cooperative_channels_in_biological_neurons_via_dynamic_clamp/scripts/plot_firing_rates.py

import matplotlib.pyplot as plt
import numpy
import pandas as pd
from matplotlib.lines import Line2D

from tools.helper import after_pulse_mean_string, pulse_mean_string
from tools.definitions import OUTPUT_FOLDER, HELPER_TABLE_FOLDER, PLOTS_FOLDER, STIMULATION_METADATA_FILTERED


path_to_plot_folder = OUTPUT_FOLDER+PLOTS_FOLDER
path_to_filtered_stimulus_file = OUTPUT_FOLDER+HELPER_TABLE_FOLDER+STIMULATION_METADATA_FILTERED

stimulations = pd.read_csv(path_to_filtered_stimulus_file, index_col="stimulation_id")

type_number_combinations = stimulations[["protocol_type", "pulse_number"]].drop_duplicates().values

print "# Plotting firing rates"

for type_number in type_number_combinations:
    protocol_type = type_number[0]
    number = type_number[1]

    # Determine the protocol
    protocol_id = "{}-{:d}".format(protocol_type, number)
    path_to_firing_rates_file = OUTPUT_FOLDER + HELPER_TABLE_FOLDER + "{}.csv".format(protocol_id)
    isis = pd.read_csv(path_to_firing_rates_file, index_col="stimulation_id")

    fig = plt.figure(figsize=(9, 9))
    ax = fig.add_subplot(111)
    markers = iter(Line2D.filled_markers)

    if protocol_type == "UP":
        firing_info_columns = ["isi_before"] + \
                              [after_pulse_mean_string.format(pulse_idx) for pulse_idx in range(1, number + 1)]
    elif protocol_type == "DOWN":
        firing_info_columns = [pulse_mean_string.format(pulse_idx) for pulse_idx in range(1, number + 1)] + [
            "isi_after"]

    else:
        RuntimeWarning("Unknown protocol {}".format(protocol_type))

    for stim_id, isi in isis.iterrows():
        legend = stim_id
        # noinspection PyTypeChecker
        firing_rates = numpy.nan_to_num(1.0 / isi[firing_info_columns].values.astype(numpy.float))
        color = 'k' if stimulations.loc[stim_id]["was_successful"] else 'r'
        ax.plot(firing_rates, ls='-', marker=markers.next(), markersize=10, color=color, label=stim_id)
    ax.set_xticks(ticks=numpy.arange(0, number + 1))
    ax.legend()

    ax.set_xlabel("Pulse")
    ax.set_ylabel("Firing [Hz]")
    fig.savefig("{}/{}.png".format(path_to_plot_folder, protocol_id))