def do_example(datafile, outfile, invert=False, bins=100, ignore=0.0): xyvv = clx.calc_load_xyvv(datafile, invert=invert) (bins, xyvv) = cgsx.calc_grid_sum_xyvs(xyvv) xyz = cxp.calc_xyvv_percentage(xyvv) xyz = cix.calc_ignore_xyz(xyz, ignore=ignore) pgx.plot_gmt_xyz(xyz, outfile, title='%loss sum binned values', np_posn='NE', s_posn='SE', cb_label='% loss')
def obsolete_plot_loss_map(indir, data, out_dir, output_file, save_file=None, title=None, np_posn=None, s_posn=None, cb_label=None, bins=100, scale=1.0, ignore=None, invert=False, colourmap=None): """Plot a loss map from randomly sampled data. indir input directory data name of the data file to plot (in indir) out_dir general output directory output_file name of map output file to create in 'out_dir' directory save_file name of map data output file to create in 'out_dir' directory title title to put on the graph np_posn place to put a north pointer symbol at s_posn place to put a length scale at cb_label label text to put on the colour bar bins either scalar for bins in each direction or (bin_x, bin_y) scale amount to scale the data by ignore the value to ignore if value <= ignore colourmap the base colourmap to use """ # read in and scale XYZ data xyz = csx.calc_sum_xyz(data, scale=scale, bins=bins, invert=invert) # ignore everything less than an 'ignore' value? if ignore is not None: xyz = cix.calc_ignore_xyz(xyz, ignore) # if we want a save of actual plotted data, do it here if save_file: save_outfile = os.path.join(out_dir, save_file) # write 'xyz' data to 'save_outfile' here # generate the plot output required plot_outfile = os.path.join(out_dir, output_file) pgx.plot_gmt_xyz(xyz, plot_outfile, bins=bins, title=title, cb_label=cb_label, np_posn=np_posn, s_posn=s_posn, colourmap=colourmap)