API Reference

Top Level Imports

podpac.Node(**kwargs)

The base class for all Nodes, which defines the common interface for everything.

podpac.Coordinates(coords[, dims, crs, …])

Multidimensional Coordinates.

Nodes

podpac.Node(**kwargs)

The base class for all Nodes, which defines the common interface for everything.

podpac.NodeException

Summary

Coordinates

podpac.coordinates.Coordinates(coords[, …])

Multidimensional Coordinates.

podpac.coordinates.Coordinates1d([name, …])

Base class for 1-dimensional coordinates.

podpac.coordinates.ArrayCoordinates1d(…[, …])

1-dimensional array of coordinates.

podpac.coordinates.UniformCoordinates1d(…)

1-dimensional array of uniformly-spaced coordinates defined by a start, stop, and step.

podpac.coordinates.StackedCoordinates(coords)

Stacked coordinates.

podpac.coordinates.GroupCoordinates(coords_list)

List of multi-dimensional Coordinates.

Utilities

podpac.coordinates.crange(start, stop, step)

Create uniformly-spaced 1d coordinates with a start, stop, and step.

podpac.coordinates.clinspace(start, stop, size)

Create uniformly-spaced 1d or stacked coordinates with a start, stop, and size.

podpac.coordinates.merge_dims(coords_list)

Merge the coordinates.

podpac.coordinates.concat(coords_list)

Combine the given coordinates by concatenating coordinate values in each dimension.

podpac.coordinates.union(coords_list)

Combine the given coordinates by collecting the unique, sorted coordinate values in each dimension.

Data Sources

Data Types

podpac.data.Array(**kwargs)

Create a DataSource from an array

podpac.data.PyDAP(**kwargs)

Create a DataSource from an OpenDAP server feed.

podpac.data.Rasterio(**kwargs)

Create a DataSource using Rasterio.

podpac.data.WCS(**kwargs)

Create a DataSource from an OGC-complient WCS service

podpac.data.ReprojectedSource(**kwargs)

Create a DataSource with a different resolution from another Node.

podpac.data.S3(**kwargs)

Create a DataSource from a file on an S3 Bucket.

podpac.data.H5PY(**kwargs)

Create a DataSource node using h5py.

Utilities

podpac.data.DataSource(**kwargs)

Base node for any data obtained directly from a single source.

podpac.data.Interpolation([definition])

Create an interpolation class to handle one interpolation method per unstacked dimension.

podpac.data.InterpolationException

Custom label for interpolation exceptions

podpac.data.INTERPOLATION_SHORTCUTS

podpac.data.INTERPOLATION_DEFAULT

str(object=’‘) -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Interpolators

podpac.interpolators.Interpolator(**kwargs)

Interpolation Method

podpac.interpolators.NearestNeighbor(**kwargs)

Nearest Neighbor Interpolation

podpac.interpolators.NearestPreview(**kwargs)

Nearest Neighbor (Preview) Interpolation

podpac.interpolators.Rasterio(**kwargs)

Rasterio Interpolation

podpac.interpolators.ScipyGrid(**kwargs)

Scipy Interpolation

podpac.interpolators.ScipyPoint(**kwargs)

Scipy Point Interpolation

Pipelines

podpac.pipeline.Pipeline(**kwargs)

Node defined by a JSON definition.

podpac.pipeline.PipelineError

Raised when parsing a Pipeline definition fails.

Pipeline Outputs

podpac.pipeline.Output(*args, **kwargs)

Base class for Pipeline Outputs.

podpac.pipeline.NoOutput(node, name)

No Output

podpac.pipeline.FileOutput(node, name[, …])

Output a file to the local filesystem.

podpac.pipeline.FTPOutput(node, name[, url, …])

Output a file and send over FTP.

podpac.pipeline.S3Output(node, name[, …])

Output a file and send to S3

podpac.pipeline.ImageOutput(node, name[, …])

Output an image in RAM

Algorithm Nodes

podpac.algorithm.Algorithm(**kwargs)

Base class for algorithm and computation nodes.

General Purpose

podpac.algorithm.Arithmetic(**kwargs)

Create a simple point-by-point computation of up to 7 different input nodes.

podpac.algorithm.SinCoords(**kwargs)

A simple test node that creates a data based on coordinates and trigonometric (sin) functions.

podpac.algorithm.Arange(**kwargs)

A simple test node that gives each value in the output a number.

podpac.algorithm.CoordData(**kwargs)

Extracts the coordinates from a request and makes it available as a data

Statistical Methods

podpac.algorithm.Min(**kwargs)

Computes the minimum across dimension(s)

podpac.algorithm.Max(**kwargs)

Computes the maximum across dimension(s)

podpac.algorithm.Sum(**kwargs)

Computes the sum across dimension(s)

podpac.algorithm.Count(**kwargs)

Counts the finite values across dimension(s)

podpac.algorithm.Mean(**kwargs)

Computes the mean across dimension(s)

podpac.algorithm.Median(**kwargs)

Computes the median across dimension(s)

podpac.algorithm.Variance(**kwargs)

Computes the variance across dimension(s)

podpac.algorithm.StandardDeviation(**kwargs)

Computes the standard deviation across dimension(s)

podpac.algorithm.Skew(**kwargs)

Computes the skew across dimension(s)

podpac.algorithm.Kurtosis(**kwargs)

Computes the kurtosis across dimension(s)

podpac.algorithm.DayOfYear(**kwargs)

Group a time-dependent source node by day of year and compute a statistic for each group.

podpac.algorithm.GroupReduce(**kwargs)

Group a time-dependent source node and then compute a statistic for each result.

Coordinates Modification

podpac.algorithm.ExpandCoordinates(**kwargs)

Evaluate a source node with expanded coordinates.

podpac.algorithm.SelectCoordinates(**kwargs)

Evaluate a source node with select coordinates.

Signal Processing

podpac.algorithm.Convolution(**kwargs)

Compute a general convolution over a source node.

podpac.algorithm.SpatialConvolution(**kwargs)

Compute a lat-lon convolution over a source node.

podpac.algorithm.TimeConvolution(**kwargs)

Compute a temporal convolution over a source node.

Compositor Nodes

podpac.compositor.Compositor(**kwargs)

podpac.cache_native_coordinates

podpac.compositor.OrderedCompositor(**kwargs)

Compositor that combines sources based on their order in self.sources.

Datalib

podpac.datalib.smap

Specialized PODPAC nodes use to access SMAP data via OpenDAP from nsidc.

podpac.datalib.SMAP(**kwargs)

Compositor of all the SMAPDateFolder’s for every available SMAP date.

podpac.datalib.SMAPBestAvailable(**kwargs)

Compositor of SMAP-Sentinel and the Level 4 SMAP Analysis Update soil moisture

podpac.datalib.SMAPSource(**kwargs)

Accesses SMAP data given a specific openDAP URL.

podpac.datalib.SMAPPorosity(**kwargs)

Retrieve the specific SMAP property: Porosity

podpac.datalib.SMAPProperties(**kwargs)

Accesses properties related to the generation of SMAP products.

podpac.datalib.SMAPWilt(**kwargs)

Retrieve the specific SMAP property: Wilting Point

podpac.datalib.SMAP_PRODUCT_MAP

N-dimensional array with labeled coordinates and dimensions.

Utilities

Authentication

podpac.authentication.SessionWithHeaderRedirection

podpac.authentication.EarthDataSession([…])

Modified from: https://wiki.earthdata.nasa.gov/display/EL/How+To+Access+Data+With+Python overriding requests.Session.rebuild_auth to maintain headers when redirected

Settings

podpac.settings

Persistently stored podpac settings

Utils

podpac.utils

Utils Summary

Version

podpac.version.semver()

Return semantic version of current PODPAC installation

podpac.version.version()

Retrieve PODPAC semantic version as string

podpac.version.VERSION

tuple() -> empty tuple tuple(iterable) -> tuple initialized from iterable’s items

podpac.version.VERSION_INFO

Dictionary that remembers insertion order