user.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"The value to be set in the new data cube.","schema":{"items":{"description":"Any data type."},"type":"array"}},"subtype":"process-graph","type":"object"}},{"description":"The name of the source dimension to apply the process on. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist.","name":"dimension","schema":{"type":"string"}},{"default":null,"description":"The name of the target dimension or `null` (the default) to use the source dimension specified in the parameter `dimension`.\n\nBy specifying a target dimension, the source dimension is removed. The target dimension with the specified name and the type `other` (see ``add_dimension()``) is created, if it doesn't exist yet.","name":"target_dimension","optional":true,"schema":{"type":["string","null"]}},{"default":null,"description":"Additional data to be passed to the process.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"A data cube with the newly computed values.\n\nAll dimensions stay the same, except for the dimensions specified in corresponding parameters. There are three cases how the dimensions can change:\n\n1. The source dimension is the target dimension:\n   - The (number of) dimensions remain unchanged as the source dimension is the target dimension.\n   - The source dimension properties name and type remain unchanged.\n   - The dimension labels, the reference system and the resolution are preserved only if the number of values in the source dimension is equal to the number of values computed by the process. Otherwise, all other dimension properties change as defined in the list below.\n2. The source dimension is not the target dimension. The target dimension exists with a single label only:\n   - The number of dimensions decreases by one as the source dimension is 'dropped' and the target dimension is filled with the processed data that originates from the source dimension.\n   - The target dimension properties name and type remain unchanged. All other dimension properties change as defined in the list below.\n3. The source dimension is not the target dimension and the latter does not exist:\n   - The number of dimensions remain unchanged, but the source dimension is replaced with the target dimension.\n   - The target dimension has the specified name and the type other. All other dimension properties are set as defined in the list below.\n\nUnless otherwise stated above, for the given (target) dimension the following applies:\n\n- the number of dimension labels is equal to the number of values computed by the process,\n- the dimension labels are incrementing integers starting from zero,\n- the resolution changes, and\n- the reference system is undefined.","schema":{"subtype":"datacube","type":"object"}},"summary":"Apply a process to all values along a dimension"},{"categories":["cubes"],"description":"Applies a focal process to a data cube.\n\nA focal process is a process that works on a 'neighborhood' of pixels. The neighborhood can extend into multiple dimensions, this extent is specified by the `size` argument. It is not only (part of) the size of the input window, but also the size of the output for a given position of the sliding window. The sliding window moves with multiples of `size`.\n\nAn overlap can be specified so that neighborhoods can have overlapping boundaries. This allows for continuity of the output. The overlap region must be included in the data cube or array returned by `process`, but any changed values will be ignored. The missing overlap at the borders of the original data cube is made available as no-data (`null`) in the sub-data cubes.\n\nThe neighborhood size should be kept small enough, to avoid running beyond computational resources, but a too-small size will result in a larger number of process invocations, which may slow down processing. Window sizes for spatial dimensions typically range from 64 to 512 pixels, while overlaps of 8 to 32 pixels are common.\n\nFor the special case of 2D convolution, it is recommended to use ``apply_kernel()``.","examples":[{"arguments":{"data":{"from_parameter":"data"},"overlap":[{"dimension":"x","unit":"px","value":16},{"dimension":"y","unit":"px","value":16},{"dimension":"t","value":"P3D"}],"process":{"process_graph":{"udf":{"arguments":{"data":{"from_parameter":"data"},"runtime":"Python","udf":"ml.py"},"process_id":"run_udf","result":true}}},"size":[{"dimension":"x","unit":"px","value":128},{"dimension":"y","unit":"px","value":128},{"dimension":"t","value":"P5D"}]}}],"exceptions":{"DataCubePropertiesImmutable":{"message":"The dimension properties (name, type, labels, reference system and resolution) must remain unchanged."},"DimensionNotAvailable":{"message":"A dimension with the specified name does not exist."}},"id":"apply_neighborhood","links":[{"href":"https://openeo.org/documentation/1.0/datacubes.html#apply","rel":"about","title":"Apply explained in the openEO documentation"}],"parameters":[{"description":"A raster data cube.","name":"data","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","type":"object"}},{"description":"Process to be applied on all neighborhoods.","name":"process","schema":{"parameters":[{"description":"The input data, which is a subset of the data cube as specified in `size` and `overlap`. If the given size and overlap result in a one-dimensional data cube it is converted to a labeled array.","name":"data","schema":[{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","title":"Multi-dimensional data","type":"object"},{"subtype":"labeled-array","title":"One-dimensional data","type":"array"}]},{"default":null,"description":"Additional data passed by the user.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"An array or data cube with the newly computed values. The data type and dimensionality must correspond to the input data.\n\n* Data cubes must have the same dimensions and the dimension properties (name, type, labels, reference system and resolution) must remain unchanged. Otherwise, a `DataCubePropertiesImmutable` exception will be thrown.\n* Arrays can be returned with or without labels.","schema":[{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","title":"Multi-dimensional data","type":"object"},{"title":"One-dimensional data","type":"array"}]},"subtype":"process-graph","type":"object"}},{"description":"Neighborhood sizes along each dimension.\n\nThis object maps dimension names to either a physical measure (e.g. 100 m, 10 days) or pixels (e.g. 32 pixels). For dimensions not specified, the default is to provide all values. Be aware that including all values from overly large dimensions may not be processed at once.","name":"size","schema":{"items":{"properties":{"dimension":{"type":"string"},"unit":{"anyOf":[{"title":"Default unit","type":"null"},{"enum":["px","m"],"title":"Specific unit","type":"string"}],"default":null,"description":"The unit the values are given in, either in meters (`m`) or pixels (`px`). If no unit or `null` is given, uses the unit specified for the dimension or otherwise the default unit of the reference system."},"value":{"anyOf":[{"title":"All values","type":"null"},{"description":"See the `unit` parameter for more information.","minimum":0,"type":"number"},{"description":"[ISO 8601 duration](https://en.wikipedia.org/wiki/ISO_8601#Durations), e.g. `P1D` for one day.","pattern":"^(-?)P(?=\\d|T\\d)(?:(\\d+)Y)?(?:(\\d+)M)?(?:(\\d+)([DW]))?(?:T(?:(\\d+)H)?(?:(\\d+)M)?(?:(\\d+(?:\\.\\d+)?)S)?)?$","subtype":"duration","type":"string"}],"default":null}},"required":["dimension","value"],"subtype":"chunk-size","type":"object"},"type":"array"}},{"default":null,"description":"Overlap of neighborhoods along each dimension to avoid border effects. By default no overlap is provided.\n\nFor instance a temporal dimension can add 1 month before and after a neighborhood. In the spatial dimensions, this is often a number of pixels. The overlap specified is added before and after, so an overlap of 8 pixels will add 8 pixels on both sides of the window, so 16 in total.\n\nBe aware that large overlaps increase the need for computational resources and modifying overlapping data in subsequent operations have no effect.","name":"overlap","optional":true,"schema":[{"title":"Without overlap","type":"null"},{"items":{"properties":{"dimension":{"type":"string"},"unit":{"anyOf":[{"title":"Default unit","type":"null"},{"enum":["px","m"],"title":"Specific unit","type":"string"}],"default":null,"description":"The unit the values are given in, either in meters (`m`) or pixels (`px`). If no unit or `null` is given, uses the unit specified for the dimension or otherwise the default unit of the reference system."},"value":{"anyOf":[{"title":"No values","type":"null"},{"description":"See the `unit` parameter for more information.","minimum":0,"type":"number"},{"description":"[ISO 8601 duration](https://en.wikipedia.org/wiki/ISO_8601#Durations), e.g. `P1D` for one day.","pattern":"^(-?)P(?=\\d|T\\d)(?:(\\d+)Y)?(?:(\\d+)M)?(?:(\\d+)([DW]))?(?:T(?:(\\d+)H)?(?:(\\d+)M)?(?:(\\d+(?:\\.\\d+)?)S)?)?$","subtype":"duration","type":"string"}],"default":null}},"required":["dimension","value"],"subtype":"chunk-size","type":"object"},"title":"With overlap","type":"array"}]},{"default":null,"description":"Additional data to be passed to the process.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"A raster data cube with the newly computed values and the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged.","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","type":"object"}},"summary":"Apply a process to pixels in a n-dimensional neighborhood"},{"categories":["cubes"],"description":"Applies a process to segments of the data cube that are defined by the given polygons. For each polygon provided, all pixels for which the point at the pixel center intersects with the polygon (as defined in the Simple Features standard by the OGC) are collected into sub data cubes. If a pixel is part of multiple of the provided polygons (e.g., when the polygons overlap), the `GeometriesOverlap` exception is thrown. Each sub data cube is passed individually to the given process.","exceptions":{"GeometriesOverlap":{"message":"Geometries are not allowed to overlap to avoid that pixel values are processed multiple times."}},"experimental":true,"id":"apply_polygon","links":[{"href":"http://www.opengeospatial.org/standards/sfa","rel":"about","title":"Simple Features standard by the OGC"}],"parameters":[{"description":"A data cube.","name":"data","schema":{"subtype":"raster-cube","type":"object"}},{"description":"A vector data cube containing at least one polygon. The provided vector data can be one of the following:\n\n* A `Polygon` or `MultiPolygon` geometry,\n* a `Feature` with a `Polygon` or `MultiPolygon` geometry, or\n* a `FeatureCollection` containing at least one `Feature` with `Polygon` or `MultiPolygon` geometries.\n* Empty geometries are ignored.","name":"polygons","schema":{"dimensions":[{"geometry_type":["Polygon","MultiPolygon"],"type":"geometry"}],"subtype":"datacube","type":"object"}},{"description":"A process that accepts and returns a single data cube and is applied on each individual sub data cube. The process may consist of multiple sub-processes.","name":"process","schema":{"parameters":[{"description":"A sub data cube of the original data cube. The sub data cubes provided cover the smallest possible grid-aligned extent of the corresponding polygon and all pixels outside of the polygon are replaced with the value given in `mask_value`.","name":"data","schema":{"subtype":"raster-cube","type":"object"}},{"default":null,"description":"Additional data passed by the user.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"The updated sub data cube with the newly computed values and the same dimensions. The dimension properties (name, type, reference system and resolution) must remain unchanged. The labels can change, but the number of labels must remain unchanged.","schema":{"description":"A data cube.","schema":{"subtype":"raster-cube","type":"object"}}},"subtype":"process-graph","type":"object"}},{"default":null,"description":"All pixels for which the point at the pixel center **does not** intersect with the polygon are replaced with the given value, which defaults to `null` (no data).\n\nIt can provide a distinction between no data values within the polygon and masked pixels outside of it.","name":"mask_value","optional":true,"schema":[{"type":"number"},{"type":"boolean"},{"type":"string"},{"type":"null"}]},{"default":null,"description":"Additional data to be passed to the process.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"A data cube with the newly computed values and the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged.","schema":{"subtype":"raster-cube","type":"object"}},"summary":"Apply a process to segments of the data cube"},{"categories":["cubes","reducer"],"description":"Applies a reducer to a data cube dimension by collapsing all the values along the specified dimension into an output value computed by the reducer.\n\nThe dimension is dropped. To avoid this, use ``apply_dimension()`` instead.","exceptions":{"DimensionNotAvailable":{"message":"A dimension with the specified name does not exist."}},"id":"reduce_dimension","links":[{"href":"https://openeo.org/documentation/1.0/datacubes.html#reduce","rel":"about","title":"Reducers explained in the openEO documentation"}],"parameters":[{"description":"A data cube.","name":"data","schema":{"subtype":"datacube","type":"object"}},{"description":"A reducer to apply on the specified dimension. A reducer is a single process such as ``mean()`` or a set of processes, which computes a single value for a list of values, see the category 'reducer' for such processes.","name":"reducer","schema":{"parameters":[{"description":"A labeled array with elements of any type.","name":"data","schema":{"items":{"description":"Any data type."},"subtype":"labeled-array","type":"array"}},{"default":null,"description":"Additional data passed by the user.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"The value to be set in the new data cube.","schema":{"description":"Any data type."}},"subtype":"process-graph","type":"object"}},{"description":"The name of the dimension over which to reduce. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist.","name":"dimension","schema":{"type":"string"}},{"default":null,"description":"Additional data to be passed to the reducer.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"A data cube with the newly computed values. It is missing the given dimension, the number of dimensions decreases by one. The dimension properties (name, type, labels, reference system and resolution) for all other dimensions remain unchanged.","schema":{"subtype":"datacube","type":"object"}},"summary":"Reduce dimensions"},{"categories":["cubes"],"description":"The process merges two 'compatible' data cubes.\n\nThe data cubes have to be compatible, which means that they must share a common subset of equal dimensions. To conveniently get to such a subset of equal dimensions, the process tries to align the horizontal spatial dimensions (axes `x` and `y`) implicitly with ``resample_cube_spatial()`` if required. `cube1` is the target data cube for resampling and the default parameters of ``resample_cube_spatial()`` apply. The equality for geometries follows the definition in the Simple Features standard by the OGC.\n\nAll dimensions share the same properties, such as name, type, reference system, and resolution. Dimensions can have disjoint or overlapping labels. If there is any overlap between the dimension labels, the parameter `overlap_resolver` must be specified to combine the two values for these overlapping labels. A merge operation without overlap should be reversible with (a set of) filter operations for each of the two cubes, if no implicit resampling was applied.\n\nIt is not possible to merge a vector and a raster data cube. Merging vector data cubes with different base geometry types (points, lines/line strings, polygons) is not possible and throws the `IncompatibleGeometryTypes` exception. The base geometry types can be merged with their corresponding multi geometry types.\n\nAfter the merge, the dimensions with a natural/inherent label order (with a reference system this is each spatial and temporal dimensions) still have all dimension labels sorted. For other dimensions without inherent order, including bands, the dimension labels keep the order in which they are present in the original data cubes, and the dimension labels of `cube2` get appended to the dimension labels of `cube1`.\n\n**Examples for merging two data cubes:**\n\n1. Data cubes with the dimensions (`x`, `y`, `t`, `bands`) have the same dimension labels in `x`, `y` and `t`, but the labels for the dimension `bands` are `B1` and `B2` for the base data cube and `B3` and `B4` for the other. An overlap resolver is *not needed*. The merged data cube has the dimensions `x`, `y`, `t`, `bands`, and the dimension `bands` has four dimension labels: `B1`, `B2`, `B3`, `B4`.\n2. Data cubes with the dimensions (`x`, `y`, `t`, `bands`) have the same dimension labels in `x`, `y` and `t`, but the labels for the dimension `bands` are `B1` and `B2` for the base data cube and `B2` and `B3` for the other. An overlap resolver is *required* to resolve overlap in band `B2`. The merged data cube has the dimensions `x`, `y`, `t` and `bands` and the dimension `bands` has three dimension labels: `B1`, `B2`, `B3`.\n3. Data cubes with the dimensions (`x`, `y`, `t`) have the same dimension labels in `x`, `y` and `t`. There are two options:\n   1. Keep the overlapping values separately in the merged data cube: An overlap resolver is *not needed*, but for each data cube you need to add a new dimension using ``add_dimension()``. The new dimensions must be equal, except that the labels for the new dimensions must differ. The merged data cube has the same dimensions and labels as the original data cubes, plus the dimension added with ``add_dimension()``, which has the two dimension labels after the merge.\n   2. Combine the overlapping values into a single value: An overlap resolver is *required* to resolve the overlap for all values. The merged data cube has the same dimensions and labels as the original data cubes, but all values have been processed by the overlap resolver.\n4. A data cube with dimensions (`x`, `y`, `t` / `bands`) or (`x`, `y`, `t`, `bands`) and another data cube with dimensions (`x`, `y`) have the same dimension labels in `x` and `y`. Merging them will join dimensions `x` and `y`, so the lower dimension cube is merged with each time step and band available in the higher dimensional cube. A use case for this is applying a digital elevation model to a spatio-temporal data cube. An overlap resolver is *required* to resolve the overlap for all pixels.","exceptions":{"IncompatibleGeometryTypes":{"message":"The geometry types are not compatible and can't be merged."},"OverlapResolverMissing":{"message":"Overlapping data cubes, but no overlap resolver has been specified."}},"id":"merge_cubes","links":[{"href":"https://en.wikipedia.org/wiki/Reduction_Operator","rel":"about","title":"Background information on reduction operators (binary reducers) by Wikipedia"},{"href":"http://www.opengeospatial.org/standards/sfa","rel":"about","title":"Simple Features standard by the OGC"}],"parameters":[{"description":"The base data cube.","name":"cube1","schema":{"subtype":"datacube","type":"object"}},{"description":"The other data cube to be merged with the base data cube.","name":"cube2","schema":{"subtype":"datacube","type":"object"}},{"default":null,"description":"A reduction operator that resolves the conflict if the data overlaps. The reducer must return a value of the same data type as the input values are. The reduction operator may be a single process such as ``multiply()`` or consist of multiple sub-processes. `null` (the default) can be specified if no overlap resolver is required.","name":"overlap_resolver","optional":true,"schema":{"parameters":[{"description":"The overlapping value from the base data cube `cube1`.","name":"x","schema":{"description":"Any data type."}},{"description":"The overlapping value from the other data cube `cube2`.","name":"y","schema":{"description":"Any data type."}},{"default":null,"description":"Additional data passed by the user.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"The value to be set in the merged data cube.","schema":{"description":"Any data type."}},"subtype":"process-graph","type":"object"}},{"default":null,"description":"Additional data to be passed to the overlap resolver.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"The merged data cube. See the process description for details regarding the dimensions and dimension properties (name, type, labels, reference system and resolution).","schema":{"subtype":"datacube","type":"object"}},"summary":"Merge two data cubes"},{"categories":["cubes","masks"],"description":"Applies a mask to a raster data cube. To apply a polygon as a mask, use ``mask_polygon()``.\n\nA mask is a raster data cube for which corresponding pixels among `data` and `mask` are compared and those pixels in `data` are replaced whose pixels in `mask` are non-zero (for numbers) or `true` (for boolean values). The pixel values are replaced with the value specified for `replacement`, which defaults to `null` (no data).\n\nThe data cubes have to be compatible except that the horizontal spatial dimensions (axes `x` and `y`) will be aligned implicitly by ``resample_cube_spatial()``. `data` is the target data cube for resampling and the default parameters of ``resample_cube_spatial()`` apply. All other dimensions in the mask must also be available in the raster data cube with the same name, type, reference system, resolution and labels. Dimensions can be missing in the mask with the result that the mask is applied to each label of the dimension in `data` that is missing in the data cube of the mask. The process fails if there's an incompatibility found between the raster data cube and the mask.","id":"mask","parameters":[{"description":"A raster data cube.","name":"data","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","type":"object"}},{"description":"A mask as a raster data cube. Every pixel in `data` must have a corresponding element in `mask`.","name":"mask","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","type":"object"}},{"default":null,"description":"The value used to replace masked values with.","name":"replacement","optional":true,"schema":{"type":["number","boolean","string","null"]}}],"returns":{"description":"A masked raster data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged.","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","type":"object"}},"summary":"Apply a raster mask"},{"categories":["cubes","masks"],"description":"Applies a (multi) polygon mask to a raster data cube. To apply a raster mask use ``mask()``.\n\nAll pixels for which the point at the pixel center **does not** intersect with any polygon (as defined in the Simple Features standard by the OGC) are replaced. This behavior can be inverted by setting the parameter `inside` to `true`. The pixel values are replaced with the value specified for `replacement`, which defaults to `null` (no data). No data values in `data` will be left untouched by the masking operation.","id":"mask_polygon","links":[{"href":"http://www.opengeospatial.org/standards/sfa","rel":"about","title":"Simple Features standard by the OGC"}],"parameters":[{"description":"A raster data cube.","name":"data","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","type":"object"}},{"description":"A GeoJSON object or a vector data cube containing at least one polygon. The provided vector data can be one of the following:\n\n* A `Polygon` or `MultiPolygon` geometry,\n* a `Feature` with a `Polygon` or `MultiPolygon` geometry, or\n* a `FeatureCollection` containing at least one `Feature` with `Polygon` or `MultiPolygon` geometries.\n* Empty geometries are ignored.","name":"mask","schema":[{"dimensions":[{"geometry_type":["Polygon","MultiPolygon"],"type":"geometry"}],"subtype":"datacube","title":"Vector Data Cube","type":"object"},{"deprecated":true,"description":"Deprecated in favor of ``load_geojson()``. The GeoJSON type `GeometryCollection` is not supported.","subtype":"geojson","title":"GeoJSON","type":"object"}]},{"default":null,"description":"The value used to replace masked values with.","name":"replacement","optional":true,"schema":[{"type":"number"},{"type":"boolean"},{"type":"string"},{"type":"null"}]},{"default":false,"description":"If set to `true` all pixels for which the point at the pixel center **does** intersect with any polygon are replaced.","name":"inside","optional":true,"schema":{"type":"boolean"}}],"returns":{"description":"A masked raster data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged.","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","type":"object"}},"summary":"Apply a polygon mask"},{"categories":["cubes"],"description":"Adds a new named dimension to the data cube.\n\nAfterwards, the dimension can be referred to with the specified `name`. If a dimension with the specified name exists, the process fails with a `DimensionExists` exception. The dimension label of the dimension is set to the specified `label`.","exceptions":{"DimensionExists":{"message":"A dimension with the specified name already exists."}},"id":"add_dimension","parameters":[{"description":"A data cube to add the dimension to.","name":"data","schema":{"subtype":"datacube","type":"object"}},{"description":"Name for the dimension.","name":"name","schema":{"type":"string"}},{"description":"A dimension label.","name":"label","schema":[{"type":"number"},{"type":"string"}]},{"default":"other","description":"The type of dimension, defaults to `other`.","name":"type","optional":true,"schema":{"enum":["bands","geometry","spatial","temporal","other"],"type":"string"}}],"returns":{"description":"The data cube with a newly added dimension. The new dimension has exactly one dimension label. All other dimensions remain unchanged.","schema":{"subtype":"datacube","type":"object"}},"summary":"Add a new dimension"},{"categories":["cubes"],"description":"Drops a dimension from the data cube.\n\nDropping a dimension only works on dimensions with a single dimension label left, otherwise the process fails with a `DimensionLabelCountMismatch` exception. Dimension values can be reduced to a single value with a filter such as ``filter_bands()`` or the ``reduce_dimension()`` process. If a dimension with the specified name does not exist, the process fails with a `DimensionNotAvailable` exception.","exceptions":{"DimensionLabelCountMismatch":{"message":"The number of dimension labels exceeds one, which requires a reducer."},"DimensionNotAvailable":{"message":"A dimension with the specified name does not exist."}},"id":"drop_dimension","parameters":[{"description":"The data cube to drop a dimension from.","name":"data","schema":{"subtype":"datacube","type":"object"}},{"description":"Name of the dimension to drop.","name":"name","schema":{"type":"string"}}],"returns":{"description":"A data cube without the specified dimension. The number of dimensions decreases by one, but the dimension properties (name, type, labels, reference system and resolution) for all other dimensions remain unchanged.","schema":{"subtype":"datacube","type":"object"}},"summary":"Remove a dimension"},{"categories":["cubes"],"description":"Renames a dimension in the data cube while preserving all other properties.","exceptions":{"DimensionExists":{"message":"A dimension with the specified name already exists."},"DimensionNotAvailable":{"message":"A dimension with the specified name does not exist."}},"id":"rename_dimension","parameters":[{"description":"The data cube.","name":"data","schema":{"subtype":"datacube","type":"object"}},{"description":"The current name of the dimension. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist.","name":"source","schema":{"type":"string"}},{"description":"A new Name for the dimension. Fails with a `DimensionExists` exception if a dimension with the specified name exists.","name":"target","schema":{"type":"string"}}],"returns":{"description":"A data cube with the same dimensions, but the name of one of the dimensions changes. The old name can not be referred to any longer. The dimension properties (name, type, labels, reference system and resolution) remain unchanged.","schema":{"subtype":"datacube","type":"object"}},"summary":"Rename a dimension"},{"categories":["cubes"],"description":"Renames the labels of the specified dimension in the data cube from `source` to `target`.\n\nIf the array for the source labels is empty (the default), the dimension labels are expected to be enumerated with zero-based numbering (0,1,2,3,...) so that the dimension labels directly map to the indices of the array specified for the parameter `target`. Otherwise, the number of the source and target labels must be equal. If none of these requirements is fulfilled, the `LabelMismatch` exception is thrown.\n\nThis process doesn't change the order of the labels and their corresponding data.","examples":[{"arguments":{"data":{"from_parameter":"data"},"dimension":"bands","source":["B1","B2","B3"],"target":["red","green","blue"]},"description":"Renaming the bands from `B1` to `red`, from `B2` to `green` and from `B3` to `blue`.","title":"Rename named labels"}],"exceptions":{"LabelExists":{"message":"A label with the specified name exists."},"LabelMismatch":{"message":"The number of labels in the parameters `source` and `target` don't match."},"LabelNotAvailable":{"message":"A label with the specified name does not exist."},"LabelsNotEnumerated":{"message":"The dimension labels are not enumerated."}},"id":"rename_labels","parameters":[{"description":"The data cube.","name":"data","schema":{"subtype":"datacube","type":"object"}},{"description":"The name of the dimension to rename the labels for.","name":"dimension","schema":{"type":"string"}},{"description":"The new names for the labels.\n\nIf a target dimension label already exists in the data cube, a `LabelExists` exception is thrown.","name":"target","schema":{"items":{"type":["number","string"]},"type":"array"}},{"default":[],"description":"The original names of the labels to be renamed to corresponding array elements in the parameter `target`. It is allowed to only specify a subset of labels to rename, as long as the `target` and `source` parameter have the same length. The order of the labels doesn't need to match the order of the dimension labels in the data cube. By default, the array is empty so that the dimension labels in the data cube are expected to be enumerated.\n\nIf the dimension labels are not enumerated and the given array is empty, the `LabelsNotEnumerated` exception is thrown. If one of the source dimension labels doesn't exist, the `LabelNotAvailable` exception is thrown.","name":"source","optional":true,"schema":{"items":{"type":["number","string"]},"type":"array"}}],"returns":{"description":"The data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged, except that for the given dimension the labels change. The old labels can not be referred to any longer. The number of labels remains the same.","schema":{"subtype":"datacube","type":"object"}},"summary":"Rename dimension labels"},{"categories":["cubes"],"description":"Gives all labels for a dimension in the data cube. The labels have the same order as in the data cube.\n\nIf a dimension with the specified name does not exist, the process fails with a `DimensionNotAvailable` exception.","exceptions":{"DimensionNotAvailable":{"message":"A dimension with the specified name does not exist."}},"id":"dimension_labels","parameters":[{"description":"The data cube.","name":"data","schema":{"subtype":"datacube","type":"object"}},{"description":"The name of the dimension to get the labels for.","name":"dimension","schema":{"type":"string"}}],"returns":{"description":"The labels as an array.","schema":{"items":{"type":["number","string"]},"type":"array"}},"summary":"Get the dimension labels"},{"categories":["cubes","filter"],"description":"Limits the data cube to the specified interval of dates and/or times.\n\nMore precisely, the filter checks whether each of the temporal dimension labels is greater than or equal to the lower boundary (start date/time) and less than the value of the upper boundary (end date/time). This corresponds to a left-closed interval, which contains the lower boundary but not the upper boundary.","exceptions":{"DimensionNotAvailable":{"message":"A dimension with the specified name does not exist."},"TemporalExtentEmpty":{"message":"The temporal extent is empty. The second instant in time must always be greater/later than the first instant in time."}},"id":"filter_temporal","links":[{"href":"https://openeo.org/documentation/1.0/datacubes.html#filter","rel":"about","title":"Filters explained in the openEO documentation"},{"href":"https://www.rfc-editor.org/rfc/rfc3339.html","rel":"about","title":"RFC3339: Details about formatting temporal strings"}],"parameters":[{"description":"A data cube.","name":"data","schema":{"dimensions":[{"type":"temporal"}],"subtype":"datacube","type":"object"}},{"description":"Left-closed temporal interval, i.e. an array with exactly two elements:\n\n1. The first element is the start of the temporal interval. The specified time instant is **included** in the interval.\n2. The second element is the end of the temporal interval. The specified time instant is **excluded** from the interval.\n\nThe second element must always be greater/later than the first element. Otherwise, a `TemporalExtentEmpty` exception is thrown.\n\nAlso supports unbounded intervals by setting one of the boundaries to `null`, but never both.","name":"extent","schema":{"examples":[["2015-01-01T00:00:00Z","2016-01-01T00:00:00Z"],["2015-01-01","2016-01-01"]],"items":{"anyOf":[{"description":"Date and time with a time zone.","format":"date-time","subtype":"date-time","type":"string"},{"description":"Date only, formatted as `YYYY-MM-DD`. The time zone is UTC. Missing time components are all 0.","format":"date","subtype":"date","type":"string"},{"type":"null"}]},"maxItems":2,"minItems":2,"subtype":"temporal-interval","type":"array"}},{"default":null,"description":"The name of the temporal dimension to filter on. If no specific dimension is specified, the filter applies to all temporal dimensions. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist.","name":"dimension","optional":true,"schema":{"type":["string","null"]}}],"returns":{"description":"A data cube restricted to the specified temporal extent. The dimensions and dimension properties (name, type, labels, reference system and resolution) remain unchanged, except that the temporal dimensions (determined by `dimensions` parameter) may have less dimension labels.","schema":{"dimensions":[{"type":"temporal"}],"subtype":"datacube","type":"object"}},"summary":"Temporal filter based on temporal intervals"},{"categories":["cubes","filter"],"description":"Filters the dimension labels in the data cube for the given dimension. Only the dimension labels that match the specified condition are preserved, all other labels with their corresponding data get removed.","examples":[{"arguments":{"condition":{"process_graph":{"eq":{"arguments":{"case_sensitive":false,"x":{"from_parameter":"value"},"y":"Sentinel-2A"},"process_id":"eq","result":true}}},"data":{"from_parameter":"sentinel2_data"},"dimension":"platform"},"description":"Filters the data cube to only contain data from platform Sentinel-2A. This example assumes that the data cube has a dimension `platform` so that computations can distinguish between Sentinel-2A and Sentinel-2B data."}],"exceptions":{"DimensionNotAvailable":{"message":"A dimension with the specified name does not exist."}},"experimental":true,"id":"filter_labels","links":[{"href":"https://openeo.org/documentation/1.0/datacubes.html#filter","rel":"about","title":"Filters explained in the openEO documentation"}],"parameters":[{"description":"A data cube.","name":"data","schema":{"subtype":"datacube","type":"object"}},{"description":"A condition that is evaluated against each dimension label in the specified dimension. A dimension label and the corresponding data is preserved for the given dimension, if the condition returns `true`.","name":"condition","schema":{"parameters":[{"description":"A single dimension label to compare against. The data type of the parameter depends on the dimension labels set for the dimension. Please note that for some dimension types a representation is used, e.g.\n\n* dates and/or times are usually strings compliant to [ISO 8601](https://en.wikipedia.org/wiki/ISO_8601),\n* geometries can be a WKT string or an identifier.","name":"value","schema":[{"type":"number"},{"type":"string"}]},{"default":null,"description":"Additional data passed by the user.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"`true` if the dimension label should be kept in the data cube, otherwise `false`.","schema":{"type":"boolean"}},"subtype":"process-graph","type":"object"}},{"description":"The name of the dimension to filter on. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist.","name":"dimension","schema":{"type":"string"}},{"default":null,"description":"Additional data to be passed to the condition.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"A data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged, except that the given dimension has less (or the same) dimension labels.","schema":{"subtype":"datacube","type":"object"}},"summary":"Filter dimension labels based on a condition"},{"categories":["cubes","filter"],"description":"Limits the data cube to the specified bounding box.\n\n* For raster data cubes, the filter retains a pixel in the data cube if the point at the pixel center intersects with the bounding box (as defined in the Simple Features standard by the OGC). Alternatively, ``filter_spatial()`` can be used to filter by geometry.\n* For vector data cubes, the filter retains the geometry in the data cube if the geometry is fully within the bounding box (as defined in the Simple Features standard by the OGC). All geometries that were empty or not contained fully within the bounding box will be removed from the data cube.\n\nAlternatively, ``filter_vector()`` can be used to filter by geometry.","id":"filter_bbox","links":[{"href":"https://openeo.org/documentation/1.0/datacubes.html#filter","rel":"about","title":"Filters explained in the openEO documentation"},{"href":"https://proj.org/usage/projections.html","rel":"about","title":"PROJ parameters for cartographic projections"},{"href":"http://www.epsg-registry.org","rel":"about","title":"Official EPSG code registry"},{"href":"http://www.epsg.io","rel":"about","title":"Unofficial EPSG code database"},{"href":"http://www.opengeospatial.org/standards/sfa","rel":"about","title":"Simple Features standard by the OGC"}],"parameters":[{"description":"A data cube.","name":"data","schema":[{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","title":"Raster data cube","type":"object"},{"dimensions":[{"type":"geometry"}],"subtype":"datacube","title":"Vector data cube","type":"object"}]},{"description":"A bounding box, which may include a vertical axis (see `base` and `height`).","name":"extent","schema":{"properties":{"base":{"default":null,"description":"Base (optional, lower left corner, coordinate axis 3).","type":["number","null"]},"crs":{"anyOf":[{"examples":[3857],"minimum":1000,"subtype":"epsg-code","title":"EPSG Code","type":"integer"},{"subtype":"wkt2-definition","title":"WKT2","type":"string"}],"default":4326,"description":"Coordinate reference system of the extent, specified as as [EPSG code](http://www.epsg-registry.org/) or [WKT2 CRS string](http://docs.opengeospatial.org/is/18-010r7/18-010r7.html). Defaults to `4326` (EPSG code 4326) unless the client explicitly requests a different coordinate reference system."},"east":{"description":"East (upper right corner, coordinate axis 1).","type":"number"},"height":{"default":null,"description":"Height (optional, upper right corner, coordinate axis 3).","type":["number","null"]},"north":{"description":"North (upper right corner, coordinate axis 2).","type":"number"},"south":{"description":"South (lower left corner, coordinate axis 2).","type":"number"},"west":{"description":"West (lower left corner, coordinate axis 1).","type":"number"}},"required":["west","south","east","north"],"subtype":"bounding-box","type":"object"}}],"returns":{"description":"A data cube restricted to the bounding box. The dimensions and dimension properties (name, type, labels, reference system and resolution) remain unchanged, except that the spatial dimensions have less (or the same) dimension labels.","schema":[{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","title":"Raster data cube","type":"object"},{"dimensions":[{"type":"geometry"}],"subtype":"datacube","title":"Vector data cube","type":"object"}]},"summary":"Spatial filter using a bounding box"},{"categories":["cubes","filter"],"description":"Limits the raster data cube over the spatial dimensions to the specified geometries.\n\n- For **polygons**, the filter retains a pixel in the data cube if the point at the pixel center intersects with at least one of the polygons (as defined in the Simple Features standard by the OGC).\n- For **points**, the process considers the closest pixel center.\n- For **lines** (line strings), the process considers all the pixels whose centers are closest to at least one point on the line.\n\nMore specifically, pixels outside of the bounding box of the given geometry will not be available after filtering. All pixels inside the bounding box that are not retained will be set to `null` (no data).\n\n Alternatively, use ``filter_bbox()`` to filter by bounding box.","id":"filter_spatial","links":[{"href":"https://openeo.org/documentation/1.0/datacubes.html#filter","rel":"about","title":"Filters explained in the openEO documentation"},{"href":"http://www.opengeospatial.org/standards/sfa","rel":"about","title":"Simple Features standard by the OGC"}],"parameters":[{"description":"A raster data cube.","name":"data","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","type":"object"}},{"description":"One or more geometries used for filtering, given as GeoJSON or vector data cube. If multiple geometries are provided, the union of them is used. Empty geometries are ignored.\n\nLimits the data cube to the bounding box of the given geometries. No implicit masking gets applied. To mask the pixels of the data cube use ``mask_polygon()``.","name":"geometries","schema":[{"dimensions":[{"type":"geometry"}],"subtype":"datacube","title":"Vector Data Cube","type":"object"},{"deprecated":true,"description":"Deprecated in favor of ``load_geojson()``. The GeoJSON type `GeometryCollection` is not supported.","subtype":"geojson","title":"GeoJSON","type":"object"}]}],"returns":{"description":"A raster data cube restricted to the specified geometries. The dimensions and dimension properties (name, type, labels, reference system and resolution) remain unchanged, except that the spatial dimensions have less (or the same) dimension labels.","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","type":"object"}},"summary":"Spatial filter raster data cubes using geometries"},{"categories":["cubes","filter"],"description":"Filters the bands in the data cube so that bands that don't match any of the criteria are dropped from the data cube. The data cube is expected to have only one dimension of type `bands`. Fails with a `DimensionMissing` exception if no such dimension exists.\n\nThe following criteria can be used to select bands:\n\n* `bands`: band name or common band name (e.g. `B01`, `B8A`, `red` or `nir`)\n* `wavelengths`: ranges of wavelengths in micrometers (\u03bcm) (e.g. 0.5 - 0.6)\n\nAll these information are exposed in the band metadata of the collection. To keep algorithms interoperable it is recommended to prefer the common band names or the wavelengths over band names that are specific to the collection and/or back-end.\n\nIf multiple criteria are specified, any of them must match and not all of them, i.e. they are combined with an OR-operation. If no criteria are specified, the `BandFilterParameterMissing` exception must be thrown.\n\n**Important:** The order of the specified array defines the order of the bands in the data cube, which can be important for subsequent processes. If multiple bands are matched by a single criterion (e.g. a range of wavelengths), they stay in the original order.","exceptions":{"BandFilterParameterMissing":{"message":"The process `filter_bands` requires any of the parameters `bands`, `common_names` or `wavelengths` to be set."},"DimensionMissing":{"message":"A band dimension is missing."}},"id":"filter_bands","links":[{"href":"https://github.com/radiantearth/stac-spec/tree/master/extensions/eo#common-band-names","rel":"about","title":"List of common band names as specified by the STAC specification"},{"href":"https://openeo.org/documentation/1.0/datacubes.html#filter","rel":"about","title":"Filters explained in the openEO documentation"}],"parameters":[{"description":"A data cube with bands.","name":"data","schema":{"dimensions":[{"type":"bands"}],"subtype":"datacube","type":"object"}},{"default":[],"description":"A list of band names. Either the unique band name (metadata field `name` in bands) or one of the common band names (metadata field `common_name` in bands). If the unique band name and the common name conflict, the unique band name has a higher priority.\n\nThe order of the specified array defines the order of the bands in the data cube. If multiple bands match a common name, all matched bands are included in the original order.","name":"bands","optional":true,"schema":{"items":{"subtype":"band-name","type":"string"},"type":"array"}},{"default":[],"description":"A list of sub-lists with each sub-list consisting of two elements. The first element is the minimum wavelength and the second element is the maximum wavelength. Wavelengths are specified in micrometers (\u03bcm).\n\nThe order of the specified array defines the order of the bands in the data cube. If multiple bands match the wavelengths, all matched bands are included in the original order.","name":"wavelengths","optional":true,"schema":{"items":{"examples":[[[0.45,0.5],[0.6,0.7]]],"items":{"type":"number"},"maxItems":2,"minItems":2,"type":"array"},"type":"array"}}],"returns":{"description":"A data cube limited to a subset of its original bands. The dimensions and dimension properties (name, type, labels, reference system and resolution) remain unchanged, except that the dimension of type `bands` has less (or the same) dimension labels.","schema":{"dimensions":[{"type":"bands"}],"subtype":"datacube","type":"object"}},"summary":"Filter the bands by names"},{"categories":["cubes","reproject"],"description":"Resamples the spatial dimensions (x,y) of the data cube to a specified resolution and/or warps the data cube to the target projection. At least `resolution` or `projection` must be specified.\n\nRelated processes:\n\n* Use ``filter_bbox()`` to set the target spatial extent.\n* To spatially align two data cubes with each other (e.g. for merging), better use the process ``resample_cube_spatial()``.","id":"resample_spatial","links":[{"href":"https://openeo.org/documentation/1.0/datacubes.html#resample","rel":"about","title":"Resampling explained in the openEO documentation"},{"href":"https://proj.org/usage/projections.html","rel":"about","title":"PROJ parameters for cartographic projections"},{"href":"http://www.epsg-registry.org","rel":"about","title":"Official EPSG code registry"},{"href":"http://www.epsg.io","rel":"about","title":"Unofficial EPSG code database"},{"href":"https://gdal.org/programs/gdalwarp.html#cmdoption-gdalwarp-r","rel":"about","title":"gdalwarp resampling methods"}],"parameters":[{"description":"A raster data cube.","name":"data","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","type":"object"}},{"default":0,"description":"Resamples the data cube to the target resolution, which can be specified either as separate values for x and y or as a single value for both axes. Specified in the units of the target projection. Doesn't change the resolution by default (`0`).","name":"resolution","optional":true,"schema":[{"description":"A single number used as the resolution for both x and y.","minimum":0,"type":"number"},{"description":"A two-element array to specify separate resolutions for x (first element) and y (second element).","items":{"minimum":0,"type":"number"},"maxItems":2,"minItems":2,"type":"array"}]},{"default":null,"description":"Warps the data cube to the target projection, specified as as [EPSG code](http://www.epsg-registry.org/) or [WKT2 CRS string](http://docs.opengeospatial.org/is/18-010r7/18-010r7.html). By default (`null`), the projection is not changed.","name":"projection","optional":true,"schema":[{"examples":[3857],"minimum":1000,"subtype":"epsg-code","title":"EPSG Code","type":"integer"},{"subtype":"wkt2-definition","title":"WKT2","type":"string"},{"title":"Don't change projection","type":"null"}]},{"default":"near","description":"Resampling method to use. The following options are available and are meant to align with [`gdalwarp`](https://gdal.org/programs/gdalwarp.html#cmdoption-gdalwarp-r):\n\n* `average`: average (mean) resampling, computes the weighted average of all valid pixels\n* `bilinear`: bilinear resampling\n* `cubic`: cubic resampling\n* `cubicspline`: cubic spline resampling\n* `lanczos`: Lanczos windowed sinc resampling\n* `max`: maximum resampling, selects the maximum value from all valid pixels\n* `med`: median resampling, selects the median value of all valid pixels\n* `min`: minimum resampling, selects the minimum value from all valid pixels\n* `mode`: mode resampling, selects the value which appears most often of all the sampled points\n* `near`: nearest neighbour resampling (default)\n* `q1`: first quartile resampling, selects the first quartile value of all valid pixels\n* `q3`: third quartile resampling, selects the third quartile value of all valid pixels\n* `rms` root mean square (quadratic mean) of all valid pixels\n* `sum`: compute the weighted sum of all valid pixels\n\nValid pixels are determined based on the function ``is_valid()``.","name":"method","optional":true,"schema":{"enum":["average","bilinear","cubic","cubicspline","lanczos","max","med","min","mode","near","q1","q3","rms","sum"],"type":"string"}},{"default":"upper-left","description":"Specifies to which corner of the spatial extent the new resampled data is aligned to.","name":"align","optional":true,"schema":{"enum":["lower-left","upper-left","lower-right","upper-right"],"type":"string"}}],"returns":{"description":"A raster data cube with values warped onto the new projection. It has the same dimensions and the same dimension properties (name, type, labels, reference system and resolution) for all non-spatial or vertical spatial dimensions. For the horizontal spatial dimensions the name and type remain unchanged, but reference system, labels and resolution may change depending on the given parameters.","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","type":"object"}},"summary":"Resample and warp the spatial dimensions"},{"categories":["cubes","reproject"],"description":"Resamples the spatial dimensions (x,y) from a source data cube to align with the corresponding dimensions of the given target data cube. Returns a new data cube with the resampled dimensions.\n\nTo resample a data cube to a specific resolution or projection regardless of an existing target data cube, refer to ``resample_spatial()``.","id":"resample_cube_spatial","links":[{"href":"https://openeo.org/documentation/1.0/datacubes.html#resample","rel":"about","title":"Resampling explained in the openEO documentation"}],"parameters":[{"description":"A raster data cube.","name":"data","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","type":"object"}},{"description":"A raster data cube that describes the spatial target resolution.","name":"target","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","type":"object"}},{"default":"near","description":"Resampling method to use. The following options are available and are meant to align with [`gdalwarp`](https://gdal.org/programs/gdalwarp.html#cmdoption-gdalwarp-r):\n\n* `average`: average (mean) resampling, computes the weighted average of all valid pixels\n* `bilinear`: bilinear resampling\n* `cubic`: cubic resampling\n* `cubicspline`: cubic spline resampling\n* `lanczos`: Lanczos windowed sinc resampling\n* `max`: maximum resampling, selects the maximum value from all valid pixels\n* `med`: median resampling, selects the median value of all valid pixels\n* `min`: minimum resampling, selects the minimum value from all valid pixels\n* `mode`: mode resampling, selects the value which appears most often of all the sampled points\n* `near`: nearest neighbour resampling (default)\n* `q1`: first quartile resampling, selects the first quartile value of all valid pixels\n* `q3`: third quartile resampling, selects the third quartile value of all valid pixels\n* `rms` root mean square (quadratic mean) of all valid pixels\n* `sum`: compute the weighted sum of all valid pixels\n\nValid pixels are determined based on the function ``is_valid()``.","name":"method","optional":true,"schema":{"enum":["average","bilinear","cubic","cubicspline","lanczos","max","med","min","mode","near","q1","q3","rms","sum"],"type":"string"}}],"returns":{"description":"A raster data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged, except for the resolution and dimension labels of the spatial dimensions.","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","type":"object"}},"summary":"Resample the spatial dimensions to match a target data cube"},{"categories":["cubes","math > indices","vegetation indices"],"description":"Computes the Normalized Difference Vegetation Index (NDVI). The NDVI is computed as *`(nir - red) / (nir + red)`*.\n\nThe `data` parameter expects a raster data cube with a dimension of type `bands` or a `DimensionAmbiguous` exception is thrown otherwise. By default, the dimension must have at least two bands with the common names `red` and `nir` assigned. Otherwise, the user has to specify the parameters `nir` and `red`. If neither is the case, either the exception `NirBandAmbiguous` or `RedBandAmbiguous` is thrown. The common names for each band are specified in the collection's band metadata and are *not* equal to the band names.\n\nBy default, the dimension of type `bands` is dropped by this process. To keep the dimension specify a new band name in the parameter `target_band`. This adds a new dimension label with the specified name to the dimension, which can be used to access the computed values. If a band with the specified name exists, a `BandExists` is thrown.\n\nThis process is very similar to the process ``normalized_difference()``, but determines the bands automatically based on the common names (`red`/`nir`) specified in the metadata.","exceptions":{"BandExists":{"message":"A band with the specified target name exists."},"DimensionAmbiguous":{"message":"dimension of type `bands` is not available or is ambiguous.."},"NirBandAmbiguous":{"message":"The NIR band can't be resolved, please specify the specific NIR band name."},"RedBandAmbiguous":{"message":"The red band can't be resolved, please specify the specific red band name."}},"id":"ndvi","links":[{"href":"https://en.wikipedia.org/wiki/Normalized_difference_vegetation_index","rel":"about","title":"NDVI explained by Wikipedia"},{"href":"https://earthobservatory.nasa.gov/features/MeasuringVegetation/measuring_vegetation_2.php","rel":"about","title":"NDVI explained by NASA"},{"href":"https://github.com/radiantearth/stac-spec/tree/master/extensions/eo#common-band-names","rel":"about","title":"List of common band names as specified by the STAC specification"}],"parameters":[{"description":"A raster data cube with two bands that have the common names `red` and `nir` assigned.","name":"data","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"},{"type":"bands"}],"subtype":"datacube","type":"object"}},{"default":"nir","description":"The name of the NIR band. Defaults to the band that has the common name `nir` assigned.\n\nEither the unique band name (metadata field `name` in bands) or one of the common band names (metadata field `common_name` in bands) can be specified. If the unique band name and the common name conflict, the unique band name has a higher priority.","name":"nir","optional":true,"schema":{"subtype":"band-name","type":"string"}},{"default":"red","description":"The name of the red band. Defaults to the band that has the common name `red` assigned.\n\nEither the unique band name (metadata field `name` in bands) or one of the common band names (metadata field `common_name` in bands) can be specified. If the unique band name and the common name conflict, the unique band name has a higher priority.","name":"red","optional":true,"schema":{"subtype":"band-name","type":"string"}},{"default":null,"description":"By default, the dimension of type `bands` is dropped. To keep the dimension specify a new band name in this parameter so that a new dimension label with the specified name will be added for the computed values.","name":"target_band","optional":true,"schema":[{"pattern":"^\\w+$","type":"string"},{"type":"null"}]}],"returns":{"description":"A raster data cube containing the computed NDVI values. The structure of the data cube differs depending on the value passed to `target_band`:\n\n* `target_band` is `null`: The data cube does not contain the dimension of type `bands`, the number of dimensions decreases by one. The dimension properties (name, type, labels, reference system and resolution) for all other dimensions remain unchanged.\n* `target_band` is a string: The data cube keeps the same dimensions. The dimension properties remain unchanged, but the number of dimension labels for the dimension of type `bands` increases by one. The additional label is named as specified in `target_band`.","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","type":"object"}},"summary":"Normalized Difference Vegetation Index"},{"categories":["cubes","math > image filter"],"description":"Applies a 2D convolution (i.e. a focal operation with a weighted kernel) on the horizontal spatial dimensions (axes `x` and `y`) of a raster data cube.\n\nEach value in the kernel is multiplied with the corresponding pixel value and all products are summed up afterwards. The sum is then multiplied with the factor.\n\nThe process can't handle non-numerical or infinite numerical values in the data cube. Boolean values are converted to integers (`false` = 0, `true` = 1), but all other non-numerical or infinite values are replaced with zeroes by default (see parameter `replace_invalid`).\n\nFor cases requiring more generic focal operations or non-numerical values, see ``apply_neighborhood()``.","exceptions":{"KernelDimensionsUneven":{"message":"Each dimension of the kernel must have an uneven number of elements."}},"id":"apply_kernel","links":[{"href":"https://openeo.org/documentation/1.0/datacubes.html#apply","rel":"about","title":"Apply explained in the openEO documentation"},{"href":"http://www.songho.ca/dsp/convolution/convolution.html","rel":"about","title":"Convolutions explained"},{"href":"http://www.songho.ca/dsp/convolution/convolution2d_example.html","rel":"about","title":"Example of 2D Convolution"}],"parameters":[{"description":"A raster data cube.","name":"data","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","type":"object"}},{"description":"Kernel as a two-dimensional array of weights. The inner level of the nested array aligns with the `x` axis and the outer level aligns with the `y` axis. Each level of the kernel must have an uneven number of elements, otherwise the process throws a `KernelDimensionsUneven` exception.","name":"kernel","schema":{"description":"A two-dimensional array of numbers.","items":{"items":{"type":"number"},"type":"array"},"subtype":"kernel","type":"array"}},{"default":1,"description":"A factor that is multiplied to each value after the kernel has been applied.\n\nThis is basically a shortcut for explicitly multiplying each value by a factor afterwards, which is often required for some kernel-based algorithms such as the Gaussian blur.","name":"factor","optional":true,"schema":{"type":"number"}},{"default":0,"description":"Determines how the data is extended when the kernel overlaps with the borders. Defaults to fill the border with zeroes.\n\nThe following options are available:\n\n* *numeric value* - fill with a user-defined constant number `n`: `nnnnnn|abcdefgh|nnnnnn` (default, with `n` = 0)\n* `replicate` - repeat the value from the pixel at the border: `aaaaaa|abcdefgh|hhhhhh`\n* `reflect` - mirror/reflect from the border: `fedcba|abcdefgh|hgfedc`\n* `reflect_pixel` - mirror/reflect from the center of the pixel at the border: `gfedcb|abcdefgh|gfedcb`\n* `wrap` - repeat/wrap the image: `cdefgh|abcdefgh|abcdef`","name":"border","optional":true,"schema":[{"enum":["replicate","reflect","reflect_pixel","wrap"],"type":"string"},{"type":"number"}]},{"default":0,"description":"This parameter specifies the value to replace non-numerical or infinite numerical values with. By default, those values are replaced with zeroes.","name":"replace_invalid","optional":true,"schema":{"type":"number"}}],"returns":{"description":"A data cube with the newly computed values and the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged.","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","type":"object"}},"summary":"Apply a spatial convolution with a kernel"},{"categories":["math"],"description":"Performs a linear transformation between the input and output range.\n\nThe given number in `x` is clipped to the bounds specified in `inputMin` and `inputMax` so that the underlying formula *`((x - inputMin) / (inputMax - inputMin)) * (outputMax - outputMin) + outputMin`* never returns any value lower than `outputMin` or greater than `outputMax`.\n\nPotential use case include\n\n* scaling values to the 8-bit range (0 - 255) often used for numeric representation of values in one of the channels of the [RGB colour model](https://en.wikipedia.org/wiki/RGB_color_model#Numeric_representations) or\n* calculating percentages (0 - 100).\n\nThe no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"inputMax":1,"inputMin":-1,"outputMax":255,"outputMin":0,"x":0.3},"returns":165.75},{"arguments":{"inputMax":255,"inputMin":0,"x":25.5},"returns":0.1},{"arguments":{"inputMax":100,"inputMin":0,"x":null},"returns":null},{"arguments":{"inputMax":1,"inputMin":0,"outputMax":255,"outputMin":0,"x":1.12},"description":"Shows that the input data is clipped.","returns":255}],"id":"linear_scale_range","parameters":[{"description":"A number to transform. The number gets clipped to the bounds specified in `inputMin` and `inputMax`.","name":"x","schema":{"type":["number","null"]}},{"description":"Minimum value the input can obtain.","name":"inputMin","schema":{"type":"number"}},{"description":"Maximum value the input can obtain.","name":"inputMax","schema":{"type":"number"}},{"default":0,"description":"Minimum value of the desired output range.","name":"outputMin","optional":true,"schema":{"type":"number"}},{"default":1,"description":"Maximum value of the desired output range.","name":"outputMax","optional":true,"schema":{"type":"number"}}],"process_graph":{"add":{"arguments":{"x":{"from_node":"multiply"},"y":{"from_parameter":"outputMin"}},"process_id":"add","result":true},"divide":{"arguments":{"x":{"from_node":"subtract1"},"y":{"from_node":"subtract2"}},"process_id":"divide"},"multiply":{"arguments":{"x":{"from_node":"divide"},"y":{"from_node":"subtract3"}},"process_id":"multiply"},"subtract1":{"arguments":{"x":{"from_parameter":"x"},"y":{"from_parameter":"inputMin"}},"process_id":"subtract"},"subtract2":{"arguments":{"x":{"from_parameter":"inputMax"},"y":{"from_parameter":"inputMin"}},"process_id":"subtract"},"subtract3":{"arguments":{"x":{"from_parameter":"outputMax"},"y":{"from_parameter":"outputMin"}},"process_id":"subtract"}},"returns":{"description":"The transformed number.","schema":{"type":["number","null"]}},"summary":"Linear transformation between two ranges"},{"categories":["cubes","aggregate"],"description":"Aggregates statistics for one or more geometries (e.g. zonal statistics for polygons) over the spatial dimensions. The given data cube can have multiple additional dimensions and for all these dimensions results will be computed individually.\n\nAn 'unbounded' aggregation over the full extent of the horizontal spatial dimensions can be computed with the process ``reduce_spatial()``.\n\nThis process passes a list of values to the reducer. The list of values has an undefined order, therefore processes such as ``last()`` and ``first()`` that depend on the order of the values will lead to unpredictable results.","exceptions":{"TargetDimensionExists":{"message":"A dimension with the specified target dimension name already exists."}},"id":"aggregate_spatial","links":[{"href":"https://openeo.org/documentation/1.0/datacubes.html#aggregate","rel":"about","title":"Aggregation explained in the openEO documentation"},{"href":"http://www.opengeospatial.org/standards/sfa","rel":"about","title":"Simple Features standard by the OGC"}],"parameters":[{"description":"A raster data cube with at least two spatial dimensions.\n\nThe data cube implicitly gets restricted to the bounds of the geometries as if ``filter_spatial()`` would have been used with the same values for the corresponding parameters immediately before this process.","name":"data","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","type":"object"}},{"description":"Geometries for which the aggregation will be computed. Feature properties are preserved for vector data cubes and all GeoJSON Features.\n\nOne value will be computed per label in the dimension of type `geometries`, GeoJSON `Feature` or `Geometry`. For a `FeatureCollection` multiple values will be computed, one value per contained `Feature`. No values will be computed for empty geometries. For example, a single value will be computed for a `MultiPolygon`, but two values will be computed for a `FeatureCollection` containing two polygons.\n\n- For **polygons**, the process considers all pixels for which the point at the pixel center intersects with the corresponding polygon (as defined in the Simple Features standard by the OGC).\n- For **points**, the process considers the closest pixel center.\n- For **lines** (line strings), the process considers all the pixels whose centers are closest to at least one point on the line.\n\nThus, pixels may be part of multiple geometries and be part of multiple aggregations. No operation is applied to geometries that are outside of the bounds of the data.","name":"geometries","schema":[{"dimensions":[{"type":"geometry"}],"subtype":"datacube","title":"Vector Data Cube","type":"object"},{"deprecated":true,"description":"Deprecated in favor of ``load_geojson()``. The GeoJSON type `GeometryCollection` is not supported.","subtype":"geojson","title":"GeoJSON","type":"object"}]},{"description":"A reducer to be applied on all values of each geometry. A reducer is a single process such as ``mean()`` or a set of processes, which computes a single value for a list of values, see the category 'reducer' for such processes.","name":"reducer","schema":{"parameters":[{"description":"An array with elements of any type.","name":"data","schema":{"items":{"description":"Any data type."},"type":"array"}},{"default":null,"description":"Additional data passed by the user.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"The value to be set in the vector data cube.","schema":{"description":"Any data type."}},"subtype":"process-graph","type":"object"}},{"default":null,"description":"By default (which is `null`), the process only computes the results and doesn't add a new dimension.\n\nIf this parameter contains a new dimension name, the computation also stores information about the total count of pixels (valid + invalid pixels) and the number of valid pixels (see ``is_valid()``) for each computed value. These values are added as a new dimension. The new dimension of type `other` has the dimension labels `value`, `total_count` and `valid_count`.\n\nFails with a `TargetDimensionExists` exception if a dimension with the specified name exists.","name":"target_dimension","optional":true,"schema":{"type":["string","null"]}},{"default":null,"description":"Additional data to be passed to the reducer.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"A vector data cube with the computed results. Empty geometries still exist but without any aggregated values (i.e. no-data). The spatial dimensions are replaced by a dimension of type 'geometries' and if `target_dimension` is not `null`, a new dimension is added.","schema":{"dimensions":[{"type":"geometry"}],"subtype":"datacube","type":"object"}},"summary":"Zonal statistics for geometries"},{"categories":["cubes","aggregate"],"description":"Aggregates statistics over the horizontal spatial dimensions (axes `x` and `y`) of the data cube.\n\nThe pixel grid for the axes `x` and `y` is divided into non-overlapping windows with the size specified in the parameter `size`. If the number of values for the axes `x` and `y` is not a multiple of the corresponding window size, the behavior specified in the parameters `boundary` and `align` is applied.\nFor each of these windows, the reducer process computes the result.","experimental":true,"id":"aggregate_spatial_window","links":[{"href":"https://openeo.org/documentation/1.0/datacubes.html#aggregate","rel":"about","title":"Aggregation explained in the openEO documentation"}],"parameters":[{"description":"A raster data cube with exactly two horizontal spatial dimensions and an arbitrary number of additional dimensions. The process is applied to all additional dimensions individually.","name":"data","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","type":"object"}},{"description":"A reducer to be applied on the list of values, which contain all pixels covered by the window. A reducer is a single process such as ``mean()`` or a set of processes, which computes a single value for a list of values, see the category 'reducer' for such processes.","name":"reducer","schema":{"parameters":[{"description":"An array with elements of any type.","name":"data","schema":{"items":{"description":"Any data type."},"type":"array"}},{"default":null,"description":"Additional data passed by the user.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"The value to be set in the new data cube.","schema":{"description":"Any data type."}},"subtype":"process-graph","type":"object"}},{"description":"Window size in pixels along the horizontal spatial dimensions.\n\nThe first value corresponds to the `x` axis, the second value corresponds to the `y` axis.","name":"size","schema":{"items":{"minimum":1,"type":"integer"},"maxItems":2,"minItems":2,"type":"array"}},{"default":"pad","description":"Behavior to apply if the number of values for the axes `x` and `y` is not a multiple of the corresponding value in the `size` parameter. Options are:\n\n- `pad` (default): pad the data cube with the no-data value `null` to fit the required window size.\n\n- `trim`: trim the data cube to fit the required window size.\n\nSet the parameter `align` to specifies to which corner the data is aligned to.","name":"boundary","optional":true,"schema":{"enum":["pad","trim"],"type":"string"}},{"default":"upper-left","description":"If the data requires padding or trimming (see parameter `boundary`), specifies to which corner of the spatial extent the data is aligned to. For example, if the data is aligned to the upper left, the process pads/trims at the lower-right.","name":"align","optional":true,"schema":{"enum":["lower-left","upper-left","lower-right","upper-right"],"type":"string"}},{"default":null,"description":"Additional data to be passed to the reducer.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"A raster data cube with the newly computed values and the same dimensions.\n\nThe resolution will change depending on the chosen values for the `size` and `boundary` parameter. It usually decreases for the dimensions which have the corresponding parameter `size` set to values greater than 1.\n\nThe dimension labels will be set to the coordinate at the center of the window. The other dimension properties (name, type and reference system) remain unchanged.","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","type":"object"}},"summary":"Zonal statistics for rectangular windows"},{"categories":["cubes","import","udf"],"description":"Runs a UDF in one of the supported runtime environments.\n\nThe process can either:\n\n1. load and run a UDF stored in a file on the server-side workspace of the authenticated user. The path to the UDF file must be relative to the root directory of the user's workspace.\n2. fetch and run a remotely stored and published UDF by absolute URI.\n3. run the source code specified inline as string.\n\nThe loaded UDF can be executed in several processes such as ``aggregate_spatial()``, ``apply()``, ``apply_dimension()`` and ``reduce_dimension()``. The user must ensure that the data is given in a way that the UDF code can make sense of it.","exceptions":{"InvalidRuntime":{"message":"The specified UDF runtime is not supported."},"InvalidVersion":{"message":"The specified UDF runtime version is not supported."}},"id":"run_udf","parameters":[{"description":"The data to be passed to the UDF.","name":"data","schema":[{"items":{"description":"Any data type."},"minItems":1,"title":"Array","type":"array"},{"description":"A single value of any data type.","title":"Single Value"}]},{"description":"Either source code, an absolute URL or a path to a UDF script.","name":"udf","schema":[{"description":"Absolute URL to a UDF","format":"uri","pattern":"^https?://","subtype":"uri","type":"string"},{"description":"Path to a UDF uploaded to the server.","pattern":"^[^\r\n\\:'\"]+$","subtype":"file-path","type":"string"},{"description":"The multi-line source code of a UDF, must contain a newline/line-break.","pattern":"(\r\n|\r|\n)","subtype":"udf-code","type":"string"}]},{"description":"A UDF runtime identifier available at the back-end.","name":"runtime","schema":{"subtype":"udf-runtime","type":"string"}},{"default":null,"description":"An UDF runtime version. If set to `null`, the default runtime version specified for each runtime is used.","name":"version","optional":true,"schema":[{"subtype":"udf-runtime-version","type":"string"},{"title":"Default runtime version","type":"null"}]},{"default":{},"description":"Additional data such as configuration options to be passed to the UDF.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"The data processed by the UDF. The returned value can be of any data type and is exactly what the UDF code returns.","schema":{"description":"Any data type.","title":"Any"}},"summary":"Run a UDF"},{"categories":["cubes","aggregate"],"description":"Computes a temporal aggregation based on an array of temporal intervals.\n\nFor common regular calendar hierarchies such as year, month, week or seasons ``aggregate_temporal_period()`` can be used. Other calendar hierarchies must be transformed into specific intervals by the clients.\n\nFor each interval, all data along the dimension will be passed through the reducer.\n\nThe computed values will be projected to the labels. If no labels are specified, the start of the temporal interval will be used as label for the corresponding values. In case of a conflict (i.e. the user-specified values for the start times of the temporal intervals are not distinct), the user-defined labels must be specified in the parameter `labels` as otherwise a `DistinctDimensionLabelsRequired` exception would be thrown. The number of user-defined labels and the number of intervals need to be equal.\n\nIf the dimension is not set or is set to `null`, the data cube is expected to only have one temporal dimension.","examples":[{"arguments":{"data":{"from_parameter":"data"},"intervals":[["2015-01-01","2016-01-01"],["2016-01-01","2017-01-01"],["2017-01-01","2018-01-01"],["2018-01-01","2019-01-01"],["2019-01-01","2020-01-01"]],"labels":["2015","2016","2017","2018","2019"],"reducer":{"process_graph":{"mean1":{"arguments":{"data":{"from_parameter":"data"}},"process_id":"mean","result":true}}}}}],"exceptions":{"DimensionNotAvailable":{"message":"A dimension with the specified name does not exist."},"DistinctDimensionLabelsRequired":{"message":"The dimension labels have duplicate values. Distinct labels must be specified."},"TemporalExtentEmpty":{"message":"At least one of the intervals is empty. The second instant in time must always be greater/later than the first instant."},"TooManyDimensions":{"message":"The data cube contains multiple temporal dimensions. The parameter `dimension` must be specified."}},"id":"aggregate_temporal","links":[{"href":"https://openeo.org/documentation/1.0/datacubes.html#aggregate","rel":"about","title":"Aggregation explained in the openEO documentation"},{"href":"https://www.rfc-editor.org/rfc/rfc3339.html","rel":"about","title":"RFC3339: Details about formatting temporal strings"}],"parameters":[{"description":"A data cube.","name":"data","schema":{"dimensions":[{"type":"temporal"}],"subtype":"datacube","type":"object"}},{"description":"Left-closed temporal intervals, which are allowed to overlap. Each temporal interval in the array has exactly two elements:\n\n1. The first element is the start of the temporal interval. The specified time instant is **included** in the interval.\n2. The second element is the end of the temporal interval. The specified time instant is **excluded** from the interval.\n\nThe second element must always be greater/later than the first element, except when using time without date. Otherwise, a `TemporalExtentEmpty` exception is thrown.","name":"intervals","schema":{"examples":[[["2015-01-01","2016-01-01"],["2016-01-01","2017-01-01"],["2017-01-01","2018-01-01"]],[["06:00:00","18:00:00"],["18:00:00","06:00:00"]]],"items":{"items":{"anyOf":[{"description":"Date and time with a time zone.","format":"date-time","subtype":"date-time","type":"string"},{"description":"Date only, formatted as `YYYY-MM-DD`. The time zone is UTC. Missing time components are all 0.","format":"date","subtype":"date","type":"string"},{"description":"Time only, formatted as `HH:MM:SS`. The time zone is UTC.","pattern":"^\\d{2}:\\d{2}:\\d{2}$","subtype":"time","type":"string"},{"type":"null"}]},"maxItems":2,"minItems":2,"subtype":"temporal-interval","type":"array","uniqueItems":true},"minItems":1,"subtype":"temporal-intervals","type":"array"}},{"description":"A reducer to be applied for the values contained in each interval. A reducer is a single process such as ``mean()`` or a set of processes, which computes a single value for a list of values, see the category 'reducer' for such processes. Intervals may not contain any values, which for most reducers leads to no-data (`null`) values by default.","name":"reducer","schema":{"parameters":[{"description":"A labeled array with elements of any type. If there's no data for the interval, the array is empty.","name":"data","schema":{"items":{"description":"Any data type."},"subtype":"labeled-array","type":"array"}},{"default":null,"description":"Additional data passed by the user.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"The value to be set in the new data cube.","schema":{"description":"Any data type."}},"subtype":"process-graph","type":"object"}},{"default":[],"description":"Distinct labels for the intervals, which can contain dates and/or times. Is only required to be specified if the values for the start of the temporal intervals are not distinct and thus the default labels would not be unique. The number of labels and the number of groups need to be equal.","name":"labels","optional":true,"schema":{"items":{"type":["number","string"]},"type":"array"}},{"default":null,"description":"The name of the temporal dimension for aggregation. All data along the dimension is passed through the specified reducer. If the dimension is not set or set to `null`, the data cube is expected to only have one temporal dimension. Fails with a `TooManyDimensions` exception if it has more dimensions. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist.","name":"dimension","optional":true,"schema":{"type":["string","null"]}},{"default":null,"description":"Additional data to be passed to the reducer.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"A new data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged, except for the resolution and dimension labels of the given temporal dimension.","schema":{"dimensions":[{"type":"temporal"}],"subtype":"datacube","type":"object"}},"summary":"Temporal aggregations"},{"categories":["aggregate","climatology","cubes"],"description":"Computes a temporal aggregation based on calendar hierarchies such as years, months or seasons. For other calendar hierarchies ``aggregate_temporal()`` can be used.\n\nFor each interval, all data along the dimension will be passed through the reducer.\n\nIf the dimension is not set or is set to `null`, the data cube is expected to only have one temporal dimension.","exceptions":{"DimensionNotAvailable":{"message":"A dimension with the specified name does not exist."},"DistinctDimensionLabelsRequired":{"message":"The dimension labels have duplicate values. Distinct labels must be specified."},"TooManyDimensions":{"message":"The data cube contains multiple temporal dimensions. The parameter `dimension` must be specified."}},"id":"aggregate_temporal_period","links":[{"href":"https://openeo.org/documentation/1.0/datacubes.html#aggregate","rel":"about","title":"Aggregation explained in the openEO documentation"}],"parameters":[{"description":"The source data cube.","name":"data","schema":{"dimensions":[{"type":"temporal"}],"subtype":"datacube","type":"object"}},{"description":"The time intervals to aggregate. The following pre-defined values are available:\n\n* `hour`: Hour of the day\n* `day`: Day of the year\n* `week`: Week of the year\n* `dekad`: Ten day periods, counted per year with three periods per month (day 1 - 10, 11 - 20 and 21 - end of month). The third dekad of the month can range from 8 to 11 days. For example, the third dekad of a year spans from January 21 till January 31 (11 days), the fourth dekad spans from February 1 till February 10 (10 days) and the sixth dekad spans from February 21 till February 28 or February 29 in a leap year (8 or 9 days respectively).\n* `month`: Month of the year\n* `season`: Three month periods of the calendar seasons (December - February, March - May, June - August, September - November).\n* `tropical-season`: Six month periods of the tropical seasons (November - April, May - October).\n* `year`: Proleptic years\n* `decade`: Ten year periods ([0-to-9 decade](https://en.wikipedia.org/wiki/Decade#0-to-9_decade)), from a year ending in a 0 to the next year ending in a 9.\n* `decade-ad`: Ten year periods ([1-to-0 decade](https://en.wikipedia.org/wiki/Decade#1-to-0_decade)) better aligned with the anno Domini (AD) calendar era, from a year ending in a 1 to the next year ending in a 0.","name":"period","schema":{"enum":["hour","day","week","dekad","month","season","tropical-season","year","decade","decade-ad"],"type":"string"}},{"description":"A reducer to be applied for the values contained in each period. A reducer is a single process such as ``mean()`` or a set of processes, which computes a single value for a list of values, see the category 'reducer' for such processes. Periods may not contain any values, which for most reducers leads to no-data (`null`) values by default.","name":"reducer","schema":{"parameters":[{"description":"A labeled array with elements of any type. If there's no data for the period, the array is empty.","name":"data","schema":{"items":{"description":"Any data type."},"subtype":"labeled-array","type":"array"}},{"default":null,"description":"Additional data passed by the user.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"The value to be set in the new data cube.","schema":{"description":"Any data type."}},"subtype":"process-graph","type":"object"}},{"default":null,"description":"The name of the temporal dimension for aggregation. All data along the dimension is passed through the specified reducer. If the dimension is not set or set to `null`, the source data cube is expected to only have one temporal dimension. Fails with a `TooManyDimensions` exception if it has more dimensions. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist.","name":"dimension","optional":true,"schema":{"type":["string","null"]}},{"default":null,"description":"Additional data to be passed to the reducer.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"A new data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged, except for the resolution and dimension labels of the given temporal dimension. The specified temporal dimension has the following dimension labels (`YYYY` = four-digit year, `MM` = two-digit month, `DD` two-digit day of month):\n\n* `hour`: `YYYY-MM-DD-00` - `YYYY-MM-DD-23`\n* `day`: `YYYY-001` - `YYYY-365`\n* `week`: `YYYY-01` - `YYYY-52`\n* `dekad`: `YYYY-00` - `YYYY-36`\n* `month`: `YYYY-01` - `YYYY-12`\n* `season`: `YYYY-djf` (December - February), `YYYY-mam` (March - May), `YYYY-jja` (June - August), `YYYY-son` (September - November).\n* `tropical-season`: `YYYY-ndjfma` (November - April), `YYYY-mjjaso` (May - October).\n* `year`: `YYYY`\n* `decade`: `YYY0`\n* `decade-ad`: `YYY1`\n\nThe dimension labels in the new data cube are complete for the whole extent of the source data cube. For example, if `period` is set to `day` and the source data cube has two dimension labels at the beginning of the year (`2020-01-01`) and the end of a year (`2020-12-31`), the process returns a data cube with 365 dimension labels (`2020-001`, `2020-002`, ..., `2020-365`). In contrast, if `period` is set to `day` and the source data cube has just one dimension label `2020-01-05`, the process returns a data cube with just a single dimension label (`2020-005`).","schema":{"dimensions":[{"type":"temporal"}],"subtype":"datacube","type":"object"}},"summary":"Temporal aggregations based on calendar hierarchies"},{"categories":["machine learning"],"description":"Executes the fit of a random forest classification based on training data. The process does not include a separate split of the data in test, validation and training data. The Random Forest classification model is based on the approach by Breiman (2001).","experimental":true,"id":"fit_class_random_forest","links":[{"href":"https://doi.org/10.1023/A:1010933404324","rel":"about","title":"Breiman (2001): Random Forests","type":"text/html"}],"parameters":[{"description":"The predictors for the classification model as a vector data cube. Aggregated to the features (vectors) of the target input variable.","name":"predictors","schema":{"subtype":"vector-cube","type":"object"}},{"description":"The training sites for the classification model as a vector data cube. This is associated with the target variable for the Random Forest model. The geometry has to be associated with a value to predict (e.g. fractional forest canopy cover).","name":"target","schema":{"subtype":"vector-cube","type":"object"}},{"description":"Specifies how many split variables will be used at a node.\n\nThe following options are available:\n\n- *integer*: The given number of variables are considered for each split.\n- `all`: All variables are considered for each split.\n- `log2`: The logarithm with base 2 of the number of variables are considered for each split.\n- `onethird`: A third of the number of variables are considered for each split.\n- `sqrt`: The square root of the number of variables are considered for each split. This is often the default for classification.","name":"max_variables","schema":[{"minimum":1,"type":"integer"},{"enum":["all","log2","onethird","sqrt"],"type":"string"}]},{"default":100,"description":"The number of trees build within the Random Forest classification.","name":"num_trees","optional":true,"schema":{"minimum":1,"type":"integer"}},{"default":null,"description":"A randomization seed to use for the random sampling in training. If not given or `null`, no seed is used and results may differ on subsequent use.","name":"seed","optional":true,"schema":{"type":["integer","null"]}}],"returns":{"description":"A model object that can be saved with ``save_ml_model()`` and restored with ``load_ml_model()``.","schema":{"subtype":"ml-model","type":"object"}},"summary":"Train a random forest classification model"},{"categories":["machine learning"],"description":"Executes the fit of a catboost classification based on training data. The process does not include a separate split of the data in test, validation and training data.","experimental":true,"id":"fit_class_catboost","links":[],"parameters":[{"description":"The predictors for the classification model as a vector data cube. Aggregated to the features (vectors) of the target input variable.","name":"predictors","schema":{"subtype":"vector-cube","type":"object"}},{"description":"The training sites for the classification model as a vector data cube. This is associated with the target variable for the Catboost model. The geometry has to be associated with a value to predict (e.g. fractional forest canopy cover).","name":"target","schema":{"subtype":"vector-cube","type":"object"}},{"default":5,"description":"The maximum number of trees that can be built during the training process.","name":"iterations","optional":true,"schema":{"maximum":500,"minimum":1,"type":"integer"}},{"default":5,"description":"Depth of the trees.","name":"depth","optional":true,"schema":{"maximum":16,"minimum":1,"type":"integer"}},{"default":0,"description":"The random seed used for training, for reproducibility.","name":"seed","optional":true,"schema":{"maximum":2147483647,"minimum":0,"type":"integer"}}],"returns":{"description":"A model object that can be saved with ``save_ml_model()`` and restored with ``load_ml_model()``.","schema":{"subtype":"ml-model","type":"object"}},"summary":"Train a catboost classification model"},{"categories":["machine learning"],"description":"Applies an onnx machine learning model to an datacube.","experimental":true,"id":"predict_onnx","parameters":[{"description":"A raster data cube.","name":"data","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","type":"object"}},{"description":"A url to an onnx model.","name":"model","schema":{"type":"string"}}],"returns":{"description":"A raster data cube with the newly computed values","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"}],"subtype":"datacube","type":"object"}},"summary":"Predict class probabilities from an onnx machine learning model"},{"categories":["machine learning","reducer"],"description":"Applies a Random Forest machine learning model to an array and predicts a value for it.","experimental":true,"id":"predict_random_forest","parameters":[{"description":"An array of numbers.","name":"data","schema":{"items":{"type":["number","null"]},"type":"array"}},{"description":"A model object that can be trained with the processes ``fit_regr_random_forest()`` (regression) and ``fit_class_random_forest()`` (classification).","name":"model","schema":{"subtype":"ml-model","type":"object"}}],"returns":{"description":"The predicted value. Returns `null` if any of the given values in the array is a no-data value.","schema":{"type":["number","null"]}},"summary":"Predict values from a Random Forest model"},{"categories":["machine learning","reducer"],"description":"Applies a Catboost machine learning model to an array and predicts a value for it.","experimental":true,"id":"predict_catboost","parameters":[{"description":"An array of numbers.","name":"data","schema":{"items":{"type":["number","null"]},"type":"array"}},{"description":"A model object that can be trained with the processes ``fit_regr_catboost()`` (regression) and ``fit_class_catboost()`` (classification).","name":"model","schema":{"subtype":"ml-model","type":"object"}}],"returns":{"description":"The predicted value.","schema":{"type":["number","null"]}},"summary":"Predict values from a Catboost model"},{"categories":["machine learning","reducer"],"description":"Applies a machine learning model to an array and predicts a probability for each class.","experimental":true,"id":"predict_probabilities","parameters":[{"description":"An array of numbers.","name":"data","schema":{"items":{"type":["number","null"]},"type":"array"}},{"description":"A model object that can be trained with the processes ``fit_regr_<model_name>()`` (regression) and ``fit_class_<model_name>()`` (classification).","name":"model","schema":{"subtype":"ml-model","type":"object"}}],"returns":{"description":"A probability for each class","schema":{"items":{"type":["number","null"]},"type":"array"}},"summary":"Predict class probabilities from a machine learning model"},{"description":"Add a buffer around a geometry.","id":"vector_buffer","parameters":[{"description":"Input geometry to add buffer to, vector-cube or GeoJSON(deprecated).","name":"geometries","optional":false,"schema":[{"dimensions":[{"type":"geometry"}],"subtype":"datacube","type":"object"},{"subtype":"geojson","type":"object"}]},{"description":"The distance of the buffer in meters.","name":"distance","optional":false,"schema":{"type":"number"}}],"returns":{"description":"Output geometry (GeoJSON object) with the added or subtracted buffer","schema":{"subtype":"geojson","type":"object"}}},{"description":"Reads vector data from a file or a URL or get geometries from a FeatureCollection","id":"get_geometries","parameters":[{"description":"filename or http url of a vector file","name":"filename","optional":true,"schema":{"type":"string"}},{"description":"feature collection","name":"feature_collection","optional":true,"schema":{"type":"object"}}],"returns":{"description":"TODO","schema":{"subtype":"vector-cube","type":"object"}}},{"description":"Reads vector data from a file or a URL.","id":"read_vector","parameters":[{"description":"Vector file reference: a HTTP(S) URL or a file path.","name":"filename","optional":false,"schema":[{"description":"Public URL to a vector file.","pattern":"^https?://","subtype":"uri","type":"string"},{"description":"File path (resolvable back-end-side) to a vector file.","pattern":"^[^\r\n\\:'\"]+$","subtype":"file-path","type":"string"}]}],"returns":{"description":"GeoJSON-style feature collection","schema":{"subtype":"geojson","type":"object"}}},{"description":"[EXPERIMENTAL:] Converts given data (e.g. GeoJson object) to a vector cube.","id":"to_vector_cube","parameters":[{"description":"GeoJson object.","name":"data","optional":false,"schema":{"subtype":"geojson","type":"object"}}],"returns":{"description":"vector-cube","schema":{"subtype":"vector-cube","type":"object"}}},{"description":"Converts this raster data cube into a vector data cube.","experimental":true,"id":"raster_to_vector","parameters":[{"description":"A raster data cube.","name":"data","optional":false,"schema":{"subtype":"raster-cube","type":"object"}}],"returns":{"description":"vector-cube","schema":{"subtype":"vector-cube","type":"object"}}},{"description":"Creates a raster cube as output based on a vector cube.","experimental":true,"id":"vector_to_raster","parameters":[{"description":"A vector data cube.","name":"data","optional":false,"schema":{"subtype":"vector-cube","type":"object"}},{"description":"A raster data cube used as reference.","name":"target","optional":false,"schema":{"subtype":"raster-cube","type":"object"}}],"returns":{"description":"raster-cube","schema":{"subtype":"raster-cube","type":"object"}}},{"categories":["cubes","optical"],"description":"Applies an atmospheric correction that converts top of atmosphere reflectance values into bottom of atmosphere/top of canopy reflectance values.","exceptions":{"DigitalElevationModelInvalid":{"message":"The digital elevation model specified is either not a DEM or can't be used with the data cube given."}},"experimental":true,"id":"atmospheric_correction","links":[{"href":"https://bok.eo4geo.eu/IP1-7-1","rel":"about","title":"Atmospheric correction explained by EO4GEO body of knowledge."}],"parameters":[{"description":"Data cube containing multi-spectral optical top of atmosphere reflectances to be corrected.","name":"data","optional":false,"schema":{"subtype":"raster-cube","type":"object"}},{"description":"The atmospheric correction method to use.","name":"method","optional":true,"schema":{"type":"string"}},{"description":"The digital elevation model to use.","name":"elevation_model","optional":true,"schema":{"type":"string"}},{"description":"non-standard mission Id, currently defaults to sentinel2","name":"missionId","optional":true,"schema":{"type":"string"}},{"description":"non-standard if set, overrides sun zenith angle values [deg]","name":"sza","optional":true,"schema":{"type":"number"}},{"description":"non-standard if set, overrides sensor zenith angle values [deg]","name":"vza","optional":true,"schema":{"type":"number"}},{"description":"non-standard if set, overrides rel. azimuth angle values [deg]","name":"raa","optional":true,"schema":{"type":"number"}},{"description":"non-standard if set, overrides ground elevation [km]","name":"gnd","optional":true,"schema":{"type":"number"}},{"description":"non-standard if set, overrides aerosol optical thickness [], usually 0.1..0.2","name":"aot","optional":true,"schema":{"type":"number"}},{"description":"non-standard if set, overrides water vapor [], usually 0..7","name":"cwv","optional":true,"schema":{"type":"number"}},{"description":"non-standard if set to 1, saves debug bands","name":"appendDebugBands","optional":true,"schema":{"type":"number"}}],"returns":{"description":"the corrected data as a data cube","schema":{"subtype":"raster-cube","type":"object"}},"summary":"Apply atmospheric correction"},{"categories":["cubes","sar"],"description":"Computes backscatter from SAR input.\n\nNote that backscatter computation may require instrument specific metadata that is tightly coupled to the original SAR products. As a result, this process may only work in combination with loading data from specific collections, not with general data cubes.\n\nThis process uses bilinear interpolation, both for resampling the DEM and the backscatter.","exceptions":{"DigitalElevationModelInvalid":{"message":"The digital elevation model specified is either not a DEM or can't be used with the data cube given."}},"experimental":true,"id":"sar_backscatter","links":[{"href":"https://bok.eo4geo.eu/PP2-2-4-3","rel":"about","title":"Gamma nought (0) explained by EO4GEO body of knowledge."},{"href":"https://bok.eo4geo.eu/PP2-2-4-2","rel":"about","title":"Sigma nought (0) explained by EO4GEO body of knowledge."},{"href":"https://www.geo.uzh.ch/microsite/rsl-documents/research/publications/peer-reviewed-articles/201108-TGRS-Small-tcGamma-3809999360/201108-TGRS-Small-tcGamma.pdf","rel":"about","title":"Flattening Gamma: Radiometric Terrain Correction for SAR Imagery"},{"href":"https://doi.org/10.3390/data4030093","rel":"about","title":"Reasoning behind the choice of bilinear resampling"}],"parameters":[{"description":"The source data cube containing SAR input.","name":"data","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"},{"type":"bands"}],"subtype":"datacube","type":"object"}},{"default":"gamma0-terrain","description":"Select the radiometric correction coefficient. The following options are available:\n\n* `beta0`: radar brightness\n* `sigma0-ellipsoid`: ground area computed with ellipsoid earth model\n* `sigma0-terrain`: ground area computed with terrain earth model\n* `gamma0-ellipsoid`: ground area computed with ellipsoid earth model in sensor line of sight\n* `gamma0-terrain`: ground area computed with terrain earth model in sensor line of sight (default)\n* `null`: non-normalized backscatter","name":"coefficient","optional":true,"schema":[{"enum":["beta0","sigma0-ellipsoid","sigma0-terrain","gamma0-ellipsoid","gamma0-terrain"],"type":"string"},{"title":"Non-normalized backscatter","type":"null"}]},{"default":null,"description":"The digital elevation model to use. Set to `null` (the default) to allow the back-end to choose, which will improve portability, but reduce reproducibility.","name":"elevation_model","optional":true,"schema":[{"subtype":"collection-id","type":"string"},{"type":"null"}]},{"default":false,"description":"If set to `true`, a data mask is added to the bands with the name `mask`. It indicates which values are valid (1), invalid (0) or contain no-data (null).","name":"mask","optional":true,"schema":{"type":"boolean"}},{"default":false,"description":"If set to `true`, a DEM-based local contributing area band named `contributing_area` is added. The values are given in square meters.","name":"contributing_area","optional":true,"schema":{"type":"boolean"}},{"default":false,"description":"If set to `true`, a DEM-based local incidence angle band named `local_incidence_angle` is added. The values are given in degrees.","name":"local_incidence_angle","optional":true,"schema":{"type":"boolean"}},{"default":false,"description":"If set to `true`, an ellipsoidal incidence angle band named `ellipsoid_incidence_angle` is added. The values are given in degrees.","name":"ellipsoid_incidence_angle","optional":true,"schema":{"type":"boolean"}},{"default":true,"description":"If set to `false`, no noise removal is applied. Defaults to `true`, which removes noise.","name":"noise_removal","optional":true,"schema":{"type":"boolean"}},{"default":{},"description":"Proprietary options for the backscatter computations. Specifying proprietary options will reduce portability.","name":"options","optional":true,"schema":{"additionalProperties":false,"type":"object"}}],"returns":{"description":"Backscatter values corresponding to the chosen parametrization. The values are given in linear scale.","schema":{"dimensions":[{"axis":["x","y"],"type":"spatial"},{"type":"bands"}],"subtype":"datacube","type":"object"}},"summary":"Computes backscatter from SAR input"},{"categories":["cubes","optical"],"description":"Resolution merging algorithms try to improve the spatial resolution of lower resolution bands (e.g. Sentinel-2 20M) based on higher resolution bands. (e.g. Sentinel-2 10M).\n ","experimental":true,"id":"resolution_merge","links":[{"href":"https://bok.eo4geo.eu/IP2-1-3","rel":"about","title":"Pansharpening explained by EO4GEO body of knowledge."},{"href":"https://doi.org/10.1109/TGRS.2016.2537929","rel":"about","title":"Scientific publication: Improving the Spatial Resolution of Land Surface Phenology by Fusing Medium- and Coarse-Resolution Inputs"}],"parameters":[{"description":"Data cube containing multiple spectral bands, with different source resolutions.","name":"data","schema":{"subtype":"raster-cube","type":"object"}},{"default":null,"description":"The method to use.\\n\\nThe supported algorithms can vary between back-ends. Set to `null` (the default) to allow the back-end to choose, which will improve portability, but reduce reproducibility..","name":"method","optional":true,"schema":{"type":["string","null"]}},{"default":[],"description":"A list of band names to use as 'high-resolution' band. 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If multiple bands match a common name, all matched bands are included in the original order.\n These bands will be modified by the process.","name":"low_resolution_bands","optional":false,"schema":{"items":{"subtype":"band-name","type":"string"},"type":"array"}}],"returns":{"description":"A datacube with the same bands and metadata as the input, but algorithmically increased spatial resolution for the selected bands.","schema":{"subtype":"raster-cube","type":"object"}},"summary":"Resolution merging or pansharpening: increase the spatial resolution of low-resolution bands, based on higher resolution bands."},{"categories":["cubes","ard"],"deprecated":true,"description":"[Deprecated: consider using to_scl_dilation_mask] Mask clouds by dilating Sen2Cor sceneclassification. This dilation algorithm removes pixels in the neighbourhood of clouds in a fairly aggressive manner, to avoid any type of contamination. 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As a result, this process may only work in combination with loading data from specific collections, not with general data cubes.\n\nThis process uses bilinear interpolation, both for resampling the DEM and the backscatter.","exceptions":{"DigitalElevationModelInvalid":{"message":"The digital elevation model specified is either not a DEM or can't be used with the data cube given."}},"experimental":true,"id":"ard_normalized_radar_backscatter","links":[{"href":"http://ceos.org/ard/files/PFS/NRB/v5.0/CARD4L-PFS_Normalised_Radar_Backscatter-v5.0.pdf","rel":"about","title":"CEOS CARD4L specification"},{"href":"https://bok.eo4geo.eu/PP2-2-4-3","rel":"about","title":"Gamma nought (0) explained by EO4GEO body of knowledge."},{"href":"https://doi.org/10.3390/data4030093","rel":"about","title":"Reasoning behind the choice of bilinear resampling"}],"parameters":[{"description":"The source data cube containing SAR input.","name":"data","schema":{"subtype":"raster-cube","type":"object"}},{"default":null,"description":"The digital elevation model to use. Set to `null` (the default) to allow the back-end to choose, which will improve portability, but reduce reproducibility.","name":"elevation_model","optional":true,"schema":[{"subtype":"collection-id","type":"string"},{"type":"null"}]},{"default":false,"description":"If set to `true`, a DEM-based local contributing area band named `contributing_area` is added. The values are given in square meters.","name":"contributing_area","optional":true,"schema":{"type":"boolean"}},{"default":false,"description":"If set to `true`, an ellipsoidal incidence angle band named `ellipsoid_incidence_angle` is added. The values are given in degrees.","name":"ellipsoid_incidence_angle","optional":true,"schema":{"type":"boolean"}},{"default":true,"description":"If set to `false`, no noise removal is applied. Defaults to `true`, which removes noise.","name":"noise_removal","optional":true,"schema":{"type":"boolean"}},{"default":{},"description":"Proprietary options for the backscatter computations. Specifying proprietary options will reduce portability.","name":"options","optional":true,"schema":{"additionalProperties":false,"type":"object"}}],"process_graph":{"nrb":{"arguments":{"coefficient":"gamma0-terrain","contributing_area":{"from_parameter":"contributing_area"},"data":{"from_parameter":"data"},"elevation_model":{"from_parameter":"elevation_model"},"ellipsoid_incidence_angle":{"from_parameter":"ellipsoid_incidence_angle"},"local_incidence_angle":true,"mask":true,"noise_removal":{"from_parameter":"noise_removal"},"options":{"from_parameter":"options"}},"process_id":"sar_backscatter","result":true}},"returns":{"description":"Backscatter values expressed as gamma0 in linear scale.\n\nIn addition to the bands `contributing_area` and `ellipsoid_incidence_angle` that can optionally be added with corresponding parameters, the following bands are always added to the data cube:\n\n- `mask`: A data mask that indicates which values are valid (1), invalid (0) or contain no-data (null).\n- `local_incidence_angle`: A band with DEM-based local incidence angles in degrees.\n\nThe data returned is CARD4L compliant with corresponding metadata.","schema":{"subtype":"raster-cube","type":"object"}},"summary":"CARD4L compliant SAR NRB generation"},{"categories":["math > constants"],"description":"Defines a constant value that can be reused in multiple places of a process.","id":"constant","parameters":[{"description":"The value of the constant.","name":"x","schema":{"description":"Any data type."}}],"returns":{"description":"The value of the constant.","schema":{"description":"Any data type."}},"summary":"Define a constant value"},{"categories":["development"],"description":"This process can be used to add runtime information to the logs, e.g. for debugging purposes. This process should be used with caution and it is recommended to remove the process in production workflows. For example, logging each value or array individually in a process such as ``apply()`` or ``reduce_dimension()`` could lead to a (too) large number of log entries. Several data structures (e.g. data cubes) are too large to log and will only return summaries of their contents.\n\nThe data provided in the parameter `data` is returned without changes.","experimental":true,"id":"inspect","parameters":[{"description":"Data to log.","name":"data","schema":{"description":"Any data type is allowed."}},{"default":"","description":"A message to send in addition to the data.","name":"message","optional":true,"schema":{"type":"string"}},{"default":"User","description":"A label to help identify one or more log entries originating from this process in the list of all log entries. It can help to group or filter log entries and is usually not unique.","name":"code","optional":true,"schema":{"type":"string"}},{"default":"info","description":"The severity level of this message, defaults to `info`.","name":"level","optional":true,"schema":{"enum":["error","warning","info","debug"],"type":"string"}}],"returns":{"description":"The data as passed to the `data` parameter without any modification.","schema":{"description":"Any data type is allowed."}},"summary":"Add information to the logs"},{"description":"Sleep for given amount of seconds (and just pass-through given data).","id":"sleep","parameters":[{"description":"Data to pass through.","name":"data","optional":true,"schema":{}},{"description":"Number of seconds to sleep.","name":"seconds","optional":false,"schema":{"type":"number"}}],"returns":{"description":"Original data","schema":{}}},{"description":"Discards given data. Used for side-effecting purposes.","id":"discard_result","parameters":[{"description":"Data to discard.","name":"data","optional":true,"schema":{}}],"returns":{"description":"Nothing","schema":{}}},{"categories":["date & time"],"description":"Based on a given date (and optionally time), calculates a new date (and time if given) by adding or subtracting a given temporal period.\n\nSome specifics about dates and times need to be taken into account:\n\n* This process doesn't have any effect on the time zone.\n* It doesn't take daylight saving time (DST) into account as only dates and times in UTC (with potential numerical time zone modifier) are supported.\n* Leap years are implemented in a way that computations handle them gracefully (see parameter `unit` for details).\n* Leap seconds are mostly ignored in manipulations as they don't follow a regular pattern. Leap seconds can be passed to the process, but will never be returned.","examples":[{"arguments":{"date":"2020-02-01T17:22:45Z","unit":"month","value":6},"returns":"2020-08-01T17:22:45Z"},{"arguments":{"date":"2021-03-31T00:00:00+02:00","unit":"day","value":-7},"returns":"2021-03-24T00:00:00+02:00"},{"arguments":{"date":"2020-02-29T17:22:45Z","unit":"year","value":1},"description":"Adding a year to February 29th in a leap year will result in February 28th in the next (non-leap) year.","returns":"2021-02-28T17:22:45Z"},{"arguments":{"date":"2020-01-31","unit":"month","value":1},"description":"Adding a month to January 31th will result in February 29th in leap years.","returns":"2020-02-29"},{"arguments":{"date":"2016-12-31T23:59:59Z","unit":"second","value":1},"description":"The process skips over the leap second `2016-12-31T23:59:60Z`.","returns":"2017-01-01T00:00:00Z"},{"arguments":{"date":"2018-12-31T17:22:45Z","unit":"millisecond","value":1150},"description":"Milliseconds can be added or subtracted. If not given, the default value is `0`.","returns":"2018-12-31T17:22:46.150Z"},{"arguments":{"date":"2018-01-01","unit":"hour","value":25},"returns":"2018-01-02"},{"arguments":{"date":"2018-01-01","unit":"hour","value":-1},"returns":"2017-12-31"}],"experimental":true,"id":"date_shift","parameters":[{"description":"The date (and optionally time) to manipulate.\n\nIf the given date doesn't include the time, the process assumes that the time component is `00:00:00Z` (i.e. midnight, in UTC). The millisecond part of the time is optional and defaults to `0` if not given.","name":"date","schema":[{"format":"date-time","subtype":"date-time","type":"string"},{"format":"date","subtype":"date","type":"string"}]},{"description":"The period of time in the unit given that is added (positive numbers) or subtracted (negative numbers). The value `0` doesn't have any effect.","name":"value","schema":{"type":"integer"}},{"description":"The unit for the value given. The following pre-defined units are available:\n\n- millisecond: Milliseconds\n- second: Seconds - leap seconds are ignored in computations.\n- minute: Minutes\n- hour: Hours\n- day: Days - changes only the the day part of a date\n- week: Weeks (equivalent to 7 days)\n- month: Months\n- year: Years\n\nManipulations with the unit `year`, `month`, `week` or `day` do never change the time. If any of the manipulations result in an invalid date or time, the corresponding part is rounded down to the next valid date or time respectively. For example, adding a month to `2020-01-31` would result in `2020-02-29`.","name":"unit","schema":{"enum":["millisecond","second","minute","hour","day","week","month","year"],"type":"string"}}],"returns":{"description":"The manipulated date. If a time component was given in the parameter `date`, the time component is returned with the date.","schema":[{"format":"date-time","subtype":"date-time","type":"string"},{"format":"date","subtype":"date","type":"string"}]},"summary":"Manipulates dates and times by addition or subtraction"},{"categories":["comparison","date & time"],"description":"By default, this process checks whether `x` is later than or equal to `min` and before or equal to `max`.\n\nIf `exclude_max` is set to `true` the upper bound is excluded so that the process checks whether `x` is later than or equal to `min` and before `max`.\n\nLower and upper bounds are not allowed to be swapped. So `min` MUST be before or equal to `max` or otherwise the process always returns `false`.","examples":[{"arguments":{"max":"2022-01-01","min":"2021-01-01","x":"2020-01-01"},"returns":false}],"experimental":true,"id":"date_between","parameters":[{"description":"The value to check.","name":"x","schema":[{"description":"Date and time with a time zone.","format":"date-time","subtype":"date-time","type":"string"},{"description":"Date only, formatted as `YYYY-MM-DD`. The time zone is UTC. Missing time components are all 0.","format":"date","subtype":"date","type":"string"},{"description":"Time only, formatted as HH:MM:SS. The time zone is UTC.","pattern":"^\\d{2}:\\d{2}:\\d{2}$","subtype":"time","type":"string"}]},{"description":"Lower boundary (inclusive) to check against.","name":"min","schema":[{"description":"Date and time with a time zone.","format":"date-time","subtype":"date-time","type":"string"},{"description":"Date only, formatted as `YYYY-MM-DD`. The time zone is UTC. Missing time components are all 0.","format":"date","subtype":"date","type":"string"},{"description":"Time only, formatted as HH:MM:SS. The time zone is UTC.","pattern":"^\\d{2}:\\d{2}:\\d{2}$","subtype":"time","type":"string"}]},{"description":"Upper boundary (inclusive) to check against.","name":"max","schema":[{"description":"Date and time with a time zone.","format":"date-time","subtype":"date-time","type":"string"},{"description":"Date only, formatted as `YYYY-MM-DD`. The time zone is UTC. Missing time components are all 0.","format":"date","subtype":"date","type":"string"},{"description":"Time only, formatted as HH:MM:SS. The time zone is UTC.","pattern":"^\\d{2}:\\d{2}:\\d{2}$","subtype":"time","type":"string"}]},{"default":false,"description":"Exclude the upper boundary `max` if set to `true`. Defaults to `false`.","name":"exclude_max","optional":true,"schema":{"type":"boolean"}}],"returns":{"description":"`true` if `x` is between the specified bounds, otherwise `false`.","schema":{"type":["boolean","null"]}},"summary":"Between comparison for dates and times"},{"categories":["logic","comparison","masks"],"description":"If the value passed is `true`, returns the value of the `accept` parameter, otherwise returns the value of the `reject` parameter.\n\nThis is basically an if-then-else construct as in other programming languages.","examples":[{"arguments":{"accept":"A","reject":"B","value":true},"returns":"A"},{"arguments":{"accept":"A","reject":"B","value":null},"returns":"B"},{"arguments":{"accept":[1,2,3],"reject":[4,5,6],"value":false},"returns":[4,5,6]},{"arguments":{"accept":123,"value":true},"returns":123},{"arguments":{"accept":1,"value":false},"returns":null}],"id":"if","parameters":[{"description":"A boolean value.","name":"value","schema":{"type":["boolean","null"]}},{"description":"A value that is returned if the boolean value is `true`.","name":"accept","schema":{"description":"Any data type is allowed."}},{"default":null,"description":"A value that is returned if the boolean value is **not** `true`. Defaults to `null`.","name":"reject","optional":true,"schema":{"description":"Any data type is allowed."}}],"returns":{"description":"Either the `accept` or `reject` argument depending on the given boolean value.","schema":{"description":"Any data type is allowed."}},"summary":"If-Then-Else conditional"},{"categories":["arrays"],"description":"Appends a new value to the end of the array, which may also include a new label for labeled arrays.","examples":[{"arguments":{"data":[1,2],"value":3},"returns":[1,2,3]}],"exceptions":{"LabelExists":{"message":"An array element with the specified label already exists."}},"id":"array_append","parameters":[{"description":"An array.","name":"data","schema":{"items":{"description":"Any data type is allowed."},"type":"array"}},{"description":"Value to append to the array.","name":"value","schema":{"description":"Any data type is allowed."}},{"default":null,"description":"If the given array is a labeled array, a new label for the new value should be given. If not given or `null`, the array index as string is used as the label. If in any case the label exists, a `LabelExists` exception is thrown.","name":"label","optional":true,"schema":{"type":["string","null"]}}],"returns":{"description":"The new array with the value being appended.","schema":{"items":{"description":"Any data type is allowed."},"type":"array"}},"summary":"Append a value to an array"},{"categories":["arrays","math","math > interpolation"],"description":"Performs a linear interpolation for each of the no-data values (`null`) in the array given, except for leading and trailing no-data values.\n\nThe linear interpolants are defined by the array indices or labels (x) and the values in the array (y).","examples":[{"arguments":{"data":[null,1,null,6,null,-8]},"returns":[null,1,3.5,6,-1,-8]},{"arguments":{"data":[null,1,null,null]},"returns":[null,1,null,null]}],"id":"array_interpolate_linear","links":[{"href":"https://en.wikipedia.org/wiki/Linear_interpolation","rel":"about","title":"Linear interpolation explained by Wikipedia"}],"parameters":[{"description":"An array of numbers and no-data values.\n\nIf the given array is a labeled array, the labels must have a natural/inherent label order and the process expects the labels to be sorted accordingly. This is the default behavior in openEO for spatial and temporal dimensions.","name":"data","schema":{"items":{"type":["number","null"]},"type":"array"}}],"returns":{"description":"An array with no-data values being replaced with interpolated values. If not at least 2 numerical values are available in the array, the array stays the same.","schema":{"items":{"type":["number","null"]},"type":"array"}},"summary":"One-dimensional linear interpolation for arrays"},{"categories":["arrays"],"description":"Concatenates two arrays into a single array by appending the second array to the first array.\n\nArray labels are kept only if both given arrays are labeled. Otherwise, the labels get discarded from both arrays. The process fails with an `ArrayLabelConflict` exception if a label is present in both arrays. Conflicts must be resolved beforehand.","examples":[{"arguments":{"array1":[1.5,2.5],"array2":[5]},"description":"Concatenates two numerical arrays.","returns":[1.5,2.5,5]},{"arguments":{"array1":["a","b"],"array2":[1,2]},"description":"Concatenates two arrays containing different data type, may not always be supported.","returns":["a","b",1,2]}],"exceptions":{"ArrayLabelConflict":{"message":"At least one label exists in both arrays and the conflict must be resolved before."}},"id":"array_concat","parameters":[{"description":"The first array.","name":"array1","schema":{"items":{"description":"Any data type is allowed."},"type":"array"}},{"description":"The second array.","name":"array2","schema":{"items":{"description":"Any data type is allowed."},"type":"array"}}],"returns":{"description":"The merged array.","schema":{"items":{"description":"Any data type is allowed."},"type":"array"}},"summary":"Merge two arrays"},{"categories":["arrays"],"description":"Creates a new array, which by default is empty.\n\nThe second parameter `repeat` allows to add the given array multiple times to the new array.\n\nIn most cases you can simply pass a (native) array to processes directly, but this process is especially useful to create a new array that is getting returned by a child process, for example in ``apply_dimension()``.","examples":[{"arguments":{},"returns":[]},{"arguments":{"data":["this","is","a","test"]},"returns":["this","is","a","test"]},{"arguments":{"data":[null],"repeat":3},"returns":[null,null,null]},{"arguments":{"data":[1,2,3],"repeat":2},"returns":[1,2,3,1,2,3]}],"id":"array_create","parameters":[{"default":[],"description":"A (native) array to fill the newly created array with. Defaults to an empty array.","name":"data","optional":true,"schema":{"items":{"description":"Any data type is allowed."},"type":"array"}},{"default":1,"description":"The number of times the (native) array specified in `data` is repeatedly added after each other to the new array being created. Defaults to `1`.","name":"repeat","optional":true,"schema":{"minimum":1,"type":"integer"}}],"returns":{"description":"The newly created array.","schema":{"items":{"description":"Any data type is allowed."},"type":"array"}},"summary":"Create an array"},{"categories":["arrays"],"description":"Applies a process to each individual value in the array. This is basically what other languages call either a `for each` loop or a `map` function.","id":"array_apply","parameters":[{"description":"An array.","name":"data","schema":{"items":{"description":"Any data type is allowed."},"type":"array"}},{"description":"A process that accepts and returns a single value and is applied on each individual value in the array. The process may consist of multiple sub-processes and could, for example, consist of processes such as ``absolute()`` or ``linear_scale_range()``.","name":"process","schema":{"parameters":[{"description":"The value of the current element being processed.","name":"x","schema":{"description":"Any data type."}},{"description":"The zero-based index of the current element being processed.","name":"index","schema":{"minimum":0,"type":"integer"}},{"default":null,"description":"The label of the current element being processed. Only populated for labeled arrays.","name":"label","optional":true,"schema":[{"type":"number"},{"type":"string"},{"type":"null"}]},{"default":null,"description":"Additional data passed by the user.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"The value to be set in the new array.","schema":{"description":"Any data type."}},"subtype":"process-graph","type":"object"}},{"default":null,"description":"Additional data to be passed to the process.","name":"context","optional":true,"schema":{"description":"Any data type."}}],"returns":{"description":"An array with the newly computed values. The number of elements are the same as for the original array.","schema":{"items":{"description":"Any data type is allowed."},"type":"array"}},"summary":"Apply a process to each array element"},{"categories":["cubes","elevation"],"description":"Computes the aspect (in radians, from due North) from elevation data.","experimental":true,"id":"aspect","parameters":[{"description":"Data cube containing elevation data.","name":"data","optional":false,"schema":{"subtype":"raster-cube","type":"object"}}],"returns":{"description":"A data cube with calculated aspects for each band, the band names are the original band names with a '_aspect' suffix.","schema":{"subtype":"raster-cube","type":"object"}},"summary":"Compute aspect on elevation data"},{"categories":["cubes","math","elevation"],"description":"Computes the slope (in radians, relative to the horizontal plane) from elevation data.","experimental":true,"id":"slope","parameters":[{"description":"Data cube containing elevation data.","name":"data","optional":false,"schema":{"subtype":"raster-cube","type":"object"}}],"returns":{"description":"A data cube with calculated slopes for each band, the band names are the original band names with a '_slope' suffix.","schema":{"subtype":"raster-cube","type":"object"}},"summary":"Compute slope on elevation data"},{"categories":["cubes"],"description":"Converts the data type of the cube to the desired data type.","experimental":true,"id":"convert_data_type","parameters":[{"description":"The data cube.","name":"data","optional":false,"schema":{"subtype":"raster-cube","type":"object"}},{"description":"The desired data type, represented as a string.","name":"data_type","optional":false,"schema":{"type":"string"}}],"returns":{"description":"A data cube with desired data type.","schema":{"subtype":"raster-cube","type":"object"}},"summary":"Converts the data type of the cube"},{"categories":["texts","comparison"],"description":"Checks whether the text (also known as *string*) specified for `data` contains the text specified for `pattern` at the beginning. Both are expected to be encoded in UTF-8 by default. The no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"data":"Lorem ipsum dolor sit amet","pattern":"amet"},"returns":false},{"arguments":{"data":"Lorem ipsum dolor sit amet","pattern":"Lorem"},"returns":true},{"arguments":{"data":"Lorem ipsum dolor sit amet","pattern":"lorem"},"returns":false},{"arguments":{"case_sensitive":false,"data":"Lorem ipsum dolor sit amet","pattern":"lorem"},"returns":true},{"arguments":{"case_sensitive":false,"data":"\u00c4","pattern":"\u00e4"},"returns":true},{"arguments":{"data":null,"pattern":"null"},"returns":null}],"id":"text_begins","parameters":[{"description":"Text in which to find something at the beginning.","name":"data","schema":{"type":["string","null"]}},{"description":"Text to find at the beginning of `data`. Regular expressions are not supported.","name":"pattern","schema":{"type":"string"}},{"default":true,"description":"Case sensitive comparison can be disabled by setting this parameter to `false`.","name":"case_sensitive","optional":true,"schema":{"type":"boolean"}}],"returns":{"description":"`true` if `data` begins with `pattern`, false` otherwise.","schema":{"type":["boolean","null"]}},"summary":"Text begins with another text"},{"categories":["texts","comparison"],"description":"Checks whether the text (also known as *string*) specified for `data` contains the text specified for `pattern`. Both are expected to be encoded in UTF-8 by default. The no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"data":"Lorem ipsum dolor sit amet","pattern":"openEO"},"returns":false},{"arguments":{"data":"Lorem ipsum dolor sit amet","pattern":"ipsum dolor"},"returns":true},{"arguments":{"data":"Lorem ipsum dolor sit amet","pattern":"Ipsum Dolor"},"returns":false},{"arguments":{"case_sensitive":false,"data":"Lorem ipsum dolor sit amet","pattern":"SIT"},"returns":true},{"arguments":{"case_sensitive":false,"data":"\u00c4\u00d6\u00dc","pattern":"\u00f6"},"returns":true},{"arguments":{"data":null,"pattern":"null"},"returns":null}],"id":"text_contains","parameters":[{"description":"Text in which to find something in.","name":"data","schema":{"type":["string","null"]}},{"description":"Text to find in `data`. Regular expressions are not supported.","name":"pattern","schema":{"type":"string"}},{"default":true,"description":"Case sensitive comparison can be disabled by setting this parameter to `false`.","name":"case_sensitive","optional":true,"schema":{"type":"boolean"}}],"returns":{"description":"`true` if `data` contains the `pattern`, false` otherwise.","schema":{"type":["boolean","null"]}},"summary":"Text contains another text"},{"categories":["texts","comparison"],"description":"Checks whether the text (also known as *string*) specified for `data` contains the text specified for `pattern` at the end. Both are expected to be encoded in UTF-8 by default. The no-data value `null` is passed through and therefore gets propagated.","examples":[{"arguments":{"data":"Lorem ipsum dolor sit amet","pattern":"amet"},"returns":true},{"arguments":{"data":"Lorem ipsum dolor sit amet","pattern":"AMET"},"returns":false},{"arguments":{"data":"Lorem ipsum dolor sit amet","pattern":"Lorem"},"returns":false},{"arguments":{"case_sensitive":false,"data":"Lorem ipsum dolor sit amet","pattern":"AMET"},"returns":true},{"arguments":{"case_sensitive":false,"data":"\u00c4","pattern":"\u00e4"},"returns":true},{"arguments":{"data":null,"pattern":"null"},"returns":null}],"id":"text_ends","parameters":[{"description":"Text in which to find something at the end.","name":"data","schema":{"type":["string","null"]}},{"description":"Text to find at the end of `data`. Regular expressions are not supported.","name":"pattern","schema":{"type":"string"}},{"default":true,"description":"Case sensitive comparison can be disabled by setting this parameter to `false`.","name":"case_sensitive","optional":true,"schema":{"type":"boolean"}}],"returns":{"description":"`true` if `data` ends with `pattern`, false` otherwise.","schema":{"type":["boolean","null"]}},"summary":"Text ends with another text"},{"categories":["texts"],"description":"Merges text representations (also known as *string*) of a set of elements to a single text, having the separator between each element.","examples":[{"arguments":{"data":["Hello","World"],"separator":" "},"returns":"Hello World"},{"arguments":{"data":[1,2,3,4,5,6,7,8,9,0]},"returns":"1234567890"},{"arguments":{"data":[null,true,false,1,-1.5,"\u00df"],"separator":"\n"},"returns":"null\ntrue\nfalse\n1\n-1.5\n\u00df"},{"arguments":{"data":[2,0],"separator":1},"returns":"210"},{"arguments":{"data":[]},"returns":""}],"id":"text_concat","parameters":[{"description":"A set of elements. Numbers, boolean values and null values get converted to their (lower case) string representation. For example: `1` (integer), `-1.5` (number), `true` / `false` (boolean values)","name":"data","schema":{"items":{"type":["string","number","boolean","null"]},"type":"array"}},{"default":"","description":"A separator to put between each of the individual texts. Defaults to an empty string.","name":"separator","optional":true,"schema":{"type":["string","number","boolean","null"]}}],"returns":{"description":"A string containing a string representation of all the array elements in the same order, with the separator between each element.","schema":{"type":"string"}},"summary":"Concatenate elements to a single text"},{"categories":["math > indices","vegetation indices"],"description":"Computes the normalized difference for two bands. The normalized difference is computed as *`(x - y) / (x + y)`*.\n\nThis process could be used for a number of remote sensing indices such as:\n\n* [NDVI](https://eos.com/ndvi/): `x` = NIR band, `y` = red band\n* [NDWI](https://eos.com/ndwi/): `x` = NIR band, `y` = SWIR band\n* [NDSI](https://eos.com/ndsi/): `x` = green band, `y` = SWIR band\n\nSome back-ends may have native processes such as ``ndvi()`` available for convenience.","id":"normalized_difference","links":[{"href":"https://eos.com/ndvi/","rel":"related","title":"NDVI explained by EOS"},{"href":"https://eos.com/ndwi/","rel":"related","title":"NDWI explained by EOS"},{"href":"https://eos.com/ndsi/","rel":"related","title":"NDSI explained by EOS"}],"parameters":[{"description":"The value for the first band.","name":"x","schema":{"type":"number"}},{"description":"The value for the second band.","name":"y","schema":{"type":"number"}}],"process_graph":{"add":{"arguments":{"x":{"from_parameter":"x"},"y":{"from_parameter":"y"}},"process_id":"add"},"divide":{"arguments":{"x":{"from_node":"subtract"},"y":{"from_node":"add"}},"process_id":"divide","result":true},"subtract":{"arguments":{"x":{"from_parameter":"x"},"y":{"from_parameter":"y"}},"process_id":"subtract"}},"returns":{"description":"The computed normalized difference.","schema":{"maximum":1,"minimum":-1,"type":"number"}},"summary":"Normalized difference"},{"description":"Compresses a data cube by means of the CORSA algorithm.","experimental":true,"id":"corsa_compress","parameters":[{"description":"a Sentinel 2 data cube with 10 bands that correspond to: \"B02\", \"B03\", \"B04\", \"B05\", \"B06\", \"B07\", \"B08\", \"B8A\", \"B11\" and \"B12\".","name":"data","optional":false,"schema":{"subtype":"datacube","type":"object"}}],"returns":{"description":"a data cube consisting of two bands: \"level_0\" and \"level_1\"","schema":{"subtype":"datacube","type":"object"}}},{"description":"Decompresses a data cube that was compressed by the CORSA algorithm to reconstruct the original data cube.","experimental":true,"id":"corsa_decompress","parameters":[{"description":"a data cube consisting of two bands: \"level_0\" and \"level_1\"","name":"data","optional":false,"schema":{"subtype":"datacube","type":"object"}}],"returns":{"description":"a Sentinel 2 data cube with 10 bands that correspond to: \"B02\", \"B03\", \"B04\", \"B05\", \"B06\", \"B07\", \"B08\", \"B8A\", \"B11\" and \"B12\".","schema":{"subtype":"datacube","type":"object"}}}],"version":"2.0.0-rc.1"}