Improved boxplots

gistfile1.py

#emacs: -*- mode: python-mode; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*- 
#ex: set sts=4 ts=4 sw=4 noet:
#------------------------- =+- Python script -+= -------------------------
"""
 @file      paired-plots.py
 @date      Fri Jan 13 11:48:00 2012
 @brief


  Yaroslav Halchenko                                            Dartmouth
  web:     http://www.onerussian.com                              College
  e-mail:  yoh@onerussian.com                              ICQ#: 60653192

 DESCRIPTION (NOTES):

 COPYRIGHT: Yaroslav Halchenko 2012

 LICENSE: MIT

  Permission is hereby granted, free of charge, to any person obtaining a copy
  of this software and associated documentation files (the "Software"), to deal
  in the Software without restriction, including without limitation the rights
  to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
  copies of the Software, and to permit persons to whom the Software is
  furnished to do so, subject to the following conditions:

  The above copyright notice and this permission notice shall be included in
  all copies or substantial portions of the Software.

  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
  IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
  FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
  AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
  LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
  OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
  THE SOFTWARE.
"""
#-----------------\____________________________________/------------------

__author__ = 'Yaroslav Halchenko'
__revision__ = '$Revision: $'
__date__ = '$Date:  $'
__copyright__ = 'Copyright (c) 2012 Yaroslav Halchenko'
__license__ = 'MIT'


import numpy as np
import pylab as pl
import scipy.stats as ss

def plot_boxplot_enhanced(
    v,
    contrast_labels=None,
    condition_labels=None,
    ccolors=['y', 'b'],
    rand_offsets=None,
    grid=True,
    xticks_rotation=0,
    **bp_kwargs):

    width = bp_kwargs.get('width', 0.5)
    pl.boxplot(v, **bp_kwargs)

    if v.ndim < 2: v = v[:, None]
    ncol = v.shape[1]

    eff = np.mean(v, axis=0)          # effect sizes
    sem = ss.sem(v, axis=0)

    if rand_offsets is None:
        rand_offsets = np.random.randn(len(v)) * 0.02

    pl.plot((np.arange(ncol) + 1)[:, None] + rand_offsets,
            v.T, '.', color='k', markerfacecolor='k')
    for i in range(ncol):
        lw = 2
        pl.plot([1 - width/2. + i, 1+i],
                [0, 0],
                '--', color=ccolors[0], linewidth=lw) # first condition
        pl.plot([1+i, 1 + width/2. +i],
                [eff[i]]*2,
                '--', color=ccolors[1], linewidth=lw)

        # place ste
        pl.errorbar(i+1 + 1.1*width/2.,
                    eff[i],
                    sem[i],
                    elinewidth=2, linewidth=0,
                    color='r', ecolor='r')

        if contrast_labels is not None and not i:                    # only for the first one
            pl.text(1 - 1.1*width/2 + i, 0.1, contrast_labels[0],
                    verticalalignment='bottom',
                    horizontalalignment='right')
            pl.text(1 + 1.2*width/2 + i, eff[i], contrast_labels[1],
                    verticalalignment='bottom', horizontalalignment='left')
    ax = pl.gca()
    if condition_labels is not None:
        ax.set_xticklabels(condition_labels, rotation=xticks_rotation)
    else:
        # hide it
        ax.axes.xaxis.set_visible(False)

    if grid:
        ax.grid()
    return ax


def plot_paired_stats(
    v0, v1, contrast_labels,
    condition_labels=None,
    style=['barplot_effect',
           'boxplot_raw',
           'boxplot_effect'],
    ccolors=['y', 'g'],
    xticks_rotation=0,
    grid=False,
    fig=None,
    bottom_adjust=None,
    bp_kwargs={}):

    if isinstance(style, str):
        style = [style]

    nplots = len(style)                 # how many subplots will be needed

    # assure having 2nd dimension
    if v0.ndim < 2: v0 = v0[:, None]
    if v1.ndim < 2: v1 = v1[:, None]
    assert(v0.shape == v1.shape)

    ncol = v0.shape[1]
    v10 = (v1 - v0)                     # differences
    mv0 = np.mean(v0, axis=0)           # means
    mv1 = np.mean(v1, axis=0)

    eff = np.mean(v10, axis=0)          # effect sizes
    sem = ss.sem(v10, axis=0)

    # so that data points have are distinguishable
    rand_offsets = np.random.randn(len(v10)) * 0.02

    # interleaved combination for some plots
    v_ = np.hstack((v0, v1))
    v = np.zeros(v_.shape, dtype=v_.dtype)
    v[:, np.hstack((np.arange(0, ncol*2, 2),
                    np.arange(1, ncol*2, 2)))] = v_

    #print v.shape
    #print np.mean(v0, axis=0), np.mean(v1, axis=0)
    #print np.min(v10, axis=0), np.max(v10, axis=0), \
    #      np.mean(v10, axis=0), ss.sem(v10, axis=0)
    #pl.boxplot(v10 + np.mean(v1), notch=1, widths=0.05)

    #print v0.shape, v1.shape, np.hstack([v0, v1]).shape

    if fig is None:
        fig = pl.figure()

    bwidth = 0.5
    plot = 1

    if condition_labels is not None:
        xlabels = [ '%s:%s' % (cond, contr)
                    for cond in condition_labels
                    for contr in contrast_labels ]
    else:
        xlabels = contrast_labels

    bp_kwargs_ = {
        #'bootstrap': 0,
        'notch' : 1
        }
    bp_kwargs_.update(bp_kwargs)

    def plot_grid(ax):
        if grid:
            ax.grid()

    if 'barplot_effect' in style:
        if len(style) > 1:
            pl.subplot(1, nplots, plot)
        plot += 1
        # The simplest one
        pl.bar(np.arange(1, ncol*2+1) - bwidth/2,
               np.mean(v, axis=0),
               color=ccolors*ncol,
               edgecolor=ccolors*ncol,
               alpha=0.8,
               width=bwidth)
        #pl.minorticks_off()
        pl.tick_params('x', direction='out', length=6, width=1,
                       top=False)
        ax = pl.gca()
        pl.xlim(0.5, ncol*2+0.5)
        ax.set_xticks(np.arange(1, ncol*2+1))
        ax.set_xticklabels(xlabels, rotation=xticks_rotation)
        # place ste for effect size into the 2nd column
        pl.errorbar(np.arange(ncol)*2+2,
                    mv1,
                    sem, elinewidth=2, linewidth=0,
                    color='g', ecolor='r')

        plot_grid(ax)

    if 'boxplot_raw' in style:
        if len(style) > 1:
            pl.subplot(1, nplots, plot)
        plot += 1

        # Figure 1 -- "raw" data
        # plot "connections" between boxplots
        for i in range(ncol):
            pargs = (np.array([i*2+1, i*2+2])[:, None] + rand_offsets,
                     np.array([v0[:,i], v1[:,i]]))
            pl.plot(*(pargs+('-',)), color='k', alpha=0.5, linewidth=0.25)
            pl.plot(*(pargs+('.',)), color='k', alpha=0.9)
        # boxplot of "raw" data
        bp1 = pl.boxplot(v, widths=bwidth, **bp_kwargs_)
        for i in range(ncol):
            for c in xrange(2):
                b = bp1['boxes'][2*i+c]
                b.set_color(ccolors[c])
                b.set_linewidth(2)

        ax = pl.gca()
        ax.set_xticklabels(xlabels, rotation=xticks_rotation)
        plot_grid(ax)

    if 'boxplot_effect' in style:
        if len(style) > 1:
            pl.subplot(1, nplots, plot)
        plot += 1
        plot_boxplot_enhanced(v10,
                              contrast_labels=contrast_labels,
                              condition_labels=condition_labels,
                              widths=bwidth,
                              rand_offsets=rand_offsets, # reuse them
                              grid=grid,
                              **bp_kwargs_)

    if bottom_adjust:
        fig.subplots_adjust(bottom=bottom_adjust)
    pl.draw_if_interactive()
    return fig

if __name__ == '__main__':

    if True:
        v = np.random.normal(size=(50,8)) * 20 + 120
        if False:
            v[:, 1] += 40
            v[:, 3] -= 30
            v[:, 5] += 60
            v[:, 6] -= 60
        else:
            v -= np.arange(v.shape[1])*10
        v /= 10

    v0 = v[:, ::2]
    v1 = v[:, 1::2]
    d = v1 - v0
    print np.mean(d, axis=0)
    styles = ['barplot_effect',
              'boxplot_raw',
              'boxplot_effect'
              ]
    styles = styles + [styles]
    pl.close('all')

    if False:
        f = plot_boxplot_enhanced((v1-v0)[:,0],
                                  grid=True, xticks_rotation=30, notch=1)

    for s in styles:
        fig = pl.figure(figsize=(12,6))
        f = plot_paired_stats(v0, v1, ['cont1', 'cont2'],
                              style=s, fig=fig,
                              condition_labels=['exp1', 'exp2', 'exp3', 'exp4'],
                              grid=True, xticks_rotation=30,
                              bp_kwargs={'notch': False})
    pl.show()