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a/virheat/command.py b/virheat/command.py index 21257a5..0b3c1f7 100644 --- a/virheat/command.py +++ b/virheat/command.py @@ -221,7 +221,7 @@ def main(sysargs=sys.argv[1:]): plotting.create_heatmap(ax, frequency_array, cmap_cells) mutation_set = plotting.create_genome_vis(ax, genome_y_location, n_mutations, unique_mutations, start, stop) plotting.create_axis(ax, n_mutations, min_y_location, n_samples, file_names, start, stop, genome_y_location, - unique_mutations, reference_name, n_scores) + unique_mutations, reference_name) plotting.create_mutation_legend(mutation_set, min_y_location, n_samples, n_scores) plotting.create_colorbar(args.threshold, cmap_cells, min_y_location, n_samples, ax) # plot gene track diff --git a/virheat/scripts/plotting.py b/virheat/scripts/plotting.py index cacc036..34b1fa9 100644 --- a/virheat/scripts/plotting.py +++ b/virheat/scripts/plotting.py @@ -82,21 +82,39 @@ def create_scores_vis(ax, genome_y_location, n_mutations, n_tracks, unique_mutat score_set.append((int(mutation_attributes[0]), float(mutation_attributes[5]))) # check if there is something to plot if score_set: - # create zero line and score name on the left - plt.axhline(y=y_zero, color='black', linestyle='-', linewidth=0.5) - ax.text(-0.5, y_zero, score_name, ha='right', va='center') # define normalization multiplier for the height of the score v lines - multiplier = max([abs(score[1]) for score in score_set]) / abs((y_zero + genome_y_location / 4) - y_zero) - # create score lines on the score rectangle and the mapping to the respective mutation lines + max_value = max([abs(score[1]) for score in score_set]) # max abs in score set + multiplier = max_value / abs((y_zero + genome_y_location / 4) - y_zero) + # add text for scale and score_name + if score_count % 2 == 0: + score_name_loc, scale_loc, vline_loc = ax.get_xlim()[1] + 0.5, ax.get_xlim()[0] - 0.5, ax.get_xlim()[0] + name_ha_aln, scale_ha_aln = "left", "right" + else: + score_name_loc, scale_loc, vline_loc = ax.get_xlim()[0] - 0.5, ax.get_xlim()[1] + 0.5, ax.get_xlim()[1] + name_ha_aln, scale_ha_aln = "right", "left" + # score name + ax.text(score_name_loc, y_zero, score_name, ha=name_ha_aln, va='center') + # scale + ax.text(scale_loc, y_zero, "0", ha=scale_ha_aln, va='center') + ax.text(scale_loc, y_zero - genome_y_location / 4, -max_value, ha=scale_ha_aln, va='center', color='red') + ax.text(scale_loc, y_zero + genome_y_location / 4, max_value, ha=scale_ha_aln, va='center', color='blue') + plt.vlines(x=vline_loc, ymin=y_zero - genome_y_location / 4, ymax=y_zero + genome_y_location / 4, color='black', linewidth=2) + # add h line boundaries for scale + if score_count is 1: + plt.axhline(y=y_zero + genome_y_location / 4, color='grey', linestyle='--', linewidth=0.5) + plt.axhline(y=y_zero - genome_y_location / 4, color='grey', linestyle='--', linewidth=0.5) + # create zero line + plt.axhline(y=y_zero, color='black', linestyle='-', linewidth=0.5) + # create bars for scores for score in score_set: # define x value mutation_x_location = n_mutations / length * (score[0] - start) - # define y value # create lines for score_set if score[1] < 0: plt.vlines(x=mutation_x_location, ymin=y_zero + score[1]/multiplier, ymax=y_zero, color="red", linestyle='-') else: plt.vlines(x=mutation_x_location, ymin=y_zero, ymax=y_zero + score[1] / multiplier, color="blue", linestyle='-') + return True # if not the track is not created else: @@ -148,7 +166,7 @@ def create_mutation_legend(mutation_set, min_y_location, n_samples, n_scores): plt.legend(bbox_to_anchor=(1.01, 0.95-(n_samples/(min_y_location+n_samples+n_scores))), handles=legend_patches) -def create_axis(ax, n_mutations, min_y_location, n_samples, file_names, start, stop, genome_y_location, unique_mutations, reference_name, n_scoresets=0): +def create_axis(ax, n_mutations, min_y_location, n_samples, file_names, start, stop, genome_y_location, unique_mutations, reference_name): """ create the axis of the plot """