ThinkStats2/code/thinkplot.py at master · brianbentley/ThinkStats2 · GitHub

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"""This file contains code for use with "Think Stats",

by Allen B. Downey, available from greenteapress.com

License: GNU GPLv3 http://www.gnu.org/licenses/gpl.html

"""

from __future__ import print_function

import math

import matplotlib

import matplotlib.pyplot as pyplot

import numpy as np

import pandas

import warnings

# customize some matplotlib attributes

#matplotlib.rc('figure', figsize=(4, 3))

#matplotlib.rc('font', size=14.0)

#matplotlib.rc('axes', labelsize=22.0, titlesize=22.0)

#matplotlib.rc('legend', fontsize=20.0)

#matplotlib.rc('xtick.major', size=6.0)

#matplotlib.rc('xtick.minor', size=3.0)

#matplotlib.rc('ytick.major', size=6.0)

#matplotlib.rc('ytick.minor', size=3.0)

class _Brewer(object):

"""Encapsulates a nice sequence of colors.

Shades of blue that look good in color and can be distinguished

in grayscale (up to a point).

Borrowed from http://colorbrewer2.org/

"""

color_iter = None

colors = ['#081D58',

'#253494',

'#225EA8',

'#1D91C0',

'#41B6C4',

'#7FCDBB',

'#C7E9B4',

'#EDF8B1',

'#FFFFD9']

# lists that indicate which colors to use depending on how many are used

which_colors = [[],

[1],

[1, 3],

[0, 2, 4],

[0, 2, 4, 6],

[0, 2, 3, 5, 6],

[0, 2, 3, 4, 5, 6],

[0, 1, 2, 3, 4, 5, 6],

]

@classmethod

def Colors(cls):

"""Returns the list of colors.

"""

return cls.colors

@classmethod

def ColorGenerator(cls, n):

"""Returns an iterator of color strings.

n: how many colors will be used

"""

for i in cls.which_colors[n]:

yield cls.colors[i]

raise StopIteration('Ran out of colors in _Brewer.ColorGenerator')

@classmethod

def InitializeIter(cls, num):

"""Initializes the color iterator with the given number of colors."""

cls.color_iter = cls.ColorGenerator(num)

@classmethod

def ClearIter(cls):

"""Sets the color iterator to None."""

cls.color_iter = None

@classmethod

def GetIter(cls):

"""Gets the color iterator."""

if cls.color_iter is None:

cls.InitializeIter(7)

return cls.color_iter

def PrePlot(num=None, rows=None, cols=None):

"""Takes hints about what's coming.

num: number of lines that will be plotted

rows: number of rows of subplots

cols: number of columns of subplots

"""

if num:

_Brewer.InitializeIter(num)

if rows is None and cols is None:

return

if rows is not None and cols is None:

cols = 1

if cols is not None and rows is None:

rows = 1

# resize the image, depending on the number of rows and cols

size_map = {(1, 1): (8, 6),

(1, 2): (14, 6),

(1, 3): (14, 6),

(2, 2): (10, 10),

(2, 3): (16, 10),

(3, 1): (8, 10),

}

if (rows, cols) in size_map:

fig = pyplot.gcf()

fig.set_size_inches(*size_map[rows, cols])

# create the first subplot

if rows > 1 or cols > 1:

pyplot.subplot(rows, cols, 1)

global SUBPLOT_ROWS, SUBPLOT_COLS

SUBPLOT_ROWS = rows

SUBPLOT_COLS = cols

def SubPlot(plot_number, rows=None, cols=None):

"""Configures the number of subplots and changes the current plot.

rows: int

cols: int

plot_number: int

"""

rows = rows or SUBPLOT_ROWS

cols = cols or SUBPLOT_COLS

pyplot.subplot(rows, cols, plot_number)

def _Underride(d, **options):

"""Add key-value pairs to d only if key is not in d.

If d is None, create a new dictionary.

d: dictionary

options: keyword args to add to d

"""

if d is None:

d = {}

for key, val in options.items():

d.setdefault(key, val)

return d

def Clf():

"""Clears the figure and any hints that have been set."""

global LOC

LOC = None

_Brewer.ClearIter()

pyplot.clf()

fig = pyplot.gcf()

fig.set_size_inches(8, 6)

def Figure(**options):

"""Sets options for the current figure."""

_Underride(options, figsize=(6, 8))

pyplot.figure(**options)

def _UnderrideColor(options):

if 'color' in options:

return options

color_iter = _Brewer.GetIter()

if color_iter:

try:

options['color'] = next(color_iter)

except StopIteration:

# TODO: reconsider whether this should warn

# warnings.warn('Warning: Brewer ran out of colors.')

_Brewer.ClearIter()

return options

def Plot(obj, ys=None, style='', **options):

"""Plots a line.

Args:

obj: sequence of x values, or Series, or anything with Render()

ys: sequence of y values

style: style string passed along to pyplot.plot

options: keyword args passed to pyplot.plot

"""

options = _UnderrideColor(options)

label = getattr(obj, 'label', '_nolegend_')

options = _Underride(options, linewidth=3, alpha=0.8, label=label)

xs = obj

if ys is None:

if hasattr(obj, 'Render'):

xs, ys = obj.Render()

if isinstance(obj, pandas.Series):

ys = obj.values

xs = obj.index

if ys is None:

pyplot.plot(xs, style, **options)

else:

pyplot.plot(xs, ys, style, **options)

def FillBetween(xs, y1, y2=None, where=None, **options):

"""Plots a line.

Args:

xs: sequence of x values

y1: sequence of y values

y2: sequence of y values

where: sequence of boolean

options: keyword args passed to pyplot.fill_between

"""

options = _UnderrideColor(options)

options = _Underride(options, linewidth=0, alpha=0.5)

pyplot.fill_between(xs, y1, y2, where, **options)

def Bar(xs, ys, **options):

"""Plots a line.

Args:

xs: sequence of x values

ys: sequence of y values

options: keyword args passed to pyplot.bar

"""

options = _UnderrideColor(options)

options = _Underride(options, linewidth=0, alpha=0.6)

pyplot.bar(xs, ys, **options)

def Scatter(xs, ys=None, **options):

"""Makes a scatter plot.

xs: x values

ys: y values

options: options passed to pyplot.scatter

"""

options = _Underride(options, color='blue', alpha=0.2,

s=30, edgecolors='none')

if ys is None and isinstance(xs, pandas.Series):

ys = xs.values

xs = xs.index

pyplot.scatter(xs, ys, **options)

def HexBin(xs, ys, **options):

"""Makes a scatter plot.

xs: x values

ys: y values

options: options passed to pyplot.scatter

"""

options = _Underride(options, cmap=matplotlib.cm.Blues)

pyplot.hexbin(xs, ys, **options)

def Pdf(pdf, **options):

"""Plots a Pdf, Pmf, or Hist as a line.

Args:

pdf: Pdf, Pmf, or Hist object

options: keyword args passed to pyplot.plot

"""

low, high = options.pop('low', None), options.pop('high', None)

n = options.pop('n', 101)

xs, ps = pdf.Render(low=low, high=high, n=n)

options = _Underride(options, label=pdf.label)

Plot(xs, ps, **options)

def Pdfs(pdfs, **options):

"""Plots a sequence of PDFs.

Options are passed along for all PDFs. If you want different

options for each pdf, make multiple calls to Pdf.

Args:

pdfs: sequence of PDF objects

options: keyword args passed to pyplot.plot

"""

for pdf in pdfs:

Pdf(pdf, **options)

def Hist(hist, **options):

"""Plots a Pmf or Hist with a bar plot.

The default width of the bars is based on the minimum difference

between values in the Hist. If that's too small, you can override

it by providing a width keyword argument, in the same units

as the values.

Args:

hist: Hist or Pmf object

options: keyword args passed to pyplot.bar

"""

# find the minimum distance between adjacent values

xs, ys = hist.Render()

if 'width' not in options:

try:

options['width'] = 0.9 * np.diff(xs).min()

except TypeError:

warnings.warn("Hist: Can't compute bar width automatically."

"Check for non-numeric types in Hist."

"Or try providing width option."

)

options = _Underride(options, label=hist.label)

options = _Underride(options, align='center')

if options['align'] == 'left':

options['align'] = 'edge'

elif options['align'] == 'right':

options['align'] = 'edge'

options['width'] *= -1

Bar(xs, ys, **options)

def Hists(hists, **options):

"""Plots two histograms as interleaved bar plots.

Options are passed along for all PMFs. If you want different

options for each pmf, make multiple calls to Pmf.

Args:

hists: list of two Hist or Pmf objects

options: keyword args passed to pyplot.plot

"""

for hist in hists:

Hist(hist, **options)

def Pmf(pmf, **options):

"""Plots a Pmf or Hist as a line.

Args:

pmf: Hist or Pmf object

options: keyword args passed to pyplot.plot

"""

xs, ys = pmf.Render()

low, high = min(xs), max(xs)

width = options.pop('width', None)

if width is None:

try:

width = np.diff(xs).min()

except TypeError:

warnings.warn("Pmf: Can't compute bar width automatically."

"Check for non-numeric types in Pmf."

"Or try providing width option.")

points = []

lastx = np.nan

lasty = 0

for x, y in zip(xs, ys):

if (x - lastx) > 1e-5:

points.append((lastx, 0))

points.append((x, 0))

points.append((x, lasty))

points.append((x, y))

points.append((x+width, y))

lastx = x + width

lasty = y

points.append((lastx, 0))

pxs, pys = zip(*points)

align = options.pop('align', 'center')

if align == 'center':

pxs = np.array(pxs) - width/2.0

if align == 'right':

pxs = np.array(pxs) - width

options = _Underride(options, label=pmf.label)

Plot(pxs, pys, **options)

def Pmfs(pmfs, **options):

"""Plots a sequence of PMFs.

Options are passed along for all PMFs. If you want different

options for each pmf, make multiple calls to Pmf.

Args:

pmfs: sequence of PMF objects

options: keyword args passed to pyplot.plot

"""

for pmf in pmfs:

Pmf(pmf, **options)

def Diff(t):

"""Compute the differences between adjacent elements in a sequence.

Args:

t: sequence of number

Returns:

sequence of differences (length one less than t)

"""

diffs = [t[i+1] - t[i] for i in range(len(t)-1)]

return diffs

def Cdf(cdf, complement=False, transform=None, **options):

"""Plots a CDF as a line.

Args:

cdf: Cdf object

complement: boolean, whether to plot the complementary CDF

transform: string, one of 'exponential', 'pareto', 'weibull', 'gumbel'

options: keyword args passed to pyplot.plot

Returns:

dictionary with the scale options that should be passed to

Config, Show or Save.

"""

xs, ps = cdf.Render()

xs = np.asarray(xs)

ps = np.asarray(ps)

scale = dict(xscale='linear', yscale='linear')

for s in ['xscale', 'yscale']:

if s in options:

scale[s] = options.pop(s)

if transform == 'exponential':

complement = True

scale['yscale'] = 'log'

if transform == 'pareto':

complement = True

scale['yscale'] = 'log'

scale['xscale'] = 'log'

if complement:

ps = [1.0-p for p in ps]

if transform == 'weibull':

xs = np.delete(xs, -1)

ps = np.delete(ps, -1)

ps = [-math.log(1.0-p) for p in ps]

scale['xscale'] = 'log'

scale['yscale'] = 'log'

if transform == 'gumbel':

xs = xp.delete(xs, 0)

ps = np.delete(ps, 0)

ps = [-math.log(p) for p in ps]

scale['yscale'] = 'log'

options = _Underride(options, label=cdf.label)

Plot(xs, ps, **options)

return scale

def Cdfs(cdfs, complement=False, transform=None, **options):

"""Plots a sequence of CDFs.

cdfs: sequence of CDF objects

complement: boolean, whether to plot the complementary CDF

transform: string, one of 'exponential', 'pareto', 'weibull', 'gumbel'

options: keyword args passed to pyplot.plot

"""

for cdf in cdfs:

Cdf(cdf, complement, transform, **options)

def Contour(obj, pcolor=False, contour=True, imshow=False, **options):

"""Makes a contour plot.

d: map from (x, y) to z, or object that provides GetDict

pcolor: boolean, whether to make a pseudocolor plot

contour: boolean, whether to make a contour plot

imshow: boolean, whether to use pyplot.imshow

options: keyword args passed to pyplot.pcolor and/or pyplot.contour

"""

try:

d = obj.GetDict()

except AttributeError:

d = obj

_Underride(options, linewidth=3, cmap=matplotlib.cm.Blues)

xs, ys = zip(*d.keys())

xs = sorted(set(xs))

ys = sorted(set(ys))

X, Y = np.meshgrid(xs, ys)

func = lambda x, y: d.get((x, y), 0)

func = np.vectorize(func)

Z = func(X, Y)

x_formatter = matplotlib.ticker.ScalarFormatter(useOffset=False)

axes = pyplot.gca()

axes.xaxis.set_major_formatter(x_formatter)

if pcolor:

pyplot.pcolormesh(X, Y, Z, **options)

if contour:

cs = pyplot.contour(X, Y, Z, **options)

pyplot.clabel(cs, inline=1, fontsize=10)

if imshow:

extent = xs[0], xs[-1], ys[0], ys[-1]

pyplot.imshow(Z, extent=extent, **options)

def Pcolor(xs, ys, zs, pcolor=True, contour=False, **options):

"""Makes a pseudocolor plot.

xs:

ys:

zs:

pcolor: boolean, whether to make a pseudocolor plot

contour: boolean, whether to make a contour plot

options: keyword args passed to pyplot.pcolor and/or pyplot.contour

"""

_Underride(options, linewidth=3, cmap=matplotlib.cm.Blues)

X, Y = np.meshgrid(xs, ys)

Z = zs

x_formatter = matplotlib.ticker.ScalarFormatter(useOffset=False)

axes = pyplot.gca()

axes.xaxis.set_major_formatter(x_formatter)

if pcolor:

pyplot.pcolormesh(X, Y, Z, **options)

if contour:

cs = pyplot.contour(X, Y, Z, **options)

pyplot.clabel(cs, inline=1, fontsize=10)

def Text(x, y, s, **options):

"""Puts text in a figure.

x: number

y: number

s: string

options: keyword args passed to pyplot.text

"""

options = _Underride(options,

fontsize=16,

verticalalignment='top',

horizontalalignment='left')

pyplot.text(x, y, s, **options)

LEGEND = True

LOC = None

def Config(**options):

"""Configures the plot.

Pulls options out of the option dictionary and passes them to

the corresponding pyplot functions.

"""

names = ['title', 'xlabel', 'ylabel', 'xscale', 'yscale',

'xticks', 'yticks', 'axis', 'xlim', 'ylim']

for name in names:

if name in options:

getattr(pyplot, name)(options[name])

# looks like this is not necessary: matplotlib understands text loc specs

loc_dict = {'upper right': 1,

'upper left': 2,

'lower left': 3,

'lower right': 4,

'right': 5,

'center left': 6,

'center right': 7,

'lower center': 8,

'upper center': 9,

'center': 10,

}

global LEGEND

LEGEND = options.get('legend', LEGEND)

if LEGEND:

global LOC

LOC = options.get('loc', LOC)

pyplot.legend(loc=LOC)

def Show(**options):

"""Shows the plot.

For options, see Config.

options: keyword args used to invoke various pyplot functions

"""

clf = options.pop('clf', True)

Config(**options)

pyplot.show()

if clf:

Clf()

def Plotly(**options):

"""Shows the plot.

For options, see Config.

options: keyword args used to invoke various pyplot functions

"""

clf = options.pop('clf', True)

Config(**options)

import plotly.plotly as plotly

url = plotly.plot_mpl(pyplot.gcf())

if clf:

Clf()

return url

def Save(root=None, formats=None, **options):

"""Saves the plot in the given formats and clears the figure.

For options, see Config.

Args:

root: string filename root

formats: list of string formats

options: keyword args used to invoke various pyplot functions

"""

clf = options.pop('clf', True)

Config(**options)

if formats is None:

formats = ['pdf', 'eps']

try:

formats.remove('plotly')

Plotly(clf=False)

except ValueError:

pass

if root:

for fmt in formats:

SaveFormat(root, fmt)

if clf:

Clf()

def SaveFormat(root, fmt='eps'):

"""Writes the current figure to a file in the given format.

Args:

root: string filename root

fmt: string format

"""

filename = '%s.%s' % (root, fmt)

print('Writing', filename)

pyplot.savefig(filename, format=fmt, dpi=300)

# provide aliases for calling functons with lower-case names

preplot = PrePlot

subplot = SubPlot

clf = Clf

figure = Figure

plot = Plot

text = Text

scatter = Scatter

pmf = Pmf

pmfs = Pmfs

hist = Hist

hists = Hists

diff = Diff

cdf = Cdf

cdfs = Cdfs

contour = Contour

pcolor = Pcolor

config = Config

show = Show

save = Save

def main():

color_iter = _Brewer.ColorGenerator(7)

for color in color_iter:

print(color)

if __name__ == '__main__':

main()

ThinkStats2/code/thinkplot.py at master · brianbentley/ThinkStats2 · GitHub

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