podpac.algorithm.Convolution¶
-
class
podpac.algorithm.
Convolution
(**kwargs)[source]¶ Bases:
podpac.core.algorithm.algorithm.UnaryAlgorithm
Compute a general convolution over a source node.
This node automatically resizes the requested coordinates to avoid edge effects.
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source
¶ Source node on which convolution will be performed.
- Type
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kernel
¶ The convolution kernel. This kernel must include the dimensions of source node outputs. The dimensions for this array are labelled by kernel_dims. Any dimensions not in the soucr nodes outputs will be summed over.
- Type
np.ndarray, optional
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kernel_dims
¶ A list of the dimensions for the kernel axes. The dimensions in this list must match the coordinates in the source, or contain additional dimensions, and the order does not need to match. Any extra dimensions are summed out.
- Type
list, optional
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kernel_type
¶ If kernel is not defined, kernel_type will create a kernel based on the inputs, and it will have the same number of axes as kernel_ndim. The format for the created kernels is ‘<kernel_type>, <kernel_size>, <kernel_params>’. Any kernel defined in scipy.signal as well as mean can be used. For example: kernel_type = ‘mean, 8’ or kernel_type = ‘gaussian,16,8’ are both valid. Note: These kernels are automatically normalized such that kernel.sum() == 1
- Type
str, optional
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
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_url
(url)Create podpac Node from a WMS/WCS request.
get_cache
(key[, coordinates])Get cached data for this node.
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.
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.
definition
dtype
A trait which allows any value.
force_eval
A boolean (True, False) trait.
hash
hash for this node, used in caching and to determine equality.
inputs
json
Definition for this node in JSON format.
json_pretty
Definition for this node in JSON format, with indentation suitable for display.
A coercing numpy array trait.
An instance of a Python list.
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
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__init__
(**kwargs)¶ Do not overwrite me
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kernel
A coercing numpy array trait.
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kernel_dims
An instance of a Python list.
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