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

# # Palettable

# Find Palettable online:
# 
# - Docs: https://jiffyclub.github.io/palettable/
# - GitHub: https://github.com/jiffyclub/palettable
# - PyPI: https://pypi.python.org/pypi/palettable/

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get_ipython().run_line_magic('matplotlib', 'inline')


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import matplotlib.pyplot as plt
import numpy as np


# # Palettable API

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from palettable.colorbrewer.qualitative import Set1_9


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Set1_9.name


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Set1_9.type


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Set1_9.number


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Set1_9.colors


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Set1_9.hex_colors


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Set1_9.mpl_colors


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Set1_9.mpl_colormap


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# requires ipythonblocks
Set1_9.show_as_blocks()


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Set1_9.show_continuous_image()


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Set1_9.show_discrete_image()


# # Setting the matplotlib Color Cycle

# Adapted from the example at http://matplotlib.org/examples/color/color_cycle_demo.html.
# Use the `.mpl_colors` attribute to change the color cycle used by matplotlib
# when colors for plots are not specified.

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from palettable.wesanderson import Aquatic1_5, Moonrise4_5


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x = np.linspace(0, 2 * np.pi)
offsets = np.linspace(0, 2*np.pi, 4, endpoint=False)
# Create array with shifted-sine curve along each column
yy = np.transpose([np.sin(x + phi) for phi in offsets])

plt.rc('lines', linewidth=4)
plt.rc('axes', color_cycle=Aquatic1_5.mpl_colors)

fig, (ax0, ax1)  = plt.subplots(nrows=2)

ax0.plot(yy)
ax0.set_title('Set default color cycle to Aquatic1_5')

ax1.set_color_cycle(Moonrise4_5.mpl_colors)
ax1.plot(yy)
ax1.set_title('Set axes color cycle to Moonrise4_5')

# Tweak spacing between subplots to prevent labels from overlapping
plt.subplots_adjust(hspace=0.3)


# # Using a Continuous Palette

# Adapted from http://matplotlib.org/examples/pylab_examples/hist2d_log_demo.html.
# Use the `.mpl_colormap` attribute any place you need a matplotlib colormap.

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from palettable.colorbrewer.sequential import YlGnBu_9


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from matplotlib.colors import LogNorm

#normal distribution center at x=0 and y=5
x = np.random.randn(100000)
y = np.random.randn(100000)+5

plt.hist2d(x, y, bins=40, norm=LogNorm(), cmap=YlGnBu_9.mpl_colormap)
plt.colorbar()


# Note that matplotlib already has colorbrewer palettes, as you can see at
# http://matplotlib.org/examples/color/colormaps_reference.html.
# Above I could have used `cmap=plt.cm.YlGnBu` for the same affect.

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