#!/usr/bin/python
-from mvpa.misc.plot.base import plot_bars
from glob import glob
try:
from json import load as jload
'pypi': 'PyPi',
'pythonbundles': 'Python bundles',
'sourceforge': 'Sourceforge',
- 'other': 'Other resource'
+ 'otherres': 'Other resource'
}
# software categories
sw_categories = {
'bci': 'Brain-computer interface',
'acq': 'Hardware interface/Data acquisition',
'rt': 'Real-time solutions',
- 'psychophys': 'Psychophysics/Experiment control'
+ 'psychphys': 'Psychophysics/Experiment control'
}
# some meaningful groups of OSes
debian_family = ["debian", "ubuntu", "biolinux"]
suse_family = ["suse", "slel"]
other_linux_family = ["gentoo", "mandriva", "arch", "slackware", "otherlinux"]
-other_family = ["starbsd", "unix", "qnx", "beos", "solaris", "other"]
+other_family = ["starbsd", "unix", "qnx", "beos", "solaris", "other", "dontknow"]
os_cat_names = {
'win': 'Windows',
pl.barh(x, stat, left=bottoms, color=os_colors[i],
label=db.get_nice_name(os), height=0.8)
bottoms += stat
- pl.legend(loc='lower left')
+ pl.legend(loc='center left')
pl.yticks(x + 0.4, env_names[::-1])
pl.ylim(-0.25, len(envs))
+ pl.xlim(0,1)
pl.title("Operating system preference by environment")
pl.xlabel("Fraction of submissions")
pl.subplots_adjust(left=0.15, right=0.97)
x = np.arange(len(envs))
bottoms = np.zeros(len(envs))
for i, t in enumerate(time_order):
- stat = [env_stats[e][t] for e in envs]
+ stat = [env_stats[e][t] for e in envs[::-1]]
pl.barh(x, stat, left=bottoms, color=time_colors[i],
label=db.get_nice_name(t), height=.6)
bottoms += stat
- pl.legend(loc='center left')
- pl.yticks(x + 0.2, env_names)
+ pl.legend(loc='lower left')
+ pl.yticks(x + 0.2, env_names[::-1])
pl.ylim(-0.4, len(envs))
pl.title("Research activity time by environment")
pl.xlabel("Fraction of submissions")
multiple=False):
counts = db.get_counts(key)
pl.figure(figsize=(6.4, (len(counts)-2) * 0.4 + 2))
- tmargin = .8/len(counts)
+ if not len(counts): tmargin = 0.4
+ else: tmargin = .8/len(counts)
if tmargin > 0.3: tmargin = 0.3
pl.subplots_adjust(left=0.03, right=0.97, top=1-tmargin, bottom=tmargin)
pl.title(title)
pl.yticks(x + 0.5, ['' for s in stats])
text_offset = pl.gca().get_xlim()[1] / 30.
for i, s in enumerate(stats[::-1]):
- pl.text(text_offset, i+.5, db.get_nice_name(s[0]),
+ pl.text(text_offset, i+.5, db.get_nice_name(s[0]) + " [%d]" % (s[1],),
horizontalalignment='left',
verticalalignment='center',
bbox=dict(facecolor='white', alpha=0.8, edgecolor='white'))
mkpic_submissions_per_key(
db, destdir, 'sw_%s' % typ,
title="Software popularity: %s" % db.get_nice_name(typ),
- sortby='name')
+ sortby='count')
def mkpic_rating_by_os(db, env, items, destdir, title):
+ from mvpa.misc.plot.base import plot_bars
+
pl.figure(figsize=(6.4, 4.8))
for i, os in enumerate(os_order):
ratings = [db.select_match(env,
<table>
""" % (title, '=' * len(title), intro_sentence))
for k, it in enumerate(items):
- pl.figure(figsize=(3.2, 0.5))
+ if k == 0:
+ pl.figure(figsize=(3.2, 0.75))
+ else:
+ pl.figure(figsize=(3.2, 0.5))
it_nice = db.get_nice_name(it)#.lstrip('.').lstrip(' ')
it_nice = it_nice[0].upper() + it_nice[1:]
for i, os in enumerate(os_order):
# assume that we have 4 grades from 0 to 3
if len(ratings):
assert(max(ratings) < max_rating)
- total = len(ratings)
- bottom = 0
- for r in range(max_rating)[::-1]: # so we go from agree to don't
- stat = np.sum(ratings == r) * per_os_width / float(total)
- #print r, it, os, stat, total
- #if it == "pers_r8" and os == "linux" and r == 3:
- # import pydb; pydb.debugger()
- kwargs = dict(label=None)
- if stat:
- pl.barh(1.0/nos * (nos - 1 - i), stat, left=bottom, color=os_colors[i],
- height=.25, alpha=0.25 + r/float(max_rating),
- label=None,
- edgecolor=os_colors[i])
- bottom += stat
# Complement with errorbar
if len(ratings):
meanstat = np.mean(ratings)
- errstat = len(ratings) > 1 and np.std(ratings) or 0
- pl.errorbar([per_os_width * (max_rating-1 - float(meanstat))/(max_rating-1)],
+ meanstat_point = per_os_width * (float(meanstat))/(max_rating-1)
+ # standard error of estimate
+ errstat = len(ratings) > 1 and np.std(ratings)/np.sqrt(len(ratings)-1) or 0
+
+ if True:
+ # Beautiful piece not yet appreciated by the audience
+ total = len(ratings)
+ bottom = 0
+ for r in range(max_rating):
+ stat = np.sum(ratings == r) * meanstat_point / float(total)
+ #print r, it, os, stat, total
+ #if it == "pers_r8" and os == "linux" and r == 3:
+ # import pydb; pydb.debugger()
+ kwargs = dict(label=None)
+ if stat:
+ pl.barh(1.0/nos * (nos - 1 - i), stat, left=bottom, color=os_colors[i],
+ height=.25, alpha=0.25 + r/float(max_rating),
+ label=None,
+ edgecolor=os_colors[i])
+ bottom += stat
+ else:
+ pl.barh(1.0/nos * (nos - 1 - i), meanstat_point, left=0,
+ color=os_colors[i], height=.25, alpha=1.0, label=None)
+ pl.errorbar([meanstat_point],
[1.0/nos * (nos - 0.5 - i)],
xerr=[errstat], fmt='o', color=os_colors[i], ecolor='k')
- #plot_bars(ratings, offset=((i+1)*0.2)-0.1, color=os_colors[i],
- # title=title, ylabel="Mean rating", label=db.get_nice_name(os))
- #import pydb; pydb.debugger()
- #pl.xlim((0, per_os_width * len(os_order)))
- #pl.ylim((0, 1)) # len(items)))
- #pl.yticks((0, 3), ['Disagree', 'Agree'], rotation=90)
- #pl.xticks(np.arange(len(items))+0.5, [i[-2:] for i in items],
- # horizontalalignment='center')
- #pl.legend(loc='lower right')
pl.xlim((0, per_os_width))
- pl.ylim((0, 1))
+ if k == 0:
+ pl.text(0, 1.1, "Disagree", horizontalalignment='left')
+ pl.text(per_os_width, 1.1, "Agree", horizontalalignment='right')
+ pl.ylim((0, 1.5))
+ else:
+ pl.ylim((0, 1))
pl.axis('off')
- pl.subplots_adjust(left=0.01, right=0.99, bottom=0.0, top=1,
+ pl.subplots_adjust(left=0.00, right=1., bottom=0.0, top=1,
wspace=0.05, hspace=0.05)
fname = '%s/ratings_%s_%s.png' % (destdir, env, it)
pl.savefig(fname, format='png', dpi=80)
oddrow_s = k % 2 == 0 and ' class="oddrow"' or ''
rst.write("""
<tr%(oddrow_s)s>
- <td class="task">%(it_nice)s</td>
- <td class="response"> <div class="figure"><img border=0 alt="%(fname)s" src="%(fname)s" /> </div> </td> </tr>"""
+ <td>%(it_nice)s</td>
+ <td><img border="0" alt="%(fname)s" src="%(fname)s" /></td> </tr>"""
% (locals()))
- #pl.yticks(range(len(items)), [db.get_nice_name(it) for it in items])
- #pl.xlim((0, per_os_width))# * len(os_order)))
- #pl.ylim((0, len(items)))
- #pl.axis('off')
- #pl.subplots_adjust(left=0, right=1, bottom=0, top=1,
- # wspace=0.05, hspace=0.05)
- #pl.savefig('%s/ratings_%s.png' % (destdir, env), format='png', dpi=80)
- #pl.close()
rst.write("""
</table>
os.makedirs(destdir)
mkpic_submissions_per_key(
- db, destdir, 'virt_prod', sortby='name',
- title='Virtualization product popularity\n(multiple choices per submission possible)')
+ db, destdir, 'virt_prod', sortby='count',
+ title='Virtualization product popularity')
mkpic_submissions_per_key(
db, destdir, 'bg_datamod', sortby='count',
- title='Submissions per data modality\n(multiple choices per submission possible)')
+ title='Submissions per data modality')
mkpic_submissions_per_key(
db, destdir, 'bg_position', title='Submissions per position', sortby='count')
"Personal environment", "I prefer this particular scientific software environment because ...")
mkpic_rating_by_os_hor_joined(db, 'man_os', ['man_r%i' % i for i in range(1, 5)], destdir,
"Managed environment")
- mkpic_rating_by_os_hor_joined(db, 'virt_host_os', ['man_r%i' % i for i in range(1, 4)], destdir,
+ mkpic_rating_by_os_hor_joined(db, 'virt_host_os', ['virt_r%i' % i for i in range(1, 4)], destdir,
"Virtual environment (by host OS)")
- ## mkpic_rating_by_os(db, 'pers_os', ['pers_r%i' % i for i in range(1, 9)], destdir,
- ## "Ratings: Personal environment")
- ## mkpic_rating_by_os(db, 'man_os', ['man_r%i' % i for i in range(1, 5)], destdir,
- ## "Ratings: Managed environment")
- ## mkpic_rating_by_os(db, 'virt_host_os', ['virt_r%i' % i for i in range(1, 4)], destdir,
- ## "Ratings: Virtual environment (by host OS)")
# submission stats: this is RST
statsfile = open('%s/stats.txt' % destdir, 'w')
statsfile.write('::\n\n Number of submissions: %i\n' % len(db))
projects / neurodebian.git / blobdiff