cso_plot module

Plotting tools.

Class hierchy

  • Figure

    • MapFigure

    • ColorbarFigure

      • ColorbarMapFigure

Classes and methods

class cso_plot.Figure(figsize=None)

Bases: object

Base class for figures.

Close()

Destroy figure.

Export(filename)

Export figure.

AddAxes(position=(0.02, 0.02, 0.96, 0.96))

Add ax to figure.

Optional arguments:

  • position=(left,bottom,width,height) : Relative position of lower left corner and size; defaults values ensure maximum axis.

Set_Domain(domain=None)

Set axis domain.

Optional arguments:

  • domain=(xmin,xmax,ymin,ymax) ;if undefined, no limits are set.

Rectangle(rect, **kwargs)

Draw rectangle with corners specified by:

rect=(west,east,south,north)

Optional keyword arguments are passed to matplotlib.pyplot.plot() method.

StackFill(x, yy, labels=None)

Add filled hatches to ax.

Arguments:

  • x : N array

  • yy : NxM array

OneToOne(*args, **kwargs)

Add 1-1 line, set ax lims to be square.

Arguments are passed to plot() method that adds the line to the axis.

cso_plot.Setup_BaseMap(ax, title=None, domain=None, raster=None, coastlines=True, countries=False, rivers=False, **kwargs)

Setup geographical basemap in the map attrbiute of the class. If no domain was specified, a global map is setup.

Arguments:

  • ax : figure axes to hold the map

Optional arguments:

  • title : title above map

  • domain : (west,east,south,north), default globe

  • raster : (meridian_distance,parallel_distance)

  • coastlines : default True

  • countries : True or False

  • rivers : True or False

Other kewyord arguments are passed directly to Basemap, e.g.:

  • projection : ‘cyl’=cylindrical,

  • resolution : ‘c’ crude, ‘l’ low, ‘i’ intermediate, ‘h’ high

If no projection is defined, a default cylindrical map is setup.

Return basemap object.

class cso_plot.MapFigure(figsize=None, position=None, bmp={})

Bases: cso_plot.Figure

Base class for figure with map.

Optional arguments passed to ‘Figure’ initialization:

  • figsize

Optional arguments to setup data axes:

  • position=(left,bottom,width,height) : position of axes; defaults are guessed

  • bmp : define geograpical map, passed to Setup_BaseMap() method

Plot(lons, lats, *args, **kwargs)

Plot using projections.

class cso_plot.ColorbarFigure(figsize=None, position=None, domain=None, title=None, facecolor=None, cmap={}, cbar={})

Bases: cso_plot.Figure

Base class for figure with colorbar.

Optional arguments passed to Figure class initialization:

  • figsize

Optional arguments to setup data axes:

  • position=(left,bottom,width,height) : position of axes; defaults is guesed

  • domain=(xmin,xmax,ymin,ymax) : axes limits passed to ‘Figure.Set_Domain’

  • title : axes title

Optional arguments that define colorbar:

Set_ColorMap(colors=None, color_under=None, color_over=None, color_bad=None, ncolor=None)

Define color map with ncolor` values. The rgb values in the colormap are interpolated between the specified colors. The ‘under’ and ‘over’ colors for lower and higher values, and ‘bad’ for masked data. The colormap is stored as the ‘cmap’ field.

Optional arguments:

  • colors : either:

    • list with color description: ['white','yellow','red']

    • locally impelemented definitions:

      • ‘wbrb’ (white-blue-red-brown)

      • ‘brb’ (blue-red-brown)

      • ‘bwr’ (blue-white-red)

      • ‘pwb’ (purple-white-brown)

    • predefined colormaps : ‘jet’, …

  • color_under : color descriptions for underflow

  • color_over : color descriptions for overflow

  • color_bad : color for masked values in numpy.ma (masked array)

  • ncolor : (int) number of slots in color table

Attributes set by this routine:

  • cmap : colormap instance

See also:

  • matplotlib.pyplot.colorbar

Set_ColorNorm(values, vmin=None, vmax=None, vbounds=None)

Setup a color normalization to map data values to an index in [0,1] . If an array ‘vbounds’ is specified, it should contain an increasing range of values that define the boundaries of interfals which have the same number of slots in the color map. Otherwise, the values are mapped linear from values in the interval ‘[vmin,vmax]’ to the slots in the color map.linear to [0,1] ; if these are not provided, the range will be the min/max of the suplied values.

This routine sets the attributes: cnorm, vmin, vmax

Arguments:

  • values : data to be displayed; use for min/max

Optional keywords:

  • vmin, vmax : data range

See also:

  • :py:class.`matplotlib.colors.normalize

Set_ColorBar(ticks=None, ntick=None, label=None, tickprops=None, **kwargs)

Set colorbar properties.

Keyword arguments:

  • ticks : tick locations (explicitly set)

  • ntick : number of tickmarks (distributed within vrange)

  • label : text below colorbar

  • tickprops : properties for ticklabels, e.g. fontsize=20 etc ; see matplotlib.text.Text class for all supported properties

Keyword arguments passed directly to matplotlib.pyplot.colorbar class, for example:

  • orientation : default 'horizontal', also 'vertical' possible

  • extend : add left or right arrows: 'neither' | 'both' | 'min' | 'max'

  • drawedges : lines between colors in colorbar ? True or False

  • format : used for labels, e.g. '%g' for general number or '%3.1f'

Add_ColorBar(p)

Fill the colorbar for the mappable p.

Uses settings stored by Set_ColorBar() method.

Arguments:

  • p : mappable object, output of pcolor(), scatter(), …

PColor(xx, yy, cc, vmin=None, vmax=None, vbounds=None, **kwargs)

Add pseudo color plot. If no grid keywords are provided, the domain specified in the initilization might be used; if no domain was provided, the axes are simply the dimension indices.

Arguments:

  • xx, yy : 2D corner fields, shapes (ny+1,nx+1)

  • cc : data values, shape (ny,nx)

Optional color mapping:

  • vmin,``vmax`` : data range for coloring, min and max values by default, or the settings for Scatter if that was called before

  • vbounds : instead of linear mapping of values to color map, specify with this variable a list of boundary values, each interval will take the same number of slots in the color map; typically use this with explicit definition of the ticks in the colorbar:

    cbar=dict(ticks=vbounds)

Other keywords are passed directly to matplotlib.pyplot.pcolormesh class.

Return value: matplotlib.pyplot.pcolormesh object

PColorRGG(rgg, values, vmin=None, vmax=None, vbounds=None, **kwargs)

Add pseudocolor fieds for values defined on reduced gaussian grid.

Arguments:

  • rgg : grid_rgg.ReducedGrid object

  • values : 1D list with values, length is rgg.npoint

Optional color mapping (see PColor):

  • vmin,``vmax``

  • vbounds

Other keywords are passed directly to matplotlib.pyplot.pcolormesh class

Scatter(xx, yy, vmin=None, vmax=None, vbounds=None, **kwargs)

Plot cloud of scattered symbols.

Arguments:

  • xx, yy : location lists

  • vmin,``vmax`` : data range for coloring, min and max values by default, or the settings for PColor if that was called before

  • vbounds : value boundaries (alternative for vmin,vmax)

Optional keywords passed to ‘pyplot.scatter’, for example:

  • c : (list of) data value(s), mapped to colors

  • s : (list of) symbol size(s)

  • marker : marker symbol

  • linewidths : edge widths

Polygons(xx, yy, values, vmin=None, vmax=None, vbounds=None, **kwargs)

Add colored polygons.

Arguments:

  • xx, yy : location arrays (npoly,ncorner)

  • values : data values (npoly) mapped to colors

Optional arguments:

  • vmin,``vmax``data range for coloring, min and max values by default,

    or the settings for PColor if that was called before

  • vbounds : value boundaries (alternative for vmin,vmax)

Density(x, y, bins=10, normed=False, **kwargs)

Add density plot (2D histogram).

Arguments are passed to matplotlib.pyplot.hist2d() method :

  • x, y : values

  • bins : number, array, or list of 2 arrays

PlotAxes(oneone=False)

Add x and y axes lines if necessary. Add 1-1 line if flag is set.

class cso_plot.ColorbarMapFigure(figsize=None, position=None, bmp={}, cmap={}, cbar={})

Bases: cso_plot.ColorbarFigure

Base class for figure with colorbar.

Optional arguments passed to ‘Figure’ initialization:

  • figsize

Optional arguments to setup data axes:

  • position=(left,bottom,width,height) : position of axes; defaults is guesed

  • bmp : define geograpical map, passed to ‘Setup_BaseMap’

Optional arguments that define colorbar:

  • cmap : defines colormap, passed to ‘Set_ColorMap’

  • cbar : defines colorbar, passed to ‘Set_ColorBar’ (False to skip)

PColor(xx, yy, cc, vmin=None, vmax=None, vbounds=None, **kwargs)

Plot pcolormesh on map.

Returns pcolormesh object.

Text(x, y, s, **kwargs)

Addd text to map.

cso_plot.GetColorMap(colors=None, color_under=None, color_over=None, color_bad=None, ncolor=256)

Define color map with N values. The rgb values in the colormap are interpolated between the specified colors. The ‘under’ and ‘over’ colors for lower and higher values, and ‘bad’ for masked data. The colormap is stored as the ‘cmap’ field.

Arguments:

  • colors : either:

    • list with color description: [‘white’,’yellow’,’red’]

    • ‘wbrb’ (white-blue-red-brown)

    • ‘brb’ (blue-red-brown)

    • ‘bwr’ (blue-white-red)

  • color_under : color descriptions for underflow

  • color_over : color descriptions for overflow

  • color_bad : color for masked values in numpy.ma (masked array)

  • ncolor : (int) number of slots in color table

Return values:

  • cmap : colormap instance

cso_plot.mid2bounds(x)

Return 1D arrays with boundary values.

cso_plot.mid2corners(xx)

Return 2D fields with corner values.

cso_plot.GetGrid(shp, xx=None, yy=None, x=None, y=None, xm=None, ym=None, xxm=None, yym=None, domain=None)

Return 2D grid arrays with corner points.

Arguments:

  • shp : shape (ny,nx) of values

Optional grid definitions:

  • xx, yy : 2D corner fields, shapes (ny+1,nx+1) ; if defined, these are the results

  • xxm, yym : 2D mid of cell fields, shapes (nx,ny) ;

  • x, y : 1D corner points, shapes (nx+1) and (ny+1); used to define 2D corner fields

  • xm, ym : 1D mid of cell, shapes (nx) and (ny); used to define 2D corners

If none of these pairs is defined, a regular grid within the domain is assumed; if the domain is not specified, the default in (0,nx,0,ny).

cso_plot.QuickPat(cc, xx=None, yy=None, x=None, y=None, xm=None, ym=None, xxm=None, yym=None, domain=None, vmin=None, vmax=None, vbounds=None, **kwargs)

Plot 2D data as colored pattern.

Arguments passed to GetGrid() method :

  • xm, ym : 1D mid of cell, shapes (nx) and (ny); used to define 2D corners

  • x, y : 1D corner points, shapes (nx+1) and (ny+1); used to define 2D corner fields

  • xxm, yym : 2D mid of cell, shapes (ny,nx)

  • xx, yy : 2D corner fields, shapes (ny+1,nx+1)

Arguments passed to ColorbarFigure.PColor():

  • cc : data values, shape (ny,nx)

  • vmin,``vmax`` : data range for coloring

Other arguments are passed to ColorbarFigure :

  • figsize   = (width,height)

  • domain    = (left,right,bottom,top)

  • facecolor = '0.5' : initial background color for ax

  • cmap      = dict( 'colors'=['blue','white','red'], ncolor=9 )

  • cbar      = dict( 'ntick'=9, extend='both', label='entity [units]' ), or False to skip colorbar

Return value:

  • fig : Figure instance

cso_plot.QuickDens(x, y, bins=10, normed=False, **kwargs)

Density plot.

Arguments passed to matplotlib.pyplot.hist2d() :

  • x, y = values

  • bins = number, array, or 2-element list of arrays

  • normed = frequency instead of numbers

Other arguments are passed to ‘ColorbarFigure’ :

  • figsize = (width,height)

  • cmap    = dict( 'colors'=['blue','white','red'], ncolor=9 )

  • cbar    = dict( 'ntick'=9, extend='both', label='entity [units]' )

Return value:

  • fig : Figure instance

cso_plot.QuickMap(cc, xx=None, yy=None, x=None, y=None, xm=None, ym=None, xxm=None, yym=None, domain=None, vmin=None, vmax=None, vbounds=None, bmp={}, cbar={}, **kwargs)

Plot 2D data as colored pattern on map.

Arguments passed to GetGrid() :

  • xm, ym : 1D mid of cell, shapes (nx) and (ny); used to define 2D corners

  • x, y : 1D corner points, shapes (nx+1) and (ny+1); used to define 2D corner fields

  • xxm, yym : 2D mid of cell, shapes (ny,nx)

  • xx, yy : 2D corner fields, shapes (ny+1,nx+1)

Also a domain=(left,right,bottom,top) might be used to setup the map; could be part of the optional bmp argument.

Arguments passed to ColorbarFigure.PColor() method:

  • cc : data values, shape (ny,nx)

  • vmin,``vmax`` : data range for coloring

  • vbounds : value bounds for colorbar (defines interval with same color)

Other arguments are passed to ‘ColorbarMapFigure’ :

  • figsize = (width,height)

  • bmp     = dict( resolution='c', countries=True, domain=(west,east,south,north), raster=[30.0,30.0], title='displayed on top' )

  • cmap    = dict( 'colors'=['blue','white','red'], ncolor=9 )

  • cbar    = dict( 'ntick'=9, extend='both', label='entity [units]' ), or False to skip colorbar

Return value:

  • fig : Figure instance