Metadata-Version: 1.0
Name: gcmtools
Version: 0.4.2
Summary: GCM Output Analysis Tools
Home-page: https://github.com/alphaparrot/gcmtools
Author: Adiv Paradise
Author-email: paradise.astro@gmail.com
License: GNU General Public License
Description: ========
        gcmtools
        ========
        
        By Adiv Paradise
        
        DEPENDENCIES:: matplotlib, numpy, basemap, python-netcdf4
        
        Usage
        =====
        
        parse(filename,variable,**kwargs)
        ---------------------------------
         
        Returns the data contained in variable, along with the latitude and longitude arrays.
         
            * filename
                Specifies the name of the netCDF4 file to open
            * variable
                Specifies the variable name to use
            * lat (optional)
                What name to use for the latitude array when parsing the file
            * lon (optional)
                What name to use for the longitude array when parsing the file
            
            
        make2d(variable,**kwargs)
        -------------------------
        
        Returns a 2D slice of the given variable
            
            * variable
                The data array to slice
            * ignoreNaNs (optional)
                Ignore NaNs when doing arithmetic operations (default=True)
            * lat (optional)
                type(int):: slice the array at this latitude
                "sum":: Take the meridional sum
                "mean":: Take the meridional mean
            * lon (optional)
                type(int):: slice the array at this longitude
                "sum" Take the zonal sum
                "mean":: Take the zonal mean
            * lev (optional)
                type(int):: slice the array at this vertical level
                "sum" Take the column sum
                "mean":: Take the column mean
            * time (optional)
                type(int):: Take the snapshot of the array at this time
                None (default):: Take the time-average of the data
                    
        
        spatialmath(variable,**kwargs)
        ------------------------------
            
        Returns the area-weighted average or sum of the given variable
            
            * variable
                Either the name of the variable to use, or the data array itself.
                If the file keyword is used, this should be the variable name. If
                not, then the lat and lon arrays must be provided.
            * file (optional)
                The name of the file from which to extract the data
            * lat (optional)
                The latitude array to use (ignored if file keyword is used)
            * lon (optional)
                The longitude array to use (ignored if file keyword is used)
            * lev (optional)
                The level slice to use (see make2d() keyword options)
            * time (optional)
                type(int):: Use the snapshot of the variable at this time
                None (default):: Use the time-average of the variable
            * mean (optional)
                If True (default), the global mean will be calculated. If False,
                only the global sum will be returned.
            * radius (optional)
                The physical radius of the sphere with which to scale the sum 
                (if not computing the mean)
        
                    
        wrap2d(variable)
        ----------------
        
        Add a longitude column to a 2D lat-lon array, and fill it with the first column
            
        
        pcolormesh(variable,**kwargs)
        -----------------------------
            
        Create and return a pcolormesh object showing variable. **kwargs can include all
        normal pcolormesh keyword arguments, and if the 'projection' keyword argument is
        specified, **kwargs can also contain any Basemap arguments.
            
        gcmtools-specific arguments::
            
            * invertx
                Invert the x-axis. This is analogous to plt.gca().invert_xaxis()
            * inverty
                Invert the y-axis. This is analogous to plt.gca().invert_yaxis()
            * symmetric
                If True, compute a colormap normalization which is symmetric about zero.
                If not None and equal to a number, compute a colormap normalization 
                symmetric about that number. Useful for divergent colormaps.
            
        Example::
            ``pcolormesh(temperature,lon=lons,lat=lats,projection='moll',lon_0=0,cmap='RdBu_r',symmetric=273.15)``
Platform: UNKNOWN
