#!/usr/bin/python
+# emacs: -*- coding: utf-8; mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
from glob import glob
try:
import numpy as np
import time
+from common import entries_to_refresh
+fresh_keys = [k
+ for k, (regex, b) in
+ reduce(list.__add__,[x.items()
+ for x in entries_to_refresh['sw_other_name'].values()],
+ [])
+ if b]
+
# uniform colors for OS results
os_colors = ['#AA2029', '#D1942B', '#7FB142', '#69A7CE']
os_order = ['linux', 'mac', 'win', 'otheros']
missing += 1
return val, missing
- def get_counts(self, key):
+ def get_counts(self, key, predef_keys=None):
# return a dict with field values as keys and respective submission
# count as value
vals = self.get_not_none(key)[0]
uniq = np.unique(vals)
counts = dict(zip(uniq, [vals.count(u) for u in uniq]))
- return counts
+ if not predef_keys is None:
+ ret = dict(zip(predef_keys, [0] * len(predef_keys)))
+ else:
+ ret = {}
+ ret.update(counts)
+ return ret
def select_match(self, key, values):
# return a db with all submissions were a field id has one of the
match[k] = v
return match
+ def select_match_exactly(self, key, values):
+ # return a db with all submissions were a field id has value
+ # equal to the supplied
+ match = DB(None)
+ set_values = set(values)
+ for k, v in self.items():
+ if not key in v:
+ continue
+ el = v[key]
+ if isinstance(el, list):
+ if set(el) == set_values:
+ match[k] = v
+ elif set([el]) == set_values:
+ match[k] = v
+ return match
+
def get_nice_name(self, id):
srcs = [DB.os_dict, os_cat_names, DB.sw_dict, sw_categories,
resource_categories, time_categories,
DB.datamod_dict, DB.position_dict, DB.employer_dict,
DB.vm_dict, DB.ratings_dict]
+ suffix = u'$^†$' if id in fresh_keys else ''
for src in srcs:
if id in src:
- return src[id]
+ return src[id] + suffix
# not found, nothing nicer
- return id
+ return id + suffix
def mkpic_os_per_env(db, destdir):
pl.legend(loc='lower right')
pl.savefig('%s/ratings_%s.png' % (destdir, env), format='png', dpi=80)
-def mkpic_rating_by_os_hor_joined(db, env, items, destdir, title,
- intro_sentence="I agree with the statements"):
- per_os_width = 10
- max_rating = 4
+def mkpic_rating_by_os_hor_joined(db, env, items, destdir='.', title=None,
+ intro_sentence="I agree with the statements",
+ suffix='', max_rating=4):
+ per_os_width = 1
#pl.figure(figsize=(6.4, 4.8))
+ if max_rating is None:
+ assert(len(items) == 1)
+ # We need to query for it
+ field = items[0]
+ max_rating = np.max([db[k][field] for k in db if field in db[k]]) + 1
+ print "max ", max_rating
nos = len(os_order)
- rst = open('figures/ratings_%s.rst' % env, 'w')
+ rst = open('figures/ratings_%s%s.rst' % (env, suffix), 'w')
rst.write("""
%s
for i, os in enumerate(os_order):
ratings = np.array(db.select_match(env,
os_family[os]).get_not_none('%s' % (it,))[0])
- # assume that we have 4 grades from 0 to 3
- if len(ratings):
- assert(max(ratings) < max_rating)
+ #if len(ratings):
+ # assert(max(ratings) < max_rating)
# Complement with errorbar
if len(ratings):
+ scaling = float(per_os_width)/(max_rating-1)
meanstat = np.mean(ratings)
- meanstat_point = per_os_width * (float(meanstat))/(max_rating-1)
+ meanstat_point = scaling * meanstat
# standard error of estimate
- errstat = len(ratings) > 1 and np.std(ratings)/np.sqrt(len(ratings)-1) or 0
-
+ errstat_point = len(ratings) > 1 and scaling*np.std(ratings)/np.sqrt(len(ratings)-1) or 0
+ #print ratings, meanstat, meanstat_point, errstat_point
if True:
# Beautiful piece not yet appreciated by the audience
total = len(ratings)
bottom = 0
- for r in range(max_rating):
+ max_rating_max = max(max_rating, max(ratings)+1)
+ for r in sorted(set(ratings)):#range(max_rating_max):
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:
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),
+ height=.25, alpha=1./max_rating_max + r/float(max_rating_max),
label=None,
edgecolor=os_colors[i])
bottom += stat
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')
+ xerr=[errstat_point], fmt='o', color=os_colors[i], ecolor='k')
pl.xlim((0, per_os_width))
- if k == 0:
+ if k == 0 and max_rating == 4: # ad-hoc: only for those disagree/agree
pl.text(0, 1.1, "Disagree", horizontalalignment='left')
pl.text(per_os_width, 1.1, "Agree", horizontalalignment='right')
pl.ylim((0, 1.5))
pl.axis('off')
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)
+ fname = '%s/ratings_%s_%s%s.png' % (destdir, env, it, suffix)
pl.savefig(fname, format='png', dpi=80)
pl.close()
oddrow_s = k % 2 == 0 and ' class="oddrow"' or ''
def main(srcdir, destdir):
db = DB(srcdir)
+ if False:
+ ## Plot maintenance time per each group
+ # assess what would be our range
+ pmts, _ = db.get_not_none('pers_maint_time')
+ max_rating = int(np.mean(pmts) + np.std(pmts))
+ for pos in db.get_unique('bg_position'):
+ print pos
+ mkpic_rating_by_os_hor_joined(db.select_match('bg_position', pos),
+ 'pers_os', ['pers_maint_time'], destdir,
+ "Personal environment", "", suffix='_maint_time_%s' % pos,
+ max_rating=max_rating)
+
+ ## db2 = db
+ # custom selection for people dealing more with hardware
+ # any electrophys
+ ## db = db2.select_match('bg_datamod', (('ephys'),))
+ # or only selected ones (so no fmri/pet etc)
+ ## db = db2.select_match_exactly('bg_datamod', (('ephys'), ('behav'),))
+ ## db.update(db2.select_match_exactly('bg_datamod', (('ephys'),)))
+ ## db.update(db2.select_match_exactly('bg_datamod', (('ephys'), ('genetic'),)))
+ ## db.update(db2.select_match_exactly('bg_datamod', (('ephys'), ('simulation'),)))
+ ## db.update(db2.select_match_exactly('bg_datamod', (('ephys'), ('meeg'),)))
+
if not os.path.exists(destdir):
os.makedirs(destdir)
for pic in [mkpic_os_per_env, mkpic_software, mkpic_time_per_env]:
pic(db, destdir)
+
+
mkpic_rating_by_os_hor_joined(db, 'pers_os', ['pers_r%i' % i for i in range(1, 9)], destdir,
"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,
+ mkpic_rating_by_os_hor_joined(db, 'man_os', ['man_r%i' % i for i in range(1, 6)], destdir,
"Managed environment")
- mkpic_rating_by_os_hor_joined(db, 'virt_host_os', ['virt_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, 5)], destdir,
"Virtual environment (by host OS)")
+ mkpic_rating_by_os_hor_joined(db, 'virt_guest_os', ['virt_r%i' % i for i in range(1, 5)], destdir,
+ "Virtual environment (by guest OS)")
+
+ ## mkpic_rating_by_os_hor_joined(db.select_match('virt_prod', (('vmware'),)),
+ ## 'virt_host_os', ['virt_r%i' % i for i in range(1, 5)], destdir,
+ ## "Virtualbox virtual environment (by host OS)")
# submission stats: this is RST
statsfile = open('%s/stats.txt' % destdir, 'w')
if __name__ == '__main__':
main(sys.argv[1], sys.argv[2])
+ #main('dataout', 'figures')
projects / neurodebian.git / blobdiff