gpm.accessor package

Submodules

gpm.accessor.methods module

This module defines GPM-API xarray accessors.

class gpm.accessor.methods.GPM_Base_Accessor(xarray_obj)

Bases: object

collocate(product, product_type='RS', version=None, scan_modes=None, variables=None, groups=None, verbose=True, decode_cf=True, chunks={})

Collocate another product on the dataset.

It assumes that along all the input dataset, there is an approximate collocated product.

crop(extent)

Crop xarray object by bounding box.

crop_by_continent(name)

Crop xarray object by continent name.

crop_by_country(name)

Crop xarray object by country name.

define_transect_slices(direction='cross_track', lon=None, lat=None, variable=None, transect_kwargs={})

property end_time

extent(padding=0)

Return the geographic extent (bbox) of the object.

get_crop_slices_by_continent(name)

Get subsetting slices given the continent name.

get_crop_slices_by_country(name)

Get subsetting slices given the country name.

get_crop_slices_by_extent(extent)

Get subsetting slices given the extent.

get_height_at_bin(bin)

Retrieve height values at specific range bins.

get_slices_contiguous_granules(min_size=2)

get_slices_contiguous_scans(min_size=2, min_n_scans=3)

get_slices_regular(min_size=None, min_n_scans=3)

get_slices_regular_time(tolerance=None, min_size=1)

get_slices_valid_geolocation(min_size=2)

get_variable_at_bin(bin, variable=None)

Retrieve variable values at specific range bins.

property has_contiguous_scans

property has_missing_granules

property has_regular_time

property has_valid_geolocation

property is_grid

property is_orbit

property is_regular

property is_spatial_2d

property is_spatial_3d

plot_map_mesh(x='lon', y='lat', ax=None, edgecolors='k', linewidth=0.1, add_background=True, fig_kwargs=None, subplot_kwargs=None, **plot_kwargs)

plot_map_mesh_centroids(x='lon', y='lat', ax=None, c='r', s=1, add_background=True, fig_kwargs=None, subplot_kwargs=None, **plot_kwargs)

plot_swath(ax=None, facecolor='orange', edgecolor='black', alpha=0.4, fig_kwargs=None, subplot_kwargs=None, add_background=True, **plot_kwargs)

plot_swath_lines(ax=None, x='lon', y='lat', linestyle='--', color='k', add_background=True, fig_kwargs=None, subplot_kwargs=None, **plot_kwargs)

plot_transect_line(ax, add_direction=True, text_kwargs={}, line_kwargs={}, **common_kwargs)

property pyresample_area

remap_on(dst_ds, radius_of_influence=20000, fill_value=nan)

Remap data from one dataset to another one.

select_transect(direction='cross_track', lon=None, lat=None, variable=None, transect_kwargs={}, keep_only_valid_variables=True)

slice_range_at_height(height)

Slice the 3D array at a given height.

slice_range_at_max_value(variable=None)

Slice the 3D arrays where the variable values are at maximum.

slice_range_at_min_value(variable=None)

Slice the 3D arrays where the variable values are at minimum.

slice_range_at_value(value, variable=None)

Slice the 3D arrays where the variable values are close to value.

slice_range_where_values(variable=None, vmin=-inf, vmax=inf)

Select the ‘range’ interval where values are within the [vmin, vmax] interval.

slice_range_with_valid_data(variable=None)

Select the ‘range’ interval with valid data.

property spatial_dimensions

property start_time

subset_by_time(start_time=None, end_time=None)

subset_by_time_slice(slice)

property vertical_dimension

class gpm.accessor.methods.GPM_DataArray_Accessor(xarray_obj)

Bases: GPM_Base_Accessor

get_slices_var_between(dim, vmin=-inf, vmax=inf, criteria='all')

get_slices_var_equals(dim, values, union=True, criteria='all')

integrate_profile_concentration(name, scale_factor=None, units=None)

plot_image(ax=None, x=None, y=None, add_colorbar=True, interpolation='nearest', fig_kwargs=None, cbar_kwargs=None, **plot_kwargs)

plot_map(ax=None, x='lon', y='lat', add_colorbar=True, add_swath_lines=True, add_background=True, interpolation='nearest', rgb=False, fig_kwargs=None, subplot_kwargs=None, cbar_kwargs=None, **plot_kwargs)

plot_transect(ax=None, add_colorbar=True, zoom=True, fig_kwargs=None, cbar_kwargs=None, **plot_kwargs)

title(prefix_product=True, add_timestep=True, time_idx=None, resolution='m', timezone='UTC')

class gpm.accessor.methods.GPM_Dataset_Accessor(xarray_obj)

Bases: GPM_Base_Accessor

available_retrievals()

Available GPM-API retrievals for that GPM product.

property frequency_variables

plot_image(variable, ax=None, x=None, y=None, add_colorbar=True, interpolation='nearest', fig_kwargs=None, cbar_kwargs=None, **plot_kwargs)

plot_map(variable, ax=None, x='lon', y='lat', rgb=False, add_colorbar=True, add_swath_lines=True, add_background=True, interpolation='nearest', fig_kwargs=None, subplot_kwargs=None, cbar_kwargs=None, **plot_kwargs)

plot_transect(variable, ax=None, add_colorbar=True, zoom=True, fig_kwargs=None, cbar_kwargs=None, **plot_kwargs)

retrieve(name, **kwargs)

Retrieve a GPM-API variable.

select_spatial_2d_variables(strict=False, squeeze=True)

select_spatial_3d_variables(strict=False, squeeze=True)

set_encoding(encoding_dict=None)

slice_range_at_temperature(temperature, variable_temperature='airTemperature')

Slice the 3D arrays along a specific isotherm.

property spatial_2d_variables

property spatial_3d_variables

title(add_timestep=True, time_idx=None, resolution='m', timezone='UTC')

to_dask_dataframe()

Convert xr.Dataset to Dask Dataframe. Expects xr.Dataset with only 2D spatial DataArrays.

to_pandas_dataframe()

Convert xr.Dataset to Pandas Dataframe. Expects xr.Dataset with only 2D spatial DataArrays.

property variables

Module contents

This directory defines GPM-API xarray accessors.

class gpm.accessor.GPM_DataArray_Accessor(xarray_obj)

Bases: GPM_Base_Accessor

get_slices_var_between(dim, vmin=-inf, vmax=inf, criteria='all')

get_slices_var_equals(dim, values, union=True, criteria='all')

integrate_profile_concentration(name, scale_factor=None, units=None)

plot_image(ax=None, x=None, y=None, add_colorbar=True, interpolation='nearest', fig_kwargs=None, cbar_kwargs=None, **plot_kwargs)

plot_map(ax=None, x='lon', y='lat', add_colorbar=True, add_swath_lines=True, add_background=True, interpolation='nearest', rgb=False, fig_kwargs=None, subplot_kwargs=None, cbar_kwargs=None, **plot_kwargs)

plot_transect(ax=None, add_colorbar=True, zoom=True, fig_kwargs=None, cbar_kwargs=None, **plot_kwargs)

title(prefix_product=True, add_timestep=True, time_idx=None, resolution='m', timezone='UTC')

class gpm.accessor.GPM_Dataset_Accessor(xarray_obj)

Bases: GPM_Base_Accessor

available_retrievals()

Available GPM-API retrievals for that GPM product.

property frequency_variables

plot_image(variable, ax=None, x=None, y=None, add_colorbar=True, interpolation='nearest', fig_kwargs=None, cbar_kwargs=None, **plot_kwargs)

plot_map(variable, ax=None, x='lon', y='lat', rgb=False, add_colorbar=True, add_swath_lines=True, add_background=True, interpolation='nearest', fig_kwargs=None, subplot_kwargs=None, cbar_kwargs=None, **plot_kwargs)

plot_transect(variable, ax=None, add_colorbar=True, zoom=True, fig_kwargs=None, cbar_kwargs=None, **plot_kwargs)

retrieve(name, **kwargs)

Retrieve a GPM-API variable.

select_spatial_2d_variables(strict=False, squeeze=True)

select_spatial_3d_variables(strict=False, squeeze=True)

set_encoding(encoding_dict=None)

slice_range_at_temperature(temperature, variable_temperature='airTemperature')

Slice the 3D arrays along a specific isotherm.

property spatial_2d_variables

property spatial_3d_variables

title(add_timestep=True, time_idx=None, resolution='m', timezone='UTC')

to_dask_dataframe()

Convert xr.Dataset to Dask Dataframe. Expects xr.Dataset with only 2D spatial DataArrays.

to_pandas_dataframe()

Convert xr.Dataset to Pandas Dataframe. Expects xr.Dataset with only 2D spatial DataArrays.

property variables