I just found some code (http://www.onerussian.com/tmp/plots.py and pasted below for review/feedback) laying around which I wrote around matplotlib for plotting primarily pair-wise stats results. Here is a demonstration: http://nbviewer.ipython.org/url/www.onerussian.com/tmp/run_plots.ipynb
I wonder if there is a need/place for it in matplotlib and what changes would you advise. Sorry for the lack of documentation -- I guess I have not finished it at that point (scipy dependency can easily be dropped, used only for standard error function iirc): #!/usr/bin/python #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: y...@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 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: 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: 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) pl.show() -- Yaroslav O. Halchenko Postdoctoral Fellow, Department of Psychological and Brain Sciences Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755 Phone: +1 (603) 646-9834 Fax: +1 (603) 646-1419 WWW: http://www.linkedin.com/in/yarik ------------------------------------------------------------------------------ Monitor your physical, virtual and cloud infrastructure from a single web console. Get in-depth insight into apps, servers, databases, vmware, SAP, cloud infrastructure, etc. Download 30-day Free Trial. Pricing starts from $795 for 25 servers or applications! http://p.sf.net/sfu/zoho_dev2dev_nov _______________________________________________ Matplotlib-devel mailing list Matplotlib-devel@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
