mixmasta 0.3.1

A library for common scientific model transforms

mixmasta

A library for common scientific model transforms. This library enables fast and intuitive transforms including:

• Converting a geotiff to a csv
• Converting a NetCDF to a csv
• Geocoding csv data that contains latitude and longitude

Setup

Ensure you have a working installation of GDAL

You also need to ensure that numpy is installed prior to mixmasta installation. This is an artifact of GDAL, which will build incorrectly if numpy is not already configured:

pip install numpy==1.20.1
pip install mixmasta

Note: if you had a prior installation of GDAL you may need to run pip install mixmasta --no-cache-dir in a clean environment.

You must install the GADM2 and GADM3 data with:

mixmasta download

Usage

Examples can be found in the input directory.

Convert a geotiff to a dataframe with:

from mixmasta import mixmasta as mix
df = mix.raster2df('chirps-v2.0.2021.01.3.tif', feature_name='rainfall', band=1)

Note that you should specify the data band of the geotiff to process if it is multi-band. You may also specify the name of the feature column to produce. You may optionally specify a date if the geotiff has an associated date. For example:

Convert a NetCDF to a dataframe with:

from mixmasta import mixmasta as mix
df = mix.netcdf2df('tos_O1_2001-2002.nc')

Geocode a dataframe:

from mixmasta import mixmasta as mix

# First, load in the geotiff as a dataframe
df = mix.raster2df('chirps-v2.0.2021.01.3.tif', feature_name='rainfall', band=1)

# next, we can geocode the dataframe to the admin-level desired (`admin2` or `admin3`)
# by specifying the names of the x and y columns 
# in this case, we will geocode to admin2 where x,y are are 'longitude' and 'latitude', respectively.
df_g = mix.geocode("admin2", df, x='longitude', y='latitude')

Running with CLI

After cloning the repository and changing to the mixmasta directory, you can run mixmasta via the command line.

Set-up:

While you can point mixmasta to any file you would like to transform, the examples below assume your file is in the inputs folder; the transformed .csv file will be written to the outputs folder.

• Transform geotiff to geocoded csv:

mixmasta mix -xform geotiff -input_file chirps-v2.0.2021.01.3.tif -output_file geotiffTEST.csv \
                        -geo admin2 -feature_name rainfall -band=1 -date='5/4/2010' -x longitude -y latitude

• Transform geotiff to csv:

mixmasta mix -xform geotiff -input_file maxhop1.tif -output_file maxhopOUT.csv \
                        -geo admin2 -feature_name probabilty -band=1 -x longitude -y latitude

• Transform netcdf to geocoded csv:

mixmasta mix -xform netcdf -input_file tos_O1_2001-2002.nc -output_file netcdf.csv \
                        -geo admin2 -x lon -y lat

• Transform netcdf to csv:

mixmasta mix -xform netcdf -input_file tos_O1_2001-2002.nc -output_file netcdf.csv

-geocode an existing csv file:

mixmasta mix -xform geocode -input_file no_geo.csv -geo admin3 -output_file geoed_no_geo.csv \
                        -x longitude -y latitude

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

History

0.1.0 (2021-02-24)

• First release on PyPI.