pytesmo.time_series.filters module

Created on Oct 16, 2013

Fast cython functions for calculating various filters

@author: Christoph Paulik christoph.paulik@geo.tuwien.ac.at

pytesmo.time_series.filters.boxcar_filter(signatures, args, kwargs, defaults)

Calculates filtered time series using a boxcar filter - basically a moving average calculation

Parameters:

• in_data (double numpy.array) – input data

• in_jd (double numpy.array) – julian dates of input data

• window (int) – characteristic time used for calculating the weight

• nan (double) – nan values to exclude from calculation

pytesmo.time_series.filters.exp_filter(signatures, args, kwargs, defaults)

Calculates exponentially smoothed time series using an iterative algorithm

Parameters:

• in_data (double numpy.array) – input data

• in_jd (double numpy.array) – julian dates of input data

• ctime (int) – characteristic time used for calculating the weight

• nan (double) – nan values to exclude from calculation