podpac.algorithm.Skew

class podpac.algorithm.Skew(**kwargs: Any)[source]

Bases: Reduce

Computes the skew across dimension(s)

TODO NaN behavior when there is NO data (currently different in reduce and reduce_chunked)

Alternative Constructors

from_definition(definition)

Create podpac Node from a dictionary definition.

from_json(s)

Create podpac Node from a JSON definition.

Methods

__init__(**kwargs)

Do not overwrite me

create_output_array(coords[, data, attrs, ...])

Initialize an output data array

dims_axes(output)

Finds the indices for the dimensions that will be reduced.

eval(coordinates, **kwargs)

Evaluate the node at the given coordinates.

eval_group(group)

Evaluate the node for each of the coordinates in the group.

find_coordinates()

Get the available coordinates for the inputs to the Node.

from_name_params(name[, params])

Create podpac Node from a WMS/WCS request.

from_url(url)

Create podpac Node from a WMS/WCS request.

get_bounds([crs])

Get the full available coordinate bounds for the Node.

get_cache(key[, coordinates])

Get cached data for this node.

get_ui_spec([help_as_html])

Get spec of node attributes for building a ui

has_cache(key[, coordinates])

Check for cached data for this node.

init()

Overwrite this method if a node needs to do any additional initialization after the standard initialization.

iteroutputs(coordinates, _selector)

Generator for the chunks of the output

load(path)

Create podpac Node from file.

probe([lat, lon, time, alt, crs])

Evaluates every part of a node / pipeline at a point and records which nodes are actively being used.

put_cache(data, key[, coordinates, expires, ...])

Cache data for this node.

reduce(x)

Computes the skew across dimension(s)

reduce_chunked(xs, output)

Computes the skew across a chunk

rem_cache(key[, coordinates, mode])

Clear cached data for this node.

save(path)

Write node to file.

trait_defaults(*names, **metadata)

Return a trait's default value or a dictionary of them

trait_has_value(name)

Returns True if the specified trait has a value.

trait_is_defined(name)

trait_values(**metadata)

A dict of trait names and their values.

Attributes

DimsTrait

attrs

List of node attributes

base_ref

Default reference/name in node definitions

cache_ctrl

A trait whose value must be an instance of a specified class.

cache_output

A boolean (True, False) trait.

chunk_size

Size of chunks for parallel processing or large arrays that do not fit in memory

definition

dims

dtype

An enum whose value must be in a given sequence.

force_eval

A boolean (True, False) trait.

hash

inputs

json

Definition for this node in JSON format.

json_pretty

Definition for this node in JSON format, with indentation suitable for display.

output

A trait for unicode strings.

outputs

An instance of a Python list.

source

style

A trait whose value must be an instance of a specified class.

units

A trait for unicode strings.

Members:

__init__(**kwargs)

Do not overwrite me

reduce(x)[source]

Computes the skew across dimension(s)

Parameters:

x (UnitsDataArray) – Source data.

Returns:

Skew of the source data over dims

Return type:

UnitsDataArray

reduce_chunked(xs, output)[source]

Computes the skew across a chunk

Parameters:

xs (iterable) – Iterable of sources

Returns:

Skew of the source data over dims

Return type:

UnitsDataArray