http://www.mediawiki.org/wiki/Special:Code/MediaWiki/95377
Revision: 95377
Author: giovanni
Date: 2011-08-24 06:40:24 +0000 (Wed, 24 Aug 2011)
Log Message:
-----------
added normplot.py
Added Paths:
-----------
trunk/tools/wsor/editor_lifecycle/normplot.py
Added: trunk/tools/wsor/editor_lifecycle/normplot.py
===================================================================
--- trunk/tools/wsor/editor_lifecycle/normplot.py
(rev 0)
+++ trunk/tools/wsor/editor_lifecycle/normplot.py 2011-08-24 06:40:24 UTC
(rev 95377)
@@ -0,0 +1,76 @@
+#!/usr/bin/python
+
+import os
+import sys
+
+import numpy as np
+import matplotlib.pyplot as pp
+
+from argparse import ArgumentParser
+from collections import defaultdict
+from datetime import datetime
+from matplotlib.font_manager import FontProperties
+
+__prog__ = os.path.basename(__file__)
+
+parser = ArgumentParser(description=__doc__)
+parser.add_argument('input_paths', metavar='data', nargs='+')
+parser.add_argument('-t', '--title', required=1)
+parser.add_argument('-xlim', nargs=2, metavar='YEAR', type=int)
+parser.add_argument('-ylim', nargs=2, metavar='VALUE', type=float)
+
+conv = defaultdict(lambda k : float)
+conv[0] = lambda k : datetime.strptime(k, '%Y-%m')
+markers = 'ov^<>sp*D'
+colors = 'brcmgyk'
+M = len(markers)
+C = len(colors)
+labeltempl = r'$10^{%d} \leq a < 10^{%d}$'
+
+if __name__ == '__main__':
+ ns = parser.parse_args()
+
+ lines = []
+
+ fig = pp.figure(figsize=(8,4))
+ ax = fig.add_axes(pp.axes([.1,.1,.65,.8], axisbg='whitesmoke'))
+
+ for i, path in enumerate(ns.input_paths):
+ try:
+ data = np.loadtxt(path, converters=conv, dtype=object, skiprows=1)
+ except IOError, e:
+ print >> sys.stderr, '%s: skipping %s because: %s' % (__prog__,\
+ path, e.message or e.args[1])
+ continue
+ act, peak_date, peak_date_err, peak, peak_err =
np.asfarray(data[:,1:]).T
+ a = act[0]
+ cohort = data[:, 0]
+ idx = np.argsort(cohort)
+ cohort = cohort[idx]
+ peak = peak[idx] / peak.mean()
+ l, = ax.plot(cohort, peak, marker=markers[i % M], color=colors[i % C],
+ ls='none', mec=colors[i % C], label=labeltempl % (a-1, a),
ms=8,
+ alpha=.65)
+ lines.append(l)
+
+ pp.figlegend(lines, [ l.get_label() for l in lines ],
+ loc='center right', prop=FontProperties(size='medium'))
+
+ if ns.xlim:
+ pp.xlim(datetime(ns.xlim[0],1,1), datetime(ns.xlim[1],1,1))
+ if ns.ylim:
+ pp.ylim(ns.ylim)
+
+ pp.xlabel('cohort')
+ pp.ylabel(r'normalized activity $\frac{a_p}{< a_p >}$')
+
+ pp.title(ns.title)
+ ax.minorticks_on()
+ ax.grid("on")
+ pp.draw()
+
+ output_path = ns.title.replace(' ', '_').lower() + '.pdf'
+ pp.savefig(output_path, fmt='pdf')
+ print 'figure saved to %s' % output_path
+
+ pp.show()
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