ClawPlotItem

For usage see Using setplot.py to specify the desired plots and Plotting examples.

Objects of this class are usually created by the new_plotitem method of a ClawPlotAxes object.

The examples shown below are fragments of a typical setplot function which assume plotaxes is an instance of ClawPlotAxes.

See also

Using setplot.py to specify the desired plots and Plotting examples

See also

Plotting examples

class ClawPlotItem

Attributes

The following attributes can be set by the user:

plot_type : str

Type of plot desired, one of the following:

• ‘1d_plot’ : one dimensional line or set of points plotted using the matplotlib plot command.

• ‘1d_from_2d_data’ : 1d plot generated from 2d data, for example as a slice of the data or a scatter plot of data that should be radially symmetric,

• ‘1d_fill_between’ : 1d filled plot between two variable specified by the attributes plot_var and fill_var2.

• ‘2d_contour’ : two dimensional contour plot,

• ‘2d_pcolor’ : two dimensional pcolor plot,

• ‘2d_schlieren’ : two dimensional Schlieren plot,

• ‘2d_patch’ : two dimensional plot of only the cell and/or patch edges, no data

outdir : str or None

Directory to find data to be plotted. If None, then data comes from the outdir attribute of the parent ClawPlotData item.

plot_var : int or function

If an integer, then this specifies which component of q to plot (with the Python convention that plot_var=0 corresponds to the first component).

If a function, then this function is applied to q on each patch to compute the variable var that is plotted. The signature is

• var = plot_var(current_data)

The current_data object holds data from the current frame that can be used to compute the variable to be plotted.

afteritem : str or function or None

A string or function that is to be executed after plotting this item. If a string, this string is executed using exec. If a function, it should be defined to have a single argument current_data.

For example:

def afteritem(current_data):

afterpatch : str or function or None

A string or function that is to be executed after plotting this item on each patch. (There may be more than 1 patch in an AMR calculation.) If a string, this string is executed using exec. If a function, it should be defined to have a single argument “data”, [documentation to appear!]

For example:

def afterpatch(current_data):
    cd = current_data
    print "On patch number %s, xlower = %s, ylower = %s" \
          % (cd.patchno, cd.xlower, cd.ylower)

would print out the patch number and lower left corner for each patch in a 2d computation after the patch is plotted.

MappedGrid : bool

If True, the mapping specified by the mapc2p attribute of the underlying ClawPlotData object should be applied to the patch before plotting.

show : bool

If False, plotting of this object is suppressed.

The other attributes required depend on the plot_type, as summarized below:

Special attributes for all 1d plots, plot_type = ‘1d…’

plotstyle : str

Anything that is valid as a fmt group in the matplotlib plot command. For example:

• ‘-’ for a solid line, ‘- -’ for a dashed line,

• ‘o’ for circles, ‘x’ for x’s, ‘-o’ for circles and a line,

• ‘bo’ for blue circles (though if the color attribute is also set that will overrule the color in the format string).

color : str

Any matplotlib color, for example red can be specified as ‘r’ or ‘red’ or ‘[1,0,0]’ or ‘#ff0000’.

Special attributes for plot_type = ‘1d_plot’

No extra attributes.

Special attributes for plot_type = ‘1d_fill_between’

This gives a filled polygon between two curves using the matplotlib fill_between command.

plot_var : int or function

as described above defines one curve,

plot_var2 : int or function

defines the second curve for the fill_between command. Default is the zero function.

fill_where : str or None

defines the where attribute of the fill_between command.

Example:

plotitem = plotaxes.new_plotitem(plot_type='1d_fill_between')
plotitem.plot_var = 0    # means use q[:,0]

would produce a filled curve between y=q[:,0] and y=0.

Example:

plotitem = plotaxes.new_plotitem(plot_type='1d_fill_between')
plotitem.plot_var = 0    # means use q[:,0]
plotitem.plot_var2 = 1

would produce a filled curve between y=q[:,0] and y=q[:,1].

Special attributes for plot_type = ‘1d_from_2d_data’

map_2d_to_1d : function

Example: In a 2d computation where the solution q[:,:,0] should be radially symmetric about (x,y)=(0,0), the following will result in a scatter plot of the cell values q[i,j,0] vs. the radius r(i,j):

def q0_vs_radius(current_data):
    # convert 2d (x,y,q) into (r,q) for scatter plot
    from numpy import sqrt
    x = current_data.x
    y = current_data.y
    r = sqrt(x**2 + y**2)
    q0 = current_data.var   # the variable specified by plot_var
    # q0 = current_data.q[:,:,0]   # would also work
    return r,q0

plotitem = plotaxes.new_plotitem(plot_type='1d_from_2d_data')
plotitem.plot_var = 0     # use q[:,:,0]
plotitem.plotstyle = 'o'  # symbol not line is best for scatter plot
plotitem.map_2d_to_1d = q0_vs_radius   # the function defined above

See current_data for a description of the current_data argument.

Special attributes for all 2d plots, plot_type = ‘2d…’

celledges_show : bool

If True, draw the cell edges on the plot. The attribute ‘amr_celledges_show’ should be used for AMR computations to specify that cell edges should be shown on some levels and not others. See AMR Attributes.

patchedges_show : bool

If True, draw the edges of patches, mostly useful in AMR computations.

Special attributes for plot_type = ‘2d_contour’

contour_levels : numpy array or None

If a numpy array, the contour levels. If None, then the next three attributes are used to set the levels.

contour_nlevels : int

Number of contour levels

contour_min : float

Minimum contour level

contour_max : float

Maximum contour level

contour_colors : color specification

Colors of contour lines. Can be a single color such as ‘b’ or ‘#0000ff’, or a colormap.

amr_contour_colors : list of color specifications

As with other attributes (see AMR Attributes below), instead of contour_colors you can specify amr_contour_colors to be a list of colors (or colormaps) to use on each AMR level, e.g.:

amr_contour_colors = ['k','b','r']

to use black lines on Level 1, blue on Level 2, and red for all subsequent levels. This is useful since with the matplotlib contour plotter you will see both fine and coarse cell edges on top of one another in refined regions (Matplotlib lacks the required hidden line removal to blank out the lines from coarser patches easily. See also the next attributes.)

contour_show : boolean

Show the contour lines only if this attribute is true. This is most commonly used in the form of the next attribute,

amr_contour_show : list or tuple of booleans

Determines whether to show the contour lines on each AMR level. Useful if you only want to view the lines on the finest patches.

contour_kwargs : dictionary

Other keyword arguments for the contour command.

Special attributes for plot_type = ‘2d_pcolor’

pcolor_cmap : matplotlib colormap

pcolor_cmin : float

pcolor_cmax : float

In general you should specify pcolor_cmin and pcolor_cmax to specify the range of q values over which the colormap applies. If they are not specified they will be chosen automatically and may vary from frame to frame. Also, if AMR is used, they may vary from patch to patch, yielding very confusing plots.

add_colorbar : bool

If True, a colorbar is added to the plot.

Special attributes for plot_type = ‘2d_imshow’

imshow_cmap : matplotlib colormap

imshow_cmin : float

imshow_cmax : float

In general you should specify imshow_cmin and imshow_cmax to specify the range of q values over which the colormap applies. If they are not specified they will be chosen automatically and may vary from frame to frame. Also, if AMR is used, they may vary from patch to patch, yielding very confusing plots.

add_colorbar : bool

If True, a colorbar is added to the plot.

AMR Attributes

Many attributes listed above also have a second related attribute with the same name pre-pended with amr_. If this attribute is set, it should be a list whose elements are of the type specified by the original name, and the elements of the list will be used for different AMR refinement levels.

For example, the following commands:

plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.contour_color = 'r'

will result in all contour lines being red on all levels of AMR. On the other hand:

plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.amr_contour_color = ['k', 'b']

will result in contour lines on patches at level 1 being black and on patches of level 2 or higher being blue.

Note that if the list is shorter than the number of levels, the last element is used repeatedly.

If both attributes contour_color and amr_contour_color are set, only amr_contour_color is used.

A common use is to show cell edges only on coarse levels, not on finer levels, e.g.:

plotitem.amr_celledges_show = [1,1,0]

will result in celledges being shown only on levels 1 and 2, not on finer levels.

Colorbar attributes

If add_colorbar == True, then the following attributes are also used (see the matplotlib colorbar documentation for descriptions and note that other kwargs can also be specified in a dictionary):

colorbar_shrink : float

colorbar_label : str

colorbar_ticks : str

colorbar_tick_labels : str

colorbar_extend : str

colorbar_kwargs : dictionary

Other kwargs to be passed to colorbar.

Methods

getframe(frameno)

Returns an object of class pyclaw.solution.Solution containing the solution being plotted by this object for frame number frameno.

gethandle()

Returns the handle for this item.