Introduction ************ Pytesmo provides a number of tools that can be used to validate satellite soil moisture (and other climate variables). The pytesmo validation framework combines these tools and also uses functions from some of our other packages. See e.g. the Supported Products. for reader packages that work within pytesmo or the `pygeogrids `__ python package for nearest neighbor searching between datasets, calculation of lookup tables, and reading all grid points of a dataset in the correct order. Features ======== * easily read data from the Supported Products. * anomaly calculation based on climatology or using a moving window see :mod:`pytesmo.time_series.anomaly` * easy temporal matching of time series see :mod:`pytesmo.temporal_matching` * multiple methods for scaling between different observation domains (CDF matching, linear regression, min-max matching) see :mod:`pytesmo.scaling` * calculate standard metrics like correlation coefficients, RMSD, bias, as well as more complex ones like :ref:`triple-collocation-example` or MSE as a decomposition of the RMSD see :mod:`pytesmo.metrics` Notebooks ========= The following documentation is created from ipython notebooks in ``pytesmo/docs/examples``. The notebooks can be run interactively and the results can be reproduced locally using `jupyter `__. Some of the examples require the packages `ascat` and `ismn`, which can be installed with `pip`.