runplot_figure_8_b.ipy

import numpy as np
import matplotlib.pyplot as plt

from pskf.tools.plot import specs as sc
import pskf.scripts.errorplot.arrays as ea
import pskf.scripts.errorplot.plot as ep
import pskf.scripts.errorplot.read as er
import pskf.tools.run.pythonmodule as pm

# Switches
is_read = 1
is_sort = 0
is_plot = 1
is_quot = 0
is_save = 0
is_show = 1
is_backup = 0

model_name = 'wavereal'

which_methods = [142, 4, 141]
# Difference between input alpha and manuscript beta

ensemble_sizes = [50, 70, 100, 250]
ensemble_size = 2000

# Read
if is_read:
    stat_array, stat_array_name = er.read(
        model=model_name,
        which_methods=which_methods,
        ensemble_sizes=ensemble_sizes,
        )

    np.save(stat_array_name, stat_array)
    print('Saved as ' + stat_array_name)

which_methods_sorted = which_methods

# Plot
if is_plot:

    # Figure
    fig = plt.figure('Errorplot', figsize=[10, 8])

    # Run plot function
    ax, pic_name = ep.plot(
        fig.add_subplot(1, 1, 1),
        model=model_name,
        which_methods=which_methods_sorted,
        ensemble_sizes=ensemble_sizes,
        axistitle='',
        figpos=[0.20, 0.3, 0.75, 0.6],
        ylims=[0.29, 0.36],
        yticks=np.arange(0.3, 0.5, 0.02),
        fontleg=20,
        is_text=True,
        text_x=1.0,
        text_y=0.34,
        legend_input=[r'Hybrid EnKF $\beta = 0.25$',
                      r'Hybrid EnKF $\beta = 0.5$, default',
                      r'Hybrid EnKF $\beta = 0.75$'],
        xlim_min=0.8,
        xlim_max=4.0,
        xdiff_nens=0.3,
        ylabel=r'RMSE  $\log_{10}(K/\mathrm{m}^2)$'
    )

    # Save
    if is_save:
        plt.savefig(pic_name)
        print('Saved as ' + pic_name)

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

# Quot
if is_quot:

    # Figure
    fig = plt.figure('Quotients', figsize=[10, 10])

    # Run plot function
    ax, pic_name = ep.quots(
        fig.add_subplot(1, 1, 1),
        model=model_name,
        which_methods=which_methods_sorted,
        ensemble_sizes=ensemble_sizes,
        ensemble_size=ensemble_size,
        figpos=[0.14, 0.14, 0.8, 0.8],
        # axistitle=model_name.upper()+r', $N_{e}$: '+str(ensemble_size),
        is_text=True,
    )

    # 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,
        ea.tag,
        "runplot_figure_8_b",
        "ipy",
        sc.specl(model_name,
                 '_'.join([str(i) for i in which_methods_sorted])[:],
                 '2018_08_10')
    )