podpac.algorithm.Mask

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

Bases: Algorithm

Masks the source based on a boolean expression involving the mask (i.e. source[mask <bool_op> <bool_val> ] = <masked_val>). For a normal boolean mask input, default values for bool_op, bool_val and masked_val can be used.

source

The source that will be masked

Type:

podpac.Node

mask

The data that will be used to compute the mask

Type:

podpac.Node

masked_val

Default value is np.nan. The value that will replace the masked items.

Type:

float, optional

bool_val

Default value is 1. The value used to compare the mask when creating the boolean expression

Type:

float, optional

bool_op

Default value is ‘==’. One of [‘==’, ‘<’, ‘<=’, ‘>’, ‘>=’]

Type:

enum, optional

in_place

Default is False. If True, the source array will be changed in-place, which could affect the value of the source in other parts of the pipeline.

Type:

bool, optional

Examples

# Mask data from a boolean data node using the default behavior. # Create a boolean masked Node (as an example) b = Arithmetic(A=SinCoords(), eqn=’A>0) # Create the source node a = Arange() masked = Mask(source=a, mask=b)

# Create a node that make the following substitution “a[b > 0] = np.nan” a = Arange() b = SinCoords() masked = Mask(source=a, mask=b,

masked_val=np.nan, bool_val=0, bool_op=’>’ in_place=True)

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)	Sets the values in inputs['source'] to self.masked_val using (inputs['mask'] <self.bool_op> <self.bool_val>)
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()	Overwrite this method if a node needs to do any additional initialization after the standard initialization.
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
bool_op	An enum whose value must be in a given sequence.
bool_val	A float trait.
cache_ctrl	A trait whose value must be an instance of a specified class.
cache_output	A boolean (True, False) trait.
definition
dtype	An enum whose value must be in a given sequence.
force_eval	A boolean (True, False) trait.
hash
in_place	A boolean (True, False) trait.
inputs
json	Definition for this node in JSON format.
json_pretty	Definition for this node in JSON format, with indentation suitable for display.
mask
masked_val	A float trait.
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

algorithm(inputs, coordinates)

Sets the values in inputs[‘source’] to self.masked_val using (inputs[‘mask’] <self.bool_op> <self.bool_val>)

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

bool_op

An enum whose value must be in a given sequence.

bool_val

A float trait.

in_place

A boolean (True, False) trait.

mask

masked_val

A float trait.

source