richardutils package#

Submodules#

richardutils.cli module#

richardutils.richardutils module#

richardutils.richardutils.cetrainbow()#

Make a CET perceptually uniform rainbow colormap newcmp = cetrainbow() cm.register_cmap(name=’cetrainbow’, cmap=newcmp)

To reverse: cet_r = ListedColormap(newcmp.colors[::-1])

cm.register_cmap(name=’cetrainbow_r’, cmap=cet_r)

richardutils.richardutils.clip_da(da, gdfpath)#

Clips a rioxarray by geodataframe polygons

Parameters:

  • da – rioxarray Data Array

  • gdfpath – Path to vector polygon dataset

Returns:

Clipped rioxarray

Examples

schaus = clip_da(‘dapath’, ‘gdfpath’)

richardutils.richardutils.clip_dabox(dapath, bb)#

Clips a rioxarray by bounding box

Parameters:

  • dapath – Path to raster

  • bb – boundingbox coordinates iterable xmin, ymin, xmax, ymax

Returns:

Clipped rioxarray

Examples

schaus = clip_dabox(‘dapath’, bb)

richardutils.richardutils.clip_raster(dapath, gdfpath)#

Clips a rioxarray by geodataframe polygons

Parameters:

  • dapath – Path to raster

  • gdfpath – Path to vector polygon dataset

Returns:

Clipped rioxarray

Examples

schaus = clip_da(‘dapath’, ‘gdfpath’)

richardutils.richardutils.create_vrt_for_geotiffs(directory)#
Parameters:

directory – Path to raster tifs

richardutils.richardutils.df_bb(df, bb, xcol='longitude', ycol='latitude')#

Clips a dataframe of points by a bounding box

Parameters:

  • df – a dataframe from csv

  • xcol – x coordinate [longitude, easting etc.]

  • ycol – y coordinate

  • bb – a bounding box

Returns:

df trimmed to bounding box

Examples

dfbb = df_bb(df,bb, ‘longitude’,’latitude’)

richardutils.richardutils.ers_dict(strpath, masked=True, chunks=None, dsmatch=None)#

Walks a directory of ers grids and returns a dictionary of rioxarray DataArrays :param strpath: directory name :param chunks: tuple of integers :param dsmatch: data array to match the directory of raster to :param masked: whether to mask by nodata, default is yes, pass masked=False if not desired

Returns:

a dictionary of rioxarrays

Examples

ers_dict(r’D:BananaSplits’) ers_dict(r’D:BananaSplits’, chunk=s(1,1024,1024))

richardutils.richardutils.extract_band(tifpath, findstr)#

Extract a named band from a geotiff via rioxarray

Parameters:

tifpath – Path to raster

Returns:

geotiff band

Examples

darock = extract_band(usepath, ‘ROCK’)

richardutils.richardutils.gdb_dict(gdbpath)#

Returns a dictionary of geodataframes

Parameters:

gdbpath – path to a FileGDB

richardutils.richardutils.gdf_bb(gdf, bb)#

Returns a bounding box filtered gdf

Parameters:

  • gdf – geodataframe

  • bb – bounding box

richardutils.richardutils.gdf_parquet_dict(strpath)#

Walks a directory of parquet geodataframes :param strpath: directory name

Returns:

a dictionary of geodataframes

Examples

gdf_parquet_dict(r’D:BananaSplits’)

richardutils.richardutils.gdf_parquet_list(strpath)#

Walks a directory of parquet geodataframes :param strpath: directory name

Returns:

a list of geodataframes

Examples

gdf_parquet_list(r’D:BananaSplits’)

richardutils.richardutils.gdf_shape_dict(strpath)#

Walks a directory of shapefiles :param strpath: directory name

Returns:

a dictionary of geodataframes

Examples

gdf_shape_dict(r’D:BananaSplits’)

richardutils.richardutils.global_low_res()#
Returns:

built in global low res world polygons for cheap clipping

richardutils.richardutils.location_sample(gdf, da, name_col)#

Returns a dataframe of points sample from a DataArray by location at once

Parameters:

  • gdf – geodataframe of points

  • da – DataArray to sample:

  • name_col – String to identify the location names

Returns:

Onshore location sample dataframe

richardutils.richardutils.makegdf(df, xcol='longitude', ycol='latitude', crs='EPSG:4326')#

Turn a dataframe of a csv of points into a geodataframe

Parameters:

  • df – a dataframe from csv

  • xcol – x coordinate [longitude, easting etc.]

  • ycol – y coordinate

Returns:

gdf geodataframe

Examples

gdf = makegdf(df,’longitude’,’latitude’,’EPSG:4326’)

richardutils.richardutils.mmnorm(da)#

Minmax norm xarray DataArray

Parameters:

da – A DataArray

Returns:

normalised DataArray

Examples

mnorm(geoscience_raster)

richardutils.richardutils.norm_diff_comparison(da1, da2)#

Normalised difference and ratio of two xarray

Parameters:

  • da1 – DataArrays

  • da2 – DataArrays

Returns:

Difference and ratio of reprojected match DataArrays

Examples

norm_diff_comparison(daarea1, daarea2):

richardutils.richardutils.plotgdf(gdf, column, title, alpha=0.5, savefig=True, cmap='cetrainbow', slide_dict=None, size=7, legend=False)#

Plot a gepdataframe with a title. Allow saving to a png Allow adding to a dictionary e.g. for presentation use

Parameters:

  • gdf – A gepdataframe

  • column – string column to plot

  • title – title of plot

  • alpha – transparently

  • savefig – write a png to the directory

  • cmap – a matplotlib colormap

  • slide_dict – dictionary to store reference to plots in

Examples:

richardutils.richardutils.plotgdf_da(gdf, da, column, title, alpha=0.5, savefig=True, cmap='cetrainbow', cmap_da='cetrainbow', slide_dict=None, size=7, legend=False, robust=False)#

Plot a geopdataframe with a title. Allow saving to a png Allow adding to a dictionary e.g. for presentation use

Parameters:

  • gdf – A gepdataframe

  • column – string column to plot

  • title – title of plot

  • alpha – transparently

  • savefig – write a png to the directory

  • cmap – a matplotlib colormap or a string with color_colorwanted e.g. plotgdf(da,cmap=”color_white”) to get a flat color gdf plot

  • slide_dict – dictionary to store reference to plots in

Examples:

richardutils.richardutils.plothist(da, title, color='Orange', savefig=True, slide_dict=None)#
richardutils.richardutils.plothist_combo(da, da2, title, color1='Orange', color2='Gold', savefig=True, slide_dict=None)#

Plot a geodataframe with a title. Allow saving to a png Allow adding to a dictionary e.g. for presentation use

Parameters:

  • da – A DataArray

  • da2 – A DataArray to compare

  • color1 – string color for first histogram

  • color2 – string color for secondt histogram

  • title – title of plot

  • alpha – transparently

  • savefig – write a png to the directory

  • slide_dict – dictionary to store reference to plots in

richardutils.richardutils.plotmap(da, robust=False, cmap='cetrainbow', size=6, title='Title Here', clip=None, savefig=True, slide_dict=None, background=False)#

Plot a dataarray with a title. Allow saving to a png Allow adding to a dictionary e.g. for presentation use

Parameters:

  • da – A DataArray

  • robust – clip to 2/98 or not

  • cmap – a matplotlib colormap

  • size – integer size of plot

  • title – string title of plot

  • clip – quantile number to clip to

  • savefig – save png to directory

  • slide_dict – add png path to a dictionary

  • background – plot a background shape layer

Returns:

The squarest root.

Examples:

richardutils.richardutils.plotmap3(da, robust=False, cmap='cetrainbow', size=6, title='Title Here', clip=None, savefig=True, slide_dict=None, background=False)#

Plot a dataarray with a title. Allow saving to a png Allow adding to a dictionary e.g. for presentation use

Parameters:

  • da – A DataArray with 3 bands

  • robust – clip to 2/98 or not

  • cmap – a matplotlib colormap

  • size – integer size of plot

  • title – string title of plot

  • clip – quantile number to clip to

  • savefig – save png to directory

  • slide_dict – add png path to a dictionary

  • background – plot a background shape layer

Returns:

The squarest root.

Examples:

richardutils.richardutils.plotmap_background(da, robust=False, cmap='cetrainbow', size=6, title='Title Here', clip=None, savefig=True, slide_dict=None, background=False, alpha=0.999)#

Plot a dataarray with a title. Allow saving to a png Allow adding to a dictionary e.g. for presentation use

Parameters:

  • da – A DataArray

  • robust – clip to 2/98 or not

  • cmap – a matplotlib colormap

  • size – integer size of plot

  • title – string title of plot

  • clip – quantile number to clip to

  • savefig – save png to directory

  • slide_dict – add png path to a dictionary

  • background – plot a background shape layer if True is passed based on the DataArray, if a da is passed, use that - assumes data > 0

Returns:

Examples:

richardutils.richardutils.plotmapc(da, robust=False, cmap='cetrainbow', size=6, title='Title Here', clip=None, savefig=True, slide_dict=None, background=False)#

Plots a dataarray and makes the colorbar the same height as the plot

Plot a dataarray with a title. Allow saving to a png Allow adding to a dictionary e.g. for presentation use

Parameters:

  • da – A DataArray

  • robust – clip to 2/98 or not

  • cmap – a matplotlib colormap

  • size – integer size of plot

  • title – string title of plot

  • clip – quantile number to clip to

  • savefig – save png to directory

  • slide_dict – add png path to a dictionary

  • background – plot a background shape layer

Returns:

The squarest root.

Examples: plotmapc(da_exploding_stars, cmap=’magma’, title=’Exploding Stars’)

richardutils.richardutils.plotmapw(da, robust=False, cmap='cetrainbow', size=6, title='Title Here', clip=None, savefig=True, slide_dict=None, vmax=None)#

Plot a dataarray with a title. Remove colorbar in the way Allow saving to a png Allow adding to a dictionary e.g. for presentation use

Parameters:

da – A DataArray

Examples:

richardutils.richardutils.rasterize_one(tilow, strpath, da)#

Rasterize a geodataframe to a default one raster

Parameters:

  • tilow – gdf

  • strpath – output geotif path

  • da – raster for resolution and bounds to match

Returns:

geotiff to file

Examples

rasterize_one(gdf, outpath, darock)

richardutils.richardutils.richardfunction(n: float) → float#

This is not currently used so pointless to look at currently My function makes square roots.

Parameters:

n – A number of some kind.

Returns:

The squarest root.

Examples: >>> richardfunction(9) 3.0 >>> richardfunction(100) 10.0

richardutils.richardutils.shape_dict(shapepath)#

Returns a dictionary of geodataframes

Parameters:

shapepath – path to a directory with shapefiles

richardutils.richardutils.tif_dict(strpath, masked=True, chunks=None, dsmatch=None)#

Walks a directory of geotiffs and returns a dictionary of rioxarray DataArrays :param strpath: directory name :param chunks: tuple of integers :param dsmatch: data array to match the directory of raster to :param masked: whether to mask by nodata, default is yes, pass masked=False if not desired

Returns:

a dictionary of rioxarrays

Examples

tif_dict(r’D:BananaSplits’) tif_dict(r’D:BananaSplits’, chunk=s(1,1024,1024))

richardutils.richardutils.tif_to_ers(strpath, masked=True, chunks=None, dsmatch=None)#

Walks a directory of geotiffs and returns each as an ers grid and writes to fiel :param strpath: directory name :param chunks: tuple of integers :param dsmatch: data array to match the directory of rasters to :param masked: whether to mask by nodata, default is yes, pass masked=False if not desired

Returns:

a dictionary of rioxarrays

Examples

tif_dict(r’D:BananaSplits’) tif_dict(r’D:BananaSplits’, chunk=s(1,1024,1024))

richardutils.richardutils.tif_to_img(strpath, masked=True, chunks=None, dsmatch=None)#

Walks a directory of geotiffs and returns each as an img rasterl :param strpath: directory name :param chunks: tuple of integers :param dsmatch: data array to reproject match the directory of rasters to :param masked: whether to mask by nodata, default is yes, pass masked=False if not desired

Returns:

a dictionary of rioxarrays

Examples

tif_dict(r’D:BananaSplits’) tif_dict(r’D:BananaSplits’, chunk=s(1,1024,1024))

richardutils.richardutils.world_low_res(country)#
Parameters:

country – string of desired country border e.g. Australia

Returns:

Built in global low res world polygons for cheap clipping filtered to one country

richardutils.richardutils.zonal_onshore(country, data)#

Returns geodataframe clipped to a country low res boundary: e.g. for after zonal stats dataframe production

Parameters:

  • country – string of desired country border e.g. Australia

  • data – ataframe with a geometry column

Returns:

onshore lowres clipped geodataframe

richardutils.richardutils.zonal_onshore_globe(data)#

Returns geodataframe clipped to global land: e.g. for after zonal stats dataframe production

Parameters:

data – dataframe with a geometry column

Returns:

Onshore zonal data

richardutils.richardutils.zonal_stats(vector_data, measurements, dalike, variable)#

Get a dataframe of zonal statistics from a DataArray

Parameters:

  • vector_data – a dataframe with a unique id

  • measurements – unique column of interest

  • dalike – DataArray to make grid from

  • variable – Name to give the out grid variable

Returns:

zonal stats dataframe

Examples

gdf = zonal_stats(gdf,’USEID’,da,’LASERBLASTRADIUS’)

Module contents#