Frequently used functions under geodat.nc
The following functions are shortcuts for applying frequently used functions from the other modules (such as monthly and math) on Variable instances.
Manipulation along time axis
| climatology(var[, appendname, ...]) |
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| anomaly(var[, appendname, clim, ...]) |
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| running_climatology(var, appendname, ...[, ...]) |
Calculate the running climatology, with anomaly |
| clim2long(clim, target) |
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| TimeSlices(var, lower, upper, toggle[, ...]) |
Return a time segment of the variable according to the lower (inclusive) |
| time_input_to_datetime(time, calendar, units) |
Return a datetime.datetime object given time as string |
| time_array_to_dim(time_array, calendar, ...) |
Return a geodat.nc.Dimension object given a time array |
| create_monthly(calendar, units, time0[, ...]) |
Return a generator that return a scalar time value with the specified calendar and unit. |
| create_climatology_dimension(calendar, units) |
Create a monthly dimension for climatology time axis :param calendar: e.g. |
| create_monthly_dimension(calendar, units, ...) |
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| create_monthly_dimension2([ref_dim]) |
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Map regridding
| pyferret_regrid(var[, ref_var, axis, nlon, ...]) |
Use pyferret to perform regridding. |
| regrid(var, nlon, nlat[, verbose]) |
Use spherical harmonic for regridding |
| conform_regrid(*args, **kwargs) |
Given a list of variable |
Mathematical functions
| nc_cal(func) |
A decorator that returns a variable object |
| div(u, v[, varname, long_name]) |
Compute wind divergence by central difference |
| gradient(var, axis[, mask_boundary]) |
Compute the gradient of a variable taking into account the convergence |
| integrate(var, axis[, varname, versatile]) |
Integrate variable along one or more axes |
Statistical analysis and signal processing
| wgt_ave(var[, axis, lat_weighted]) |
A more general routine for averaging |
| wgt_sum(var[, axis]) |
A more general routine for sum |
| gaus_filter(var, gausize) |
Filter a variable spatially (i.e. |
| spatial_corr(var1, var2) |
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| regress(var1, var2) |
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Indexing and Slicing
| concatenate(variables[, axis]) |
Concatenate a list of variables similar to numpy.concatenate |
| ensemble(variables[, new_axis, new_axis_unit]) |
Given a list of variables, perform numpy.concatenate() |
| conform_region(*args) |
Return a dictionary with the common lat-lon region |
File I/O
| getvar(filename, varname, *args, **kwargs) |
Short hand for retrieving variable from a netcdf file |
| savefile(filename, listofvar[, overwrite, ...]) |
filename - a string that specifies the filename, |
Visualisation
| contour(variable, *args, **kwargs) |
Use mpl_toolkits.basemap.Basemap to plot |
| contourf(variable, *args, **kwargs) |
Use mpl_toolkits.basemap.Basemap to plot |
| quiver(variable, *args, **kwargs) |
Use mpl_toolkits.basemap.Basemap to plot |
| plot_vs_axis(var, axis, *args, **kwargs) |
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Working with PyFerret
| var2fer(var[, name]) |
Given a geodat.nc.Variable, return a dictionary |
| fer2var(var) |
Convert the dictionary returned by pyferret.getdata into a |
