#!/usr/bin/python
+from mvpa.misc.plot.base import plot_bars
from glob import glob
-import json
-import sys
+try:
+ from json import load as jload
+ def jsonload(f):
+ return jload(f)
+except ImportError:
+ from json import read as jread
+ def jsonload(f):
+ return jread(f.read())
+import sys, os
import pylab as pl
import numpy as np
+import time
+
+# uniform colors for OS results
+os_colors = ['#AA2029', '#D1942B', '#7FB142', '#69A7CE']
+os_order = ['linux', 'mac', 'win', 'otheros']
+time_order = ['notime', 'little', 'most', 'always']
+time_colors = ['#FF0000', '#FF5500', '#FFAC00', '#FFFD08']
+time_categories = {
+ 'notime': "don't use it",
+ 'little': "less than 50%",
+ 'most': "more than 50%",
+ 'always': "always"
+ }
+# resources
+resource_categories = {
+ 'vendor': 'Vendor/Project website',
+ 'retailer': 'Retailer',
+ 'os': 'Operating system',
+ 'cpan': 'CPAN',
+ 'cran': 'CRAN',
+ 'epel': 'EPEL',
+ 'fink': 'Fink',
+ 'freebsdports': 'FreeBSD ports',
+ 'incf': 'INCF',
+ 'macports': 'Macports',
+ 'matlabcentral': 'Matlab Central',
+ 'neurodebian': 'NeuroDebian',
+ 'nitrc': 'NITRC',
+ 'pypi': 'PyPi',
+ 'pythonbundles': 'Python bundles',
+ 'sourceforge': 'Sourceforge',
+ 'other': 'Other resource'
+ }
+# software categories
+sw_categories = {
+ 'general': 'General computing',
+ 'dc': 'Distributed computing',
+ 'img': 'Brain imaging',
+ 'datamanage': 'Data management',
+ 'neusys': 'Neural systems modeling',
+ 'electro': 'Electrophysiology, MEG/EEG',
+ 'bci': 'Brain-computer interface',
+ 'acq': 'Hardware interface/Data acquisition',
+ 'rt': 'Real-time solutions',
+ 'psychophys': 'Psychophysics/Experiment control'
+ }
+
+# some meaningful groups of OSes
+redhat_family = ["rhel", "centos", "fedora", "scilinux"]
+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"]
+
+os_cat_names = {
+ 'win': 'Windows',
+ 'mac': 'Mac OS',
+ 'linux': 'GNU/Linux',
+ 'otheros': 'Other OS'
+ }
+
+os_family = {
+ 'win': ["windows"],
+ 'mac': ["macosx"],
+ 'linux': redhat_family + debian_family + suse_family + other_linux_family,
+ 'otheros': other_family
+ }
+# end the reverse mapping
+os_family_rev = {}
+for ost in os_family:
+ for os_ in os_family[ost]:
+ os_family_rev[os_] = ost
+
+
+def load_list2dict(name):
+ d = {}
+ lfile = open(name)
+ for line in lfile:
+ if line.strip() == "":
+ continue
+ kv = line.split(':')
+ if kv[0] in d:
+ raise RuntimeError(
+ "Got a line %s with a duplicate key %s whenever value for it "
+ "is known already to be %r" % (line, kv[0], d[kv[0]]))
+ d[kv[0]] = kv[1].strip().strip('"')
+ return d
+
+
class DB(dict):
+ os_dict = load_list2dict('oslist.txt')
+ datamod_dict = load_list2dict('datamodlist.txt')
+ sw_dict = load_list2dict('swlist.txt')
+ position_dict = load_list2dict('position-dd-list.txt')
+ employer_dict = load_list2dict('employer-dd-list.txt')
+ ratings_dict = load_list2dict('ratingslist.txt')
+ vm_dict = load_list2dict('vmlist.txt')
+
def __init__(self, srcdir):
# eats the whole directory
+ if srcdir is None:
+ return
datafilenames = glob('%s/*.json' % srcdir)
for dfn in datafilenames:
- rawdata = json.load(open(dfn))
+ rawdata = jsonload(open(dfn))
self[rawdata['timestamp']] = rawdata
def get_unique(self, key):
def select_match(self, key, values):
# return a db with all submissions were a field id has one of the
# supplied values
- match = {}
+ match = DB(None)
for k, v in self.items():
if not key in v:
continue
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]
+ for src in srcs:
+ if id in src:
+ return src[id]
+ # not found, nothing nicer
+ return id
-def load_list2dict(name):
- d = {}
- lfile = open(name)
- for line in lfile:
- kv = line.split(':')
- d[kv[0]] = kv[1].strip().strip('"')
- return d
+def mkpic_os_per_env(db, destdir):
+ envs = ['pers_os', 'man_os', 'virt_host_os', 'virt_guest_os']
+ env_names = ['Personal', 'Managed', 'Virt. Host', 'Virt. Guest']
+ env_stats = {}
+ for env in envs:
+ counts = db.get_counts(env)
+ stats = dict(zip(os_family.keys(), [0] * len(os_family)))
+ for os in counts:
+ stats[os_family_rev[os]] += counts[os]
+ total_count = np.sum(stats.values())
+ for osf in stats:
+ if not total_count:
+ stats[osf] = 0
+ else:
+ stats[osf] = float(stats[osf]) / total_count
+ env_stats[env] = stats
+ # make stacked barplot
+ pl.figure(figsize=(7.5, 4))
+ x = np.arange(len(envs))
+ bottoms = np.zeros(len(envs))
+ for i, os in enumerate(os_order):
+ stat = [env_stats[e][os] for e in envs[::-1]]
+ 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.yticks(x + 0.4, env_names[::-1])
+ pl.ylim(-0.25, len(envs))
+ pl.title("Operating system preference by environment")
+ pl.xlabel("Fraction of submissions")
+ pl.subplots_adjust(left=0.15, right=0.97)
+ pl.savefig('%s/ospref_by_env.png' % destdir, format='png', dpi=80)
+
+
+def mkpic_time_per_env(db, destdir):
+ envs = ['pers_time', 'man_time', 'virt_time']
+ env_names = ['Personal', 'Managed', 'Virtual']
+ env_stats = {}
+ for env in envs:
+ counts = dict(zip(time_order, [0] * len(time_order)))
+ counts.update(db.get_counts(env))
+ total_count = np.sum(counts.values())
+ for c in counts:
+ counts[c] = float(counts[c]) / total_count
+ env_stats[env] = counts
+ # make stacked barplot
+ pl.figure(figsize=(7.5, 4))
+ 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]
+ 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.ylim(-0.4, len(envs))
+ pl.title("Research activity time by environment")
+ pl.xlabel("Fraction of submissions")
+ pl.subplots_adjust(right=0.97)
+ pl.savefig('%s/time_by_env.png' % destdir, format='png', dpi=80)
+
+
+def mkpic_submissions_per_key(db, destdir, key, title, sortby='name',
+ multiple=False):
+ counts = db.get_counts(key)
+ pl.figure(figsize=(6.4, (len(counts)-2) * 0.4 + 2))
+ 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)
+ if not len(counts):
+ pl.text(.5, .5, "[Insufficient data for this figure]",
+ horizontalalignment='center')
+ pl.axis('off')
+ else:
+ # sort by name
+ if sortby == 'name':
+ stats = sorted(counts.items(), cmp=lambda x, y: cmp(x[0], y[0]))
+ elif sortby == 'count':
+ stats = sorted(counts.items(), cmp=lambda x, y: cmp(x[1], y[1]))[::-1]
+ else:
+ raise ValueError("Specify either name or count for sortby")
+ x = np.arange(len(stats))
+ pl.barh(x + (1./8), [s[1] for s in stats[::-1]], height=0.75, color = '#008200')
+ 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]),
+ horizontalalignment='left',
+ verticalalignment='center',
+ bbox=dict(facecolor='white', alpha=0.8, edgecolor='white'))
+ pl.ylim(0, len(stats))
+ yl = "Number of submissions"
+ if multiple:
+ yl += "\n(multiple choices per submission possible)"
+ pl.xlabel(yl)
+ pl.savefig('%s/submissions_per_%s.png' % (destdir, key), format='png', dpi=80)
+
+
+def mkpic_software(db, destdir):
+ for typ in sw_categories.keys():
+ mkpic_submissions_per_key(
+ db, destdir, 'sw_%s' % typ,
+ title="Software popularity: %s" % db.get_nice_name(typ),
+ sortby='name')
+
+def mkpic_rating_by_os(db, env, items, destdir, title):
+ pl.figure(figsize=(6.4, 4.8))
+ for i, os in enumerate(os_order):
+ ratings = [db.select_match(env,
+ os_family[os]).get_not_none('%s' % (it,))[0]
+ for it in items]
+ 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))
+ pl.ylim((0,3))
+ pl.xlim((0,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.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
+ #pl.figure(figsize=(6.4, 4.8))
+ nos = len(os_order)
+ rst = open('figures/ratings_%s.rst' % env, 'w')
+ rst.write("""
+
+%s
+%s
+
+%s
+
+.. raw:: html
+
+ <table>
+ """ % (title, '=' * len(title), intro_sentence))
+ for k, it in enumerate(items):
+ 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):
+ 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)
+ 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)],
+ [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))
+ pl.axis('off')
+ pl.subplots_adjust(left=0.01, right=0.99, 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)
+ pl.close()
+ 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>"""
+ % (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>
+
+ """)
+ rst.close()
+ return
-def mkpic_submissions_per_datamod(db, destdir):
- # simple demo
- dmd = load_list2dict('datamodlist.txt')
- spd = db.get_counts('bg_datamod')
- spd = sorted(spd.items(), cmp=lambda x, y: cmp(x[1], y[1]))[::-1]
- x = np.arange(len(spd))
- pl.figure(figsize=(8, 6), dpi=80, facecolor='w', edgecolor='k')
- pl.title('Data modality')
- pl.bar(x, [s[1] for s in spd])
- pl.xticks(x + 0.5, [dmd[k[0]] for k in spd], rotation=-15)
- pl.ylabel('Survey submissions per data modality\n(multiple choices per submission possible)')
- pl.savefig('%s/submissions_per_datamod.png' % destdir, format='png')
def main(srcdir, destdir):
db = DB(srcdir)
- mkpic_submissions_per_datamod(db, destdir)
+ if not os.path.exists(destdir):
+ os.makedirs(destdir)
+
+ mkpic_submissions_per_key(
+ db, destdir, 'virt_prod', sortby='name',
+ title='Virtualization product popularity\n(multiple choices per submission possible)')
+
+ mkpic_submissions_per_key(
+ db, destdir, 'bg_datamod', sortby='count',
+ title='Submissions per data modality\n(multiple choices per submission possible)')
+
+ mkpic_submissions_per_key(
+ db, destdir, 'bg_position', title='Submissions per position', sortby='count')
+
+ mkpic_submissions_per_key(
+ db, destdir, 'bg_country', title='Submissions per country', sortby='count')
+
+ mkpic_submissions_per_key(
+ db, destdir, 'bg_employer', title='Submissions per venue', sortby='count')
+
+ mkpic_submissions_per_key(
+ db, destdir, 'software_resource', title='Software resource popularity', sortby='count')
+
+ 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,
+ "Managed environment")
+ mkpic_rating_by_os_hor_joined(db, 'virt_host_os', ['man_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))
+ statsfile.write(' Statistics last updated: %s\n\n' \
+ % time.strftime('%A, %B %d %Y, %H:%M:%S UTC', time.gmtime()))
+ statsfile.close()
if __name__ == '__main__':
main(sys.argv[1], sys.argv[2])