def plot_data_split(request, id, split_nr):
split_nr = int(split_nr)
task = get_object_or_404(Task, pk=id)
img = [task.get_split_image(split_nr)]
#import pdb
#pdb.set_trace()
if (img == None):
return None
# why it does not work ?
from pylab import axis
axis('off')
from StringIO import StringIO
dpi = 60
bgcol = '#ffffff'
fig = Figure(figsize=(7, 0.3), dpi=dpi, facecolor=bgcol)
canvas = FigureCanvas(fig)
bx = fig.add_subplot(111)
bx.set_yticklabels([])
bx.set_xticklabels([])
bx.set_yticks([])
#import pdb
#pdb.set_trace()
bx.imshow(img,
aspect='auto',
interpolation='nearest',
vmin=0,
vmax=3,
cmap=cmap_mldata)
# bx = fig.add_subplot(212)
# bx.set_yticklabels([])
# bx.set_xticklabels([])
# bx.imshow(img,aspect='auto',interpolation='nearest',cmap=cm.jet,extent=[0,len(img[0])-1,0,1])
canvas.draw()
imdata = StringIO()
fig.savefig(imdata, format='png', dpi=dpi, facecolor=bgcol)
return HttpResponse(imdata.getvalue(), mimetype='image/png')
def plot_data_split(request,id,split_nr):
split_nr=int(split_nr)
task=get_object_or_404(Task, pk=id)
img = [task.get_split_image(split_nr)]
#import pdb
#pdb.set_trace()
if (img == None):
return None
# why it does not work ?
from pylab import axis
axis('off')
from StringIO import StringIO
dpi=60
bgcol='#ffffff'
fig = Figure(figsize=(7,0.3), dpi=dpi, facecolor=bgcol)
canvas = FigureCanvas(fig)
bx = fig.add_subplot(111)
bx.set_yticklabels([])
bx.set_xticklabels([])
bx.set_yticks([])
#import pdb
#pdb.set_trace()
bx.imshow(img,aspect='auto',interpolation='nearest',vmin=0,vmax=3,cmap=cmap_mldata)
# bx = fig.add_subplot(212)
# bx.set_yticklabels([])
# bx.set_xticklabels([])
# bx.imshow(img,aspect='auto',interpolation='nearest',cmap=cm.jet,extent=[0,len(img[0])-1,0,1])
canvas.draw()
imdata=StringIO()
fig.savefig(imdata,format='png', dpi=dpi, facecolor=bgcol)
return HttpResponse(imdata.getvalue(),mimetype='image/png')
def stats_helper(request, software_id, type, dpi):
# matplotlib needs a writable home directory
if settings.PRODUCTION:
import os
os.environ['HOME']='/home/mloss/tmp'
import matplotlib
import datetime
matplotlib.use('Cairo')
from matplotlib.figure import Figure
from matplotlib.backends.backend_cairo import FigureCanvasCairo as FigureCanvas
from matplotlib.dates import DayLocator, WeekdayLocator, HourLocator, MonthLocator, YearLocator
from matplotlib.dates import DateFormatter, date2num
from StringIO import StringIO
if dpi<=40:
bgcol='#f7f7f7'
else:
bgcol='#ffffff'
fig = Figure(figsize=(8,6), dpi=dpi, facecolor=bgcol)
canvas = FigureCanvas(fig)
ax = fig.add_subplot(111)
stat = SoftwareStatistics.objects.filter(software=software_id).distinct().order_by('date')
if stat.count()<=0:
return HttpResponseForbidden()
x=list()
y=list()
for entry in stat:
x.append(date2num(entry.date))
if type=='downloads':
y.append(entry.number_of_downloads)
elif type=='views':
y.append(entry.number_of_views)
#ax.plot(x,y,'bo', alpha=0.7)
#ax.plot(x,y,'b-',linewidth=1, alpha=0.5)
ax.bar(x,y)
days = DayLocator()
weeks= WeekdayLocator()
months= MonthLocator()
years= YearLocator()
dateFmt = DateFormatter("%Y-%m-%d")
ax.xaxis.set_major_formatter(dateFmt)
if len(x)<=14:
ax.xaxis.set_major_locator(days)
elif len(x)<60:
ax.xaxis.set_major_locator(weeks)
ax.xaxis.set_minor_locator(days)
elif len(x)<720:
ax.xaxis.set_major_locator(months)
ax.xaxis.set_minor_locator(weeks)
else:
ax.xaxis.set_major_locator(years)
ax.xaxis.set_minor_locator(months)
if dpi>40:
if type=='downloads':
ax.set_title('Number of Downloads')
ax.set_ylabel('Downloads per Day')
elif type=='views':
ax.set_title('Number of Views')
ax.set_ylabel('Views per Day')
ax.grid(True)
ax.axis("tight")
for label in ax.get_xticklabels():
label.set_ha('right')
label.set_rotation(30)
canvas.draw()
imdata=StringIO()
fig.savefig(imdata,format='png', dpi=dpi, facecolor=bgcol)
del fig
del ax
return HttpResponse(imdata.getvalue(), mimetype='image/png')
def plot_legend(request):
import numpy
img=numpy.array([[0,1,2,3]])
#from pylab import axis
#axis('off')
from StringIO import StringIO
dpi=25
bgcol='#ffffff'
fig = Figure(figsize=(7,1.5), dpi=dpi, facecolor=bgcol)
canvas = FigureCanvas(fig)
ax = fig.add_subplot(171)
ax.set_title('not used')
ax.title.set_fontsize(30)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.set_yticks([])
ax.set_xticks([])
ax.imshow([[0]],interpolation='nearest',vmin=0,vmax=3,cmap=cmap_mldata)
bx = fig.add_subplot(173)
bx.set_title('train')
bx.title.set_fontsize(30)
bx.set_yticklabels([])
bx.set_xticklabels([])
bx.set_yticks([])
bx.set_xticks([])
bx.imshow([[1]],interpolation='nearest',vmin=0,vmax=3,cmap=cmap_mldata)
cx = fig.add_subplot(175)
cx.set_title('validation')
cx.title.set_fontsize(30)
cx.set_yticklabels([])
cx.set_xticklabels([])
cx.set_yticks([])
cx.set_xticks([])
cx.imshow([[2]],interpolation='nearest',vmin=0,vmax=3,cmap=cmap_mldata)
dx = fig.add_subplot(177)
dx.set_title('test')
dx.title.set_fontsize(30)
dx.set_yticklabels([])
dx.set_xticklabels([])
dx.set_yticks([])
dx.set_xticks([])
dx.imshow([[3]],interpolation='nearest',vmin=0,vmax=3,cmap=cmap_mldata)
#bx.set_title('legend')
#bx.set_yticklabels([])
#bx.set_xticklabels([])
#bx.set_yticklabels([])
#bx.set_xticklabels(['not used','train','validation','test'])
#bx.set_yticks([])
#bx.set_xticks([2,7,12,17])
#for label in bx.get_xticklabels():
# label.set_fontsize(12)
#bx.imshow([[0,0,0,0,0,1,1,1,1,1,2,2,2,2,2,3,3,3,3,3]],aspect=None,interpolation='nearest',cmap=cm.Greys)
canvas.draw()
imdata=StringIO()
fig.savefig(imdata,format='png', dpi=dpi, facecolor=bgcol)
return HttpResponse(imdata.getvalue(),mimetype='image/png')
def plot_legend(request):
import numpy
img = numpy.array([[0, 1, 2, 3]])
#from pylab import axis
#axis('off')
from StringIO import StringIO
dpi = 25
bgcol = '#ffffff'
fig = Figure(figsize=(7, 1.5), dpi=dpi, facecolor=bgcol)
canvas = FigureCanvas(fig)
ax = fig.add_subplot(171)
ax.set_title('not used')
ax.title.set_fontsize(30)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.set_yticks([])
ax.set_xticks([])
ax.imshow([[0]], interpolation='nearest', vmin=0, vmax=3, cmap=cmap_mldata)
bx = fig.add_subplot(173)
bx.set_title('train')
bx.title.set_fontsize(30)
bx.set_yticklabels([])
bx.set_xticklabels([])
bx.set_yticks([])
bx.set_xticks([])
bx.imshow([[1]], interpolation='nearest', vmin=0, vmax=3, cmap=cmap_mldata)
cx = fig.add_subplot(175)
cx.set_title('validation')
cx.title.set_fontsize(30)
cx.set_yticklabels([])
cx.set_xticklabels([])
cx.set_yticks([])
cx.set_xticks([])
cx.imshow([[2]], interpolation='nearest', vmin=0, vmax=3, cmap=cmap_mldata)
dx = fig.add_subplot(177)
dx.set_title('test')
dx.title.set_fontsize(30)
dx.set_yticklabels([])
dx.set_xticklabels([])
dx.set_yticks([])
dx.set_xticks([])
dx.imshow([[3]], interpolation='nearest', vmin=0, vmax=3, cmap=cmap_mldata)
#bx.set_title('legend')
#bx.set_yticklabels([])
#bx.set_xticklabels([])
#bx.set_yticklabels([])
#bx.set_xticklabels(['not used','train','validation','test'])
#bx.set_yticks([])
#bx.set_xticks([2,7,12,17])
#for label in bx.get_xticklabels():
# label.set_fontsize(12)
#bx.imshow([[0,0,0,0,0,1,1,1,1,1,2,2,2,2,2,3,3,3,3,3]],aspect=None,interpolation='nearest',cmap=cm.Greys)
canvas.draw()
imdata = StringIO()
fig.savefig(imdata, format='png', dpi=dpi, facecolor=bgcol)
return HttpResponse(imdata.getvalue(), mimetype='image/png')
