5 from json import load as jload
9 from json import read as jread
11 return jread(f.read())
17 # uniform colors for OS results
18 os_colors = ['#AA2029', '#D1942B', '#7FB142', '#69A7CE']
19 os_order = ['linux', 'mac', 'win', 'otheros']
20 time_order = ['notime', 'little', 'most', 'always']
21 time_colors = ['#FF0000', '#FF5500', '#FFAC00', '#FFFD08']
23 'notime': "don't use it",
24 'little': "less than 50%",
25 'most': "more than 50%",
29 resource_categories = {
30 'vendor': 'Vendor/Project website',
31 'retailer': 'Retailer',
32 'os': 'Operating system',
37 'freebsdports': 'FreeBSD ports',
39 'macports': 'Macports',
40 'matlabcentral': 'Matlab Central',
41 'neurodebian': 'NeuroDebian',
44 'pythonbundles': 'Python bundles',
45 'sourceforge': 'Sourceforge',
46 'otherres': 'Other resource'
50 'general': 'General computing',
51 'dc': 'Distributed computing',
52 'img': 'Brain imaging',
53 'datamanage': 'Data management',
54 'neusys': 'Neural systems modeling',
55 'electro': 'Electrophysiology, MEG/EEG',
56 'bci': 'Brain-computer interface',
57 'acq': 'Hardware interface/Data acquisition',
58 'rt': 'Real-time solutions',
59 'psychphys': 'Psychophysics/Experiment control'
62 # some meaningful groups of OSes
63 redhat_family = ["rhel", "centos", "fedora", "scilinux"]
64 debian_family = ["debian", "ubuntu", "biolinux"]
65 suse_family = ["suse", "slel"]
66 other_linux_family = ["gentoo", "mandriva", "arch", "slackware", "otherlinux"]
67 other_family = ["starbsd", "unix", "qnx", "beos", "solaris", "other", "dontknow"]
79 'linux': redhat_family + debian_family + suse_family + other_linux_family,
80 'otheros': other_family
82 # end the reverse mapping
85 for os_ in os_family[ost]:
86 os_family_rev[os_] = ost
89 def load_list2dict(name):
93 if line.strip() == "":
98 "Got a line %s with a duplicate key %s whenever value for it "
99 "is known already to be %r" % (line, kv[0], d[kv[0]]))
100 d[kv[0]] = kv[1].strip().strip('"')
106 os_dict = load_list2dict('oslist.txt')
107 datamod_dict = load_list2dict('datamodlist.txt')
108 sw_dict = load_list2dict('swlist.txt')
109 position_dict = load_list2dict('position-dd-list.txt')
110 employer_dict = load_list2dict('employer-dd-list.txt')
111 ratings_dict = load_list2dict('ratingslist.txt')
112 vm_dict = load_list2dict('vmlist.txt')
114 def __init__(self, srcdir):
115 # eats the whole directory
118 datafilenames = glob('%s/*.json' % srcdir)
119 for dfn in datafilenames:
120 rawdata = jsonload(open(dfn))
121 self[rawdata['timestamp']] = rawdata
123 def get_unique(self, key):
124 # return a set of all (unique) values for a field id
126 for d in self.values():
129 if isinstance(el, list):
130 uniq = uniq.union(el)
132 uniq = uniq.union((el,))
135 def get_not_none(self, key):
136 # return a list of all values of a specific field id
137 # the second return value is count of submission that did not have data
141 for d in self.values():
144 if isinstance(el, list):
155 def get_counts(self, key):
156 # return a dict with field values as keys and respective submission
158 vals = self.get_not_none(key)[0]
159 uniq = np.unique(vals)
160 counts = dict(zip(uniq, [vals.count(u) for u in uniq]))
163 def select_match(self, key, values):
164 # return a db with all submissions were a field id has one of the
167 for k, v in self.items():
171 if isinstance(el, list):
172 if len(set(values).intersection(el)):
178 def select_match_exactly(self, key, values):
179 # return a db with all submissions were a field id has value
180 # equal to the supplied
182 set_values = set(values)
183 for k, v in self.items():
187 if isinstance(el, list):
188 if set(el) == set_values:
190 elif set([el]) == set_values:
194 def get_nice_name(self, id):
195 srcs = [DB.os_dict, os_cat_names, DB.sw_dict, sw_categories,
196 resource_categories, time_categories,
197 DB.datamod_dict, DB.position_dict, DB.employer_dict,
198 DB.vm_dict, DB.ratings_dict]
202 # not found, nothing nicer
206 def mkpic_os_per_env(db, destdir):
207 envs = ['pers_os', 'man_os', 'virt_host_os', 'virt_guest_os']
208 env_names = ['Personal', 'Managed', 'Virt. Host', 'Virt. Guest']
211 counts = db.get_counts(env)
212 stats = dict(zip(os_family.keys(), [0] * len(os_family)))
214 stats[os_family_rev[os]] += counts[os]
215 total_count = np.sum(stats.values())
220 stats[osf] = float(stats[osf]) / total_count
221 env_stats[env] = stats
222 # make stacked barplot
223 pl.figure(figsize=(7.5, 4))
224 x = np.arange(len(envs))
225 bottoms = np.zeros(len(envs))
226 for i, os in enumerate(os_order):
227 stat = [env_stats[e][os] for e in envs[::-1]]
228 pl.barh(x, stat, left=bottoms, color=os_colors[i],
229 label=db.get_nice_name(os), height=0.8)
231 pl.legend(loc='center left')
232 pl.yticks(x + 0.4, env_names[::-1])
233 pl.ylim(-0.25, len(envs))
235 pl.title("Operating system preference by environment")
236 pl.xlabel("Fraction of submissions")
237 pl.subplots_adjust(left=0.15, right=0.97)
238 pl.savefig('%s/ospref_by_env.png' % destdir, format='png', dpi=80)
241 def mkpic_time_per_env(db, destdir):
242 envs = ['pers_time', 'man_time', 'virt_time']
243 env_names = ['Personal', 'Managed', 'Virtual']
246 counts = dict(zip(time_order, [0] * len(time_order)))
247 counts.update(db.get_counts(env))
248 total_count = np.sum(counts.values())
250 counts[c] = float(counts[c]) / total_count
251 env_stats[env] = counts
252 # make stacked barplot
253 pl.figure(figsize=(7.5, 4))
254 x = np.arange(len(envs))
255 bottoms = np.zeros(len(envs))
256 for i, t in enumerate(time_order):
257 stat = [env_stats[e][t] for e in envs[::-1]]
258 pl.barh(x, stat, left=bottoms, color=time_colors[i],
259 label=db.get_nice_name(t), height=.6)
261 pl.legend(loc='lower left')
262 pl.yticks(x + 0.2, env_names[::-1])
263 pl.ylim(-0.4, len(envs))
264 pl.title("Research activity time by environment")
265 pl.xlabel("Fraction of submissions")
266 pl.subplots_adjust(right=0.97)
267 pl.savefig('%s/time_by_env.png' % destdir, format='png', dpi=80)
270 def mkpic_submissions_per_key(db, destdir, key, title, sortby='name',
272 counts = db.get_counts(key)
273 pl.figure(figsize=(6.4, (len(counts)-2) * 0.4 + 2))
274 if not len(counts): tmargin = 0.4
275 else: tmargin = .8/len(counts)
276 if tmargin > 0.3: tmargin = 0.3
277 pl.subplots_adjust(left=0.03, right=0.97, top=1-tmargin, bottom=tmargin)
280 pl.text(.5, .5, "[Insufficient data for this figure]",
281 horizontalalignment='center')
286 stats = sorted(counts.items(), cmp=lambda x, y: cmp(x[0], y[0]))
287 elif sortby == 'count':
288 stats = sorted(counts.items(), cmp=lambda x, y: cmp(x[1], y[1]))[::-1]
290 raise ValueError("Specify either name or count for sortby")
291 x = np.arange(len(stats))
292 pl.barh(x + (1./8), [s[1] for s in stats[::-1]], height=0.75, color = '#008200')
293 pl.yticks(x + 0.5, ['' for s in stats])
294 text_offset = pl.gca().get_xlim()[1] / 30.
295 for i, s in enumerate(stats[::-1]):
296 pl.text(text_offset, i+.5, db.get_nice_name(s[0]) + " [%d]" % (s[1],),
297 horizontalalignment='left',
298 verticalalignment='center',
299 bbox=dict(facecolor='white', alpha=0.8, edgecolor='white'))
300 pl.ylim(0, len(stats))
301 yl = "Number of submissions"
303 yl += "\n(multiple choices per submission possible)"
305 pl.savefig('%s/submissions_per_%s.png' % (destdir, key), format='png', dpi=80)
308 def mkpic_software(db, destdir):
309 for typ in sw_categories.keys():
310 mkpic_submissions_per_key(
311 db, destdir, 'sw_%s' % typ,
312 title="Software popularity: %s" % db.get_nice_name(typ),
315 def mkpic_rating_by_os(db, env, items, destdir, title):
316 from mvpa.misc.plot.base import plot_bars
318 pl.figure(figsize=(6.4, 4.8))
319 for i, os in enumerate(os_order):
320 ratings = [db.select_match(env,
321 os_family[os]).get_not_none('%s' % (it,))[0]
323 plot_bars(ratings, offset=((i+1)*0.2)-0.1, color=os_colors[i],
324 title=title, ylabel="Mean rating", label=db.get_nice_name(os))
326 pl.xlim((0,len(items)))
327 pl.yticks((0, 3), ['Disagree', 'Agree'], rotation=90)
328 pl.xticks(np.arange(len(items))+0.5, [i[-2:] for i in items],
329 horizontalalignment='center')
330 pl.legend(loc='lower right')
331 pl.savefig('%s/ratings_%s.png' % (destdir, env), format='png', dpi=80)
333 def mkpic_rating_by_os_hor_joined(db, env, items, destdir='.', title=None,
334 intro_sentence="I agree with the statements",
335 suffix='', max_rating=4):
337 #pl.figure(figsize=(6.4, 4.8))
338 if max_rating is None:
339 assert(len(items) == 1)
340 # We need to query for it
342 max_rating = np.max([db[k][field] for k in db if field in db[k]]) + 1
343 print "max ", max_rating
345 rst = open('figures/ratings_%s%s.rst' % (env, suffix), 'w')
356 """ % (title, '=' * len(title), intro_sentence))
357 for k, it in enumerate(items):
359 pl.figure(figsize=(3.2, 0.75))
361 pl.figure(figsize=(3.2, 0.5))
362 it_nice = db.get_nice_name(it)#.lstrip('.').lstrip(' ')
363 it_nice = it_nice[0].upper() + it_nice[1:]
364 for i, os in enumerate(os_order):
365 ratings = np.array(db.select_match(env,
366 os_family[os]).get_not_none('%s' % (it,))[0])
368 # assert(max(ratings) < max_rating)
369 # Complement with errorbar
371 scaling = float(per_os_width)/(max_rating-1)
372 meanstat = np.mean(ratings)
373 meanstat_point = scaling * meanstat
374 # standard error of estimate
375 errstat_point = len(ratings) > 1 and scaling*np.std(ratings)/np.sqrt(len(ratings)-1) or 0
376 #print ratings, meanstat, meanstat_point, errstat_point
378 # Beautiful piece not yet appreciated by the audience
381 max_rating_max = max(max_rating, max(ratings)+1)
382 for r in sorted(set(ratings)):#range(max_rating_max):
383 stat = np.sum(ratings == r) * meanstat_point / float(total)
384 #print r, it, os, stat, total
385 #if it == "pers_r8" and os == "linux" and r == 3:
386 # import pydb; pydb.debugger()
387 kwargs = dict(label=None)
389 pl.barh(1.0/nos * (nos - 1 - i), stat, left=bottom, color=os_colors[i],
390 height=.25, alpha=1./max_rating_max + r/float(max_rating_max),
392 edgecolor=os_colors[i])
395 pl.barh(1.0/nos * (nos - 1 - i), meanstat_point, left=0,
396 color=os_colors[i], height=.25, alpha=1.0, label=None)
397 pl.errorbar([meanstat_point],
398 [1.0/nos * (nos - 0.5 - i)],
399 xerr=[errstat_point], fmt='o', color=os_colors[i], ecolor='k')
400 pl.xlim((0, per_os_width))
401 if k == 0 and max_rating == 4: # ad-hoc: only for those disagree/agree
402 pl.text(0, 1.1, "Disagree", horizontalalignment='left')
403 pl.text(per_os_width, 1.1, "Agree", horizontalalignment='right')
408 pl.subplots_adjust(left=0.00, right=1., bottom=0.0, top=1,
409 wspace=0.05, hspace=0.05)
410 fname = '%s/ratings_%s_%s%s.png' % (destdir, env, it, suffix)
411 pl.savefig(fname, format='png', dpi=80)
413 oddrow_s = k % 2 == 0 and ' class="oddrow"' or ''
417 <td><img border="0" alt="%(fname)s" src="%(fname)s" /></td> </tr>"""
428 def main(srcdir, destdir):
431 ## Plot maintenance time per each group
432 # assess what would be our range
433 pmts, _ = db.get_not_none('pers_maint_time')
434 max_rating = int(np.mean(pmts) + np.std(pmts))
435 for pos in db.get_unique('bg_position'):
437 mkpic_rating_by_os_hor_joined(db.select_match('bg_position', pos),
438 'pers_os', ['pers_maint_time'], destdir,
439 "Personal environment", "", suffix='_maint_time_%s' % pos,
440 max_rating=max_rating)
443 # custom selection for people dealing more with hardware
445 ## db = db2.select_match('bg_datamod', (('ephys'),))
446 # or only selected ones (so no fmri/pet etc)
447 ## db = db2.select_match_exactly('bg_datamod', (('ephys'), ('behav'),))
448 ## db.update(db2.select_match_exactly('bg_datamod', (('ephys'),)))
449 ## db.update(db2.select_match_exactly('bg_datamod', (('ephys'), ('genetic'),)))
450 ## db.update(db2.select_match_exactly('bg_datamod', (('ephys'), ('simulation'),)))
451 ## db.update(db2.select_match_exactly('bg_datamod', (('ephys'), ('meeg'),)))
453 if not os.path.exists(destdir):
456 mkpic_submissions_per_key(
457 db, destdir, 'virt_prod', sortby='count',
458 title='Virtualization product popularity')
460 mkpic_submissions_per_key(
461 db, destdir, 'bg_datamod', sortby='count',
462 title='Submissions per data modality')
464 mkpic_submissions_per_key(
465 db, destdir, 'bg_position', title='Submissions per position', sortby='count')
467 mkpic_submissions_per_key(
468 db, destdir, 'bg_country', title='Submissions per country', sortby='count')
470 mkpic_submissions_per_key(
471 db, destdir, 'bg_employer', title='Submissions per venue', sortby='count')
473 mkpic_submissions_per_key(
474 db, destdir, 'software_resource', title='Software resource popularity', sortby='count')
476 for pic in [mkpic_os_per_env, mkpic_software, mkpic_time_per_env]:
480 mkpic_rating_by_os_hor_joined(db, 'pers_os', ['pers_r%i' % i for i in range(1, 9)], destdir,
481 "Personal environment", "I prefer this particular scientific software environment because ...")
482 mkpic_rating_by_os_hor_joined(db, 'man_os', ['man_r%i' % i for i in range(1, 6)], destdir,
483 "Managed environment")
484 mkpic_rating_by_os_hor_joined(db, 'virt_host_os', ['virt_r%i' % i for i in range(1, 5)], destdir,
485 "Virtual environment (by host OS)")
486 mkpic_rating_by_os_hor_joined(db, 'virt_guest_os', ['virt_r%i' % i for i in range(1, 5)], destdir,
487 "Virtual environment (by guest OS)")
489 ## mkpic_rating_by_os_hor_joined(db.select_match('virt_prod', (('vmware'),)),
490 ## 'virt_host_os', ['virt_r%i' % i for i in range(1, 5)], destdir,
491 ## "Virtualbox virtual environment (by host OS)")
493 # submission stats: this is RST
494 statsfile = open('%s/stats.txt' % destdir, 'w')
495 statsfile.write('::\n\n Number of submissions: %i\n' % len(db))
496 statsfile.write(' Statistics last updated: %s\n\n' \
497 % time.strftime('%A, %B %d %Y, %H:%M:%S UTC', time.gmtime()))
500 if __name__ == '__main__':
501 main(sys.argv[1], sys.argv[2])
502 #main('dataout', 'figures')