Climat module

These functions compute averages, standard deviations, counds, and trends over the time axis in various ways.

Mean

NaN-aware Mean

Std. Deviation

Nan-Aware Std. Dev.

Count

dailymean()

dailynanmean()

dailystdev()

dailynanstdev()

dailycount()

monthlymean()

monthlynanmean()

monthlystdev()

monthlynanstdev()

monthlycount()

seasonalmean()

seasonalnanmean()

seasonalstdev()

seasonalnanstdev()

seasonalcount()

yearlymean()

yearlynanmean()

yearlystdev()

yearlynanstdev()

yearlycount()

diurnalmean()

diurnalnanmean()

diurnalstdev()

diurnalnanstdev()

diurnalcount()

climatology()

nanclimatology()

climstdev()

climnanstdev()

climcount()
pygeode.climatology(var)[source]

Computes a climatological mean. Averages over all years, returning a single value for each distinct month, day, hour, etc.

pygeode.dailymean(var)[source]

Computes an average value for each day.

pygeode.monthlymean(var)[source]

Averages over each month.

pygeode.seasonalmean(var)[source]

Averages over each season. Currently, the seasons are hard-coded as (DJF, MAM, JJA, SON).

pygeode.yearlymean(var)[source]

Averages over each year.

pygeode.diurnalmean(var)[source]

Computes an average value for each time of day (averages over all years, months, days).

pygeode.nanclimatology(var)[source]

Computes a climatological nan-aware mean. Averages over all years, returning a single value for each distinct month, day, hour, etc.

pygeode.dailynanmean(var)[source]

Computes a nan-aware average value for each day.

pygeode.monthlynanmean(var)[source]

Nan-aware Averages over each month.

pygeode.seasonalnanmean(var)[source]

Nan-aware averages over each season. Currently, the seasons are hard-coded as (DJF, MAM, JJA, SON).

pygeode.yearlynanmean(var)[source]

Nan-aware Averages over each year.

pygeode.diurnalnanmean(var)[source]

Computes a nan-aware average value for each time of day (averages over all years, months, days).

pygeode.climstdev(var)[source]

Computes a climatological standard deviation. Computes standard deviation over all years, returning a single value for each distinct month, day, hour, etc.

pygeode.dailystdev(var)[source]

Computes daily standard deviation.

pygeode.monthlystdev(var)[source]

Computes monthly standard deviation.

pygeode.seasonalstdev(var)[source]

Computes seasonal standard deviation.

pygeode.yearlystdev(var)[source]

Computes yearly standard deviation.

pygeode.diurnalstdev(var)[source]

Computes diurnal standard deviation.

pygeode.climnanstdev(var)[source]

Computes nan-aware climatological standard deviation.

pygeode.dailynanstdev(var)[source]

Computes nan-aware daily standard deviation.

pygeode.monthlynanstdev(var)[source]

Computes nan-aware monthly standard deviation.

pygeode.seasonalnanstdev(var)[source]

Computes nan-aware seasonal standard deviation.

pygeode.yearlynanstdev(var)[source]

Computes nan-aware yearly standard deviation.

pygeode.diurnalnanstdev(var)[source]

Computes nan-aware diurnal standard deviation.

pygeode.climcount(var)[source]

Counts number of non-nan data points contributing to climatology.

pygeode.dailycount(var)[source]

Counts number of non-nan data points contributing to daily mean.

pygeode.monthlycount(var)[source]

Counts number of non-nan data points contributing to monthly mean.

pygeode.seasonalcount(var)[source]

Counts number of non-nan data points contributing to seasonal mean.

pygeode.yearlycount(var)[source]

Counts number of non-nan data points contributing to yearly mean.

pygeode.diurnalcount(var)[source]

Counts number of non-nan data points contributing to diurnal mean.

pygeode.climtrend(var)[source]

For each month, day, hour, etc., compute a least-squares fit to a linear trend over all years. This is similar to the climatology, but instead of averaging over all years, it computes the rate of change over all years.

pygeode.from_trend(taxis, coef=None, A=None, B=None)[source]

Reconstructs linear timeseries from a given trend.

pygeode.climat.detrend(var, taxis=<class 'pygeode.timeaxis.Time'>, return_clim=False)[source]