envtoolkit.ts

Functions/classes relative to time-series

Functions

autolag1(TS1)
compute_daily_anom(data, date, clim)	Computes daily anomalies relative to a daily climatology.
compute_daily_clim(data, date[, smooth, nharm])	Computes a daily seasonal cycle from a daily dataset.
compute_monthly_anom(data, yyyymm, clim)	Computes anomalies relative to a monthly climatology.
compute_monthly_clim(data, yyyymm)	Compute a monthly seasonal cycle from a monthly dataset.
corr_ND(xdata, ydata[, use_covariance])	Computes the correlation/covariance between the xdata and ydata arrays at 0-lag.
corr_sig(ts1, ts2, df, coeff[, use_bretherton])
day_of_year(yymmdd)	Returns the day of year of
doy_to_date(year, doy)	Converts from day of year into date
make_monthly_means(data, yymmdd)	Computes monthy means from daily values
make_yymm(date)	Converts a list/array of date objects into YYYYMM integers.
make_yymmdd(date)	Converts a list/array of dates into YYYYMMDD integers.
remove_mean(xdata)	Remove the mean from the dataset.
smooth_data_fft(data, nharm)	Smooth an input data array by using a FFT filter.
standardize(xdata[, ddof])	Standardizes the xdata array
xcorr_1d(xdata, ydata[, maxlag, …])	Computes the cross-correlation/cross-covariance two one-dimensional arrays.
xcorr_ND(xdata, ydata[, maxlag, use_covariance])	Computes the cross-correlation/cross-covariance between the xdata and ydata arrays.

Classes

Lanczos(filt_type, nwts, pca[, pcb, …])

Class for Lanczos filtering.