import matplotlib.pyplot as plt
import numpy as np

np.random.seed(12)

fig, ax = plt.subplots(1)

ax.hist(np.random.randn(1000))
fig.savefig('hist_matplotlib_default.png')

import matplotlib.pyplot as plt
import numpy as np

np.random.seed(12)

fig, ax = plt.subplots(1)

ax.hist(np.random.randn(1000))
ax.grid(True)
fig.savefig('hist_matplotlib_grid.png')

import prettyplotlib as ppl
import matplotlib.pyplot as plt
import numpy as np

np.random.seed(12)

fig, ax = plt.subplots(1)

ppl.hist(np.random.randn(1000))
fig.savefig('hist_prettyplotlib_default.png')

import prettyplotlib as ppl
import matplotlib.pyplot as plt
import numpy as np

np.random.seed(12)

fig, ax = plt.subplots(1)

# 'y' for the 'y' axis. Could also add a grid over the 'x' axis.
ppl.hist(ax, np.random.randn(1000), grid='y')
fig.savefig('hist_prettyplotlib_grid.png')

import prettyplotlib as ppl
import matplotlib.pyplot as plt
import numpy as np

np.random.seed(12)

fig, ax = plt.subplots(1)

# 'y' for the 'y' axis. Could also add a grid over the 'x' axis.
ppl.hist(ax, np.random.randn(1000), grid='y')
fig.savefig('hist_prettyplotlib_grid.png')

%load_ext autoreload
%autoreload 2

%pdb

import prettyplotlib as ppl
import matplotlib.pyplot as plt
import numpy as np

np.random.seed(12)

fig, ax = ppl.subplots()

# 'y' for the 'y' axis. Could also add a grid over the 'x' axis.
for i in range(2):
    ppl.hist(np.random.randn(1000), grid='y')
fig.savefig('hist_prettyplotlib_two_datasets.png')

ax._get_lines.color_cycle

print [(k,v) for k,v in ax.__dict__.iteritems() if 'cycle' in k]