geoips.xarray_utils package#

Submodules#

geoips.xarray_utils.data module#

Utilities for manipulating xarray Datasets and DataArrays.

geoips.xarray_utils.data.get_lat_lon_points(checklat, checklon, diff, sect_xarray, varname, drop=False)[source]#

Pull values from xarray Datasets in specified geographic location.

Return points a given distance around a specified lat/lon location, from xarray Datasets.

Parameters:

  • checklat (float) – latitude of interest

  • checklon (float) – longitude of interest

  • diff (float) – check +- diff of latitude and longitude

  • sect_xarray (Dataset) – xarray dataset containing ‘latitude’ ‘longitude’ and varname variables

  • varname (str) – variable name of data array to use for returning data values

Returns:

  • min value in range

  • max value in range

  • and number of points in range

Return type:

float, float, int

geoips.xarray_utils.data.get_lat_lon_points_numpy(checklat, checklon, diff, lat_array, lon_array, data_array)[source]#

Pull values from numpy arrays in specified geographic location.

Return points a given distance around a specified lat/lon location, from numpy arrays.

Parameters:

  • checklat (float) – latitude of interest

  • checklon (float) – longitude of interest

  • diff (float) – check +- diff of latitude and longitude

  • lat_array (ndarray) – numpy ndarray of latitude locations - same shape as lon_array and data_array

  • lon_array (ndarray) – numpy ndarray of longitude locations - same shape as lat_array and data_array

  • data_array (ndarray) – numpy ndarray data values - same shape as lat_array and lon_array

Returns:

  • min value in range

  • max value in range

  • and number of points in range

Return type:

float, float, int

geoips.xarray_utils.data.get_sectored_xarrays(xobjs, area_def, varlist, get_bg_xarrays=False, check_center=True, drop=False)[source]#

Get all xarray objects sectored to area_def.

Return primary dataset, as well as VIS/IR overlay datasets.

geoips.xarray_utils.data.get_vis_ir_bg(sect_xarray)[source]#

Find matching vis/ir background for data in sect_xarray.

geoips.xarray_utils.data.sector_xarray_dataset(full_xarray, area_def, varnames, lon_pad=3, lat_pad=0, verbose=False, hours_before_sector_time=18, hours_after_sector_time=6, drop=False)[source]#

Use the xarray to appropriately sector out data by lat/lon and time.

geoips.xarray_utils.data.sector_xarray_spatial(full_xarray, extent_lonlat, varnames, lon_pad=3, lat_pad=0, verbose=False, drop=False)[source]#

Sector an xarray object spatially. If full_xarray is None, return None.

Parameters:

  • full_xarray (xarray.Dataset) – xarray object to sector spatially

  • extent_lonlat (list of float) – Area to sector: [MINLON, MINLAT, MAXLON, MAXLAT]

  • varnames (list of str) – list of variable names that should be sectored based on ‘time’

  • drop (bool) – Specify whether to remove points with no coverage (rather than masking)

Returns:

  • if full_xarray is None, return None,

  • else return resulting xarray Dataset.

Return type:

xarray.Dataset

geoips.xarray_utils.data.sector_xarray_temporal(full_xarray, mindt, maxdt, varnames, verbose=False, drop=False)[source]#

Sector an xarray object temporally. If full_xarray is None, return None.

Parameters:

  • full_xarray (xarray.Dataset) – xarray object to sector temporally

  • mindt (datetime.datetime) – minimum datetime of desired data

  • maxdt (datetime.datetime) – maximum datetime of desired data

  • varnames (list of str) – list of variable names that should be sectored based on ‘time’, mindt, maxdt

Returns:

  • if full_xarray is None, return None

  • return full original xarray object if ‘time’ is not included in varnames list

  • else, return sectored xarray object with only the desired times, specified by mindt and maxdt

Return type:

xarray Dataset, or None

geoips.xarray_utils.data.sector_xarrays(xobjs, area_def, varlist, verbose=False, hours_before_sector_time=18, hours_after_sector_time=6, check_center=True, drop=False, lon_pad=3, lat_pad=0)[source]#

Return list of sectored xarray objects.

geoips.xarray_utils.time module#

Utils to handle time stamp information within xarray objects.

geoips.xarray_utils.time.get_datetime_from_datetime64(dt64)[source]#

Get a python datetime object from a numpy datetime64 object.

Parameters:

dt64 (numpy.datetime64') – numpy.datetime64 object

Returns:

Python datetime object

Return type:

datetime.datetime

Notes

Backwards compatible with numpy versions

geoips.xarray_utils.time.get_max_from_xarray_time(xarray_obj, varname)[source]#

Get the maximum time as a datetime object from xarray object.

Parameters:

  • xarray_obj (xarray.Dataset or xarray.DataArray) – xarray object from which to extract the maximum time

  • varname (str) – Timestamp variable name from which to extract the maximum time

Returns:

Python datetime.datetime object representing maximum time of the Dataset or DataArray

Return type:

datetime.datetime

geoips.xarray_utils.time.get_min_from_xarray_time(xarray_obj, varname)[source]#

Get the minimum time as a datetime object from xarray object.

Parameters:

  • xarray_obj (xarray.Dataset or xarray.DataArray) – xarray object from which to extract the minimum time

  • varname (str) – Timestamp variable name from which to extract the minimum time

Returns:

Python datetime.datetime object representing minimum time of the Dataset or DataArray

Return type:

datetime.datetime

geoips.xarray_utils.time.get_posix_from_datetime(dt)[source]#

Return the POSIX timestamp in seconds.

Parameters:

dt (datetime.datetime) – datetime object to convert to posix timestamp

Returns:

representing seconds since 1 January 1970 at 00Z (epoch seconds)

Return type:

long

Module contents#

Geoips xarray utils init file.