Matplotlib plotter for json files generated by jack

view.py

import matplotlib.pyplot as plt
from numpy import loadtxt
import numpy as np
import pprint
import argparse
import json
from collections import namedtuple

pp = pprint.PrettyPrinter(indent=4)



def get_options():
    parser = argparse.ArgumentParser(description='View Results')

    parser.add_argument('files', type=str, nargs='+',
                        help='files to be viewed in json format')
    parser.add_argument('--output-only', '-x', action='store_true',
                        help='only generate plots, to not open viewer', default=False)
    parser.add_argument('--well', '-w', action='store_true',
                        help='generate well plots', default=False)
    parser.add_argument('--color', '-c', action='store_true',
                        help='generate color plots', default=False)

    return parser.parse_args()


def load_data(path):
    all_samples = None

    with open(path, 'r') as content_file:
        content = content_file.read()
        all_samples = json.loads(content, object_hook=lambda d: namedtuple('sample', d.keys())(*d.values()))

    return all_samples



def plot_all_wells(data, save_name=None):
    all_cycles = list(map(lambda x: x.cycle, data))
    f, ax = build_configure_plot('All Wells All Colors', all_cycles)

    # Extract only color, reduce to distinct set
    colors = set(map(lambda x: x.color, data))
    wells = set(map(lambda x: x.well, data))

    for w in wells:
        for c in colors:
            # get data set for specific well and color
            samples = list(filter(lambda x: x.color == c and x.well == w, data))

            samples = sorted(samples, key=lambda x: x.cycle)

            value = list(map(lambda x: x.value, samples))
            cycle = list(map(lambda x: x.cycle, samples))

            plt.plot(cycle, value)


    if save_name is not None:
        f.saveFigure(save_name)


def plot_well_all_colors(well, data, save_name=None):
    all_cycles = list(map(lambda x: x.cycle, data))

    title = 'Well {0} All Colors'.format(well)
    f, ax = build_configure_plot(title, all_cycles)

    # Extract only color, reduce to distinct set
    colors = set(map(lambda x: x.color, data))

    for c in colors:
        # get data set for specific well and color
        samples = list(filter(lambda x: x.color == c and x.well == well, data))

        samples = sorted(samples, key=lambda x: x.cycle)

        value = list(map(lambda x: x.value, samples))
        cycle = list(map(lambda x: x.cycle, samples))

        plt.plot(cycle, value)


    if save_name is not None:
        f.saveFigure(save_name)


def plot_color_all_wells(color, data, save_name=None):
    all_cycles = list(map(lambda x: x.cycle, data))

    title = 'Color {0} All wells'.format(color.upper())
    f, ax = build_configure_plot(title, all_cycles)

    wells = set(map(lambda x: x.well, data))

    for w in wells:
        # get data set for specific well and color
        samples = list(filter(lambda x: x.color == color and x.well == w, data))

        samples = sorted(samples, key=lambda x: x.cycle)

        value = list(map(lambda x: x.value, samples))
        cycle = list(map(lambda x: x.cycle, samples))

        plt.plot(cycle, value)


    if save_name is not None:
        f.saveFigure(save_name)



def plot_per_color(data, save_name=None):
    for c in set(map(lambda x: x.color, data)):
        plot_color_all_wells(c, data, save_name)


def plot_per_well(data, save_name=None):
    for w in set(map(lambda x: x.well, data)):
        plot_well_all_colors(w, data, save_name)



def build_configure_plot(title, cycles=[]):
    f = plt.figure()
    ax = f.add_subplot(1,1,1)

    f.suptitle(title, fontsize=14, fontweight='bold')
    plt.xlabel('Cycle')
    plt.ylabel('Intensity')
    ax.grid(which='both')
    ax.grid(which='minor', alpha=0.2)
    ax.grid(which='major', alpha=0.5)

    if len(cycles) > 1:
        plt.xticks(np.arange(min(cycles), max(cycles)+1, 5.0))
        ax.set_xticks(np.arange(min(cycles), max(cycles)+1, 1.0), minor=True)

    return f, ax



if __name__ == "__main__":
    options = get_options()

    for file in options.files:
        data = load_data(file)
        plot_all_wells(data)

        if options.well:
            plot_per_well(data)

        if options.color:
            plot_per_color(data)

    if not options.output_only:
        plt.show()