#!/usr/bin/env python
# -*- coding: utf-8 -*-

import numpy as np
import matplotlib.pyplot as plt
from scipy import stats
from matplotlib import ticker
from mpl_toolkits.axes_grid1 import AxesGrid
from matplotlib.backends.backend_pdf import PdfPages

nums = 2
figs = [plt.figure(figsize=(11, 8.5)) for i in range(nums)]
grids = [AxesGrid(figs[i], 111, nrows_ncols=(4,4), axes_pad = 0.0, share_all=0, aspect=0) for i in range(nums)]

dd1 = np.linspace(5,75,25)
dd2 = np.linspace(100,900,50)

conc1 = np.random.randn(nums*16,25) * 30
conc2 = np.random.randn(nums*16,50) * 10

for i,j in zip(np.repeat(range(nums), 16), range(16*nums)):
    pass
    grids[i][j%16].plot(dd1, conc1[j], color='r', lw=1.5)
    grids[i][j%16].plot(dd2, conc2[j], color='b', lw=1.5)
 
for gg in grids:
    for grid in gg:
        grid.set_xlim(1,2000)
        grid.set_ylim(-50,50)
        grid.set_xscale('log')
        grid.set_xticks([10, 100, 1000])
        grid.set_yticks([-25, 0, 25])
        grid.yaxis.set_minor_locator(ticker.MultipleLocator(5))

# Saving the figures
pdf = PdfPages('test_speed.pdf') 

for fig in figs:
    fig.text(0.5, 0.01, u"Xlabel", fontsize=16, transform=fig.transFigure)
    fig.text(0.01, 0.6, u"Ylabel", fontsize=16, rotation='90', transform=fig.transFigure)
    fig.subplots_adjust(left=0.06, right=0.98, wspace=0.2, bottom=0.07, top=0.98)
    pdf.savefig(fig)

pdf.close()
plt.close('all')
plt.show()