Source code for prism.scatter

import cycler

import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np

import prism.util as util

[docs]def scatter_1d(subclone_assignments, num_subclones, depths, fingerprint_fractions, width, height, dpi): """Generate annotated scatterplot for one-dimensional PRISM analysis. :param list subclone_assignments: List containing subclone assignment status for each fingerprint epilocus. :param int num_subclones: Number of subclones. :param list depths: List of depths (pattern counts). :param list fingerprint_fractions: List of fingerprint fractions. :param float width: Figure width. :param float height: Figure height. :param int dpi: Figure DPI. """ fig = plt.figure(figsize=(width, height)) ax = fig.add_subplot(111) ax.grid() ax.set_axisbelow(True) ax.set_xlabel('Fraction of fingerprint') ax.set_ylabel('Depth') for subclone_index in range(num_subclones): mask = (subclone_assignments == subclone_index) ax.scatter( fingerprint_fractions[mask, 0], depths[mask, 0], label=f'S{subclone_index + 1}', s=60, edgecolors='black', linewidth=0.3, )
[docs]def scatter_2d(subclone_assignments, num_subclones, fingerprint_fractions, width, height, dpi): """Generate annotated scatterplot for two-dimensional PRISM analysis. :param list subclone_assignments: List containing subclone assignment status for each fingerprint epilocus. :param int num_subclones: Number of subclones. :param list fingerprint_fractions: List of fingerprint fractions. :param list annotation_names: List of the names of annotations. :param list annotation_mask: List containing annotation status for each fingerprint epilocus. :param float width: Figure width. :param float height: Figure height. :param int dpi: Figure DPI. """ fig = plt.figure(figsize=(width, height)) ax = fig.add_subplot(111) ax.grid() ax.set_axisbelow(True) ax.set_xlabel('FF1') ax.set_ylabel('FF2') for subclone_index in range(num_subclones): mask = (subclone_assignments == subclone_index) ax.scatter( fingerprint_fractions[mask, 0], fingerprint_fractions[mask, 1], label=f'S{subclone_index + 1}', s=60, edgecolors='black', linewidth=0.3, )
[docs]def run(input_fp, output_fp, dpi=400, width=4, height=4, scale=1, font_family=None): util.preset_rc(scale=scale, font_family=font_family) subclone_assignments = [] depths = [] fingerprint_fractions = [] with open(input_fp) as inFile: inFile.readline() for line in inFile.readlines(): header, cluster, subclone, d, c, ffs = util.parse_result_line(line) subclone_assignments.append(subclone) depths.append(d) fingerprint_fractions.append(ffs) subclone_assignments = np.array(subclone_assignments) fingerprint_fractions = np.array(fingerprint_fractions) depths = np.array(depths) num_subclones = len(set(subclone_assignments)) n_dim = len(fingerprint_fractions[0]) if n_dim == 1: scatter_1d(subclone_assignments, num_subclones, depths, fingerprint_fractions, width, height, dpi) elif n_dim == 2: scatter_2d(subclone_assignments, num_subclones, fingerprint_fractions, width, height, dpi) plt.legend() plt.tight_layout() plt.savefig(output_fp, dpi=dpi)