runplot_figure_7_a.ipy

import numpy as np
import matplotlib.pyplot as plt

from pskf.tools.plot import specs as sc
from pskf.tools.plot import plotarrays as pa
import pskf.scripts.gaussianity.arrays as ga
import pskf.scripts.gaussianity.plot as gp
import pskf.scripts.gaussianity.read as gr
import pskf.tools.run.pythonmodule as pm

# Switches
is_read = 0
is_backup = 0
is_hist = 1
is_save = 0
is_show = 1

model_name = 'wavereal'
which_methods = [
    4, 4, 4, 4, 4, 4,
    6, 6, 6, 6, 6, 6,
    1, 1, 1, 1, 1, 1,
    2, 2, 2, 2, 2, 2,
    5, 5, 5, 5, 5, 5,
    0, 0, 0, 0, 0, 0,
    3, 3, 3, 3, 3, 3,
]
n_syns = [
    1, 10, 100, 1, 10, 100,
    1, 10, 100, 1, 10, 100,
    1, 10, 100, 1, 10, 100,
    1, 10, 100, 1, 10, 100,
    1, 10, 100, 1, 10, 100,
    1, 10, 100, 1, 10, 100,
    1, 10, 100, 1, 10, 100,
]
ensemble_sizes = [
    50, 50, 50, 250, 250, 250,
    50, 50, 50, 250, 250, 250,
    50, 50, 50, 250, 250, 250,
    50, 50, 50, 250, 250, 250,
    50, 50, 50, 250, 250, 250,
    50, 50, 50, 250, 250, 250,
    50, 50, 50, 250, 250, 250,
]
n_comparisons = 1000

nplots = len(which_methods)

# Read
if is_read:
    for i in range(nplots):
        gauss_array, gauss_array_name = gr.read(
            model_name=model_name,
            which_method=which_methods[i],
            ensemble_size=ensemble_sizes[i],
            n_syn=n_syns[i],
            n_comparisons=n_comparisons,
        )

        np.save(gauss_array_name, gauss_array)
        print('Saved as ' + gauss_array_name)


# Histogram
if is_hist:

    # Figure
    fig = plt.figure('Gaussianity', figsize=[30, 15])
    fig.suptitle("Tracer", fontsize=30,
                 bbox={'facecolor': (0.8, 0.8, 0.8), 'alpha': 1.0, 'pad': 10})

    # Run plot function
    for i in range(nplots):
        ax, pic_name = gp.hist(
            fig.add_subplot(7,
                            6,
                            i+1),
            model_name=model_name,
            which_method=which_methods[i],
            ensemble_size=ensemble_sizes[i],
            n_syn=n_syns[i],
            n_comparisons=n_comparisons,
            title=(r"$n_{e}$: "+str(ensemble_sizes[i])
                   + r", $n_{syn}$: "+str(n_syns[i]) if i in [0, 3] else
                   (r"$n_{syn}$: "+str(n_syns[i]) if i in [1, 2, 4, 5] else
                    "")),
            xlabel=(None if i not in [nplots-2, nplots-5] else
                    r'RMSE  $\log(K[m^2])$'),
            ylabel=(pa.names_methods[which_methods[i]] if not np.mod(i, 6) else
                    None),
            is_xticks=(False if i < nplots - 6 else True),
            is_yticks=(True if not np.mod(i, 6) else False),
            itickhide=2,
            xlims=[0.2, 0.6],
            fontaxl=20,
            fonttit=30,
            fonttic=15,
        )
    # Save
    if is_save:
        plt.savefig(pic_name)
        print('Saved as ' + pic_name)

    # Show
    if is_show:
        plt.show()
    else:
        plt.clf()

# Backup
if is_backup:
    pm.py_backup(
        pm.python_scripts_dir,
        ga.tag,
        "runplot_figure_7_a",
        "ipy",
        sc.specl(model_name,
                 str(which_methods[0]),
                 '2018_08_10')
    )