podpac.algorithm.Generic

class podpac.algorithm.Generic(**kwargs: Any)

Bases: GenericInputs

Generic Algorithm Node that allows arbitrary Python code to be executed.

code

The multi-line code that will be evaluated. This code should assign “output” to the desired result, and “output” needs to be a “numpy array” or “xarray DataArray”

Type:

str

inputs

A dictionary of PODPAC nodes that will serve as the input data for the Python script

Type:

dict(str: podpac.Node)

Examples

a = SinCoords() b = Arange() code = ‘’’import numpy as np output = np.minimum(a, b) ‘’’ generic = Generic(code=code, a=a, b=b)

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
algorithm(inputs, coordinates)	Run the generic code.
create_output_array(coords[, data, attrs, ...])	Initialize an output data array
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()
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.
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

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.
code	A trait for unicode strings.
definition
dtype	An enum whose value must be in a given sequence.
force_eval	A boolean (True, False) trait.
hash
inputs	An instance of a Python dict.
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.
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

algorithm(inputs, coordinates)

Run the generic code.

inputs

Evaluated outputs of the input nodes. The keys are the attribute names.

Type:

dict

coordinates

Requested coordinates. Note that the inputs may contain with different coordinates.

Type:

podpac.Coordinates

Returns:

result – Algorithm result.

Return type:

UnitsDataArray

code

A trait for unicode strings.

init()