def daily_timseries(ts):
fig = Figure((2.56, 2.56), 300)
canvas = FigureCanvas(fig)
ax = fig.add_axes((0, 0, 1, 1))
ax.set_ylim([0, 500])
preferspan = ax.axhspan(SAFE[0],
SAFE[1],
facecolor='g',
alpha=0.2,
edgecolor='#003333',
linewidth=1)
# XXX: gets a list of days.
timestamps = glucose.get_days(ts.time)
halfday = dates.relativedelta(hours=12)
soleday = dates.relativedelta(days=1)
xmin, xmax = (timestamps[0], timestamps[1] + soleday)
ax.set_xlim([xmin, xmax])
#fig.autofmt_xdate( )
#plot_glucose_stems( ax, ts )
plt.setp(ax.get_xminorticklabels(), visible=False)
plt.setp(ax.get_xmajorticklabels(), visible=False)
plt.setp(ax.get_ymajorticklabels(), visible=False)
plt.setp(ax.get_yminorticklabels(), visible=False)
ax.grid(True)
xmin, xmax = ax.get_xlim()
log.info(pformat({
'xlim': [dates.num2date(xmin),
dates.num2date(xmax)],
}))
return canvas
def tiled_axis( ts, filename=None ):
fig = Figure( ( 2.56 * 4, 2.56 * 4), 300 )
canvas = FigureCanvas(fig)
#ax = fig.add_subplot(111)
grid = ImageGrid(fig, 111, # similar to subplot(111)
nrows_ncols = (3, 1),
axes_pad = 0.5,
add_all=True,
label_mode = "L",
)
# pad half a day so that major ticks show up in the middle, not on the edges
delta = dates.relativedelta( days=2, hours=12 )
# XXX: gets a list of days.
timestamps = glucose.get_days( ts.time )
xmin, xmax = ( timestamps[ 0 ] - delta,
timestamps[ -1 ] + delta )
fig.autofmt_xdate( )
def make_plot( ax, limit ):
preferspan = ax.axhspan( SAFE[0], SAFE[1],
facecolor='g', alpha=0.2,
edgecolor = '#003333',
linewidth=1
)
def draw_title( ax, limit ):
ax.set_title('glucose history')
#ax.set_ylabel('glucose mm/dL')
return canvas
def grid( data ):
fig = Figure( ( 2.56, 2.56 ), 300 )
canvas = FigureCanvas(fig)
d = data.time[ 0 ]
day = glucose.glucose_for_day( data, d )
days = glucose.get_days( data.time )
name = str( d )
ax = fig.add_axes((.5,0,1,1))
xmin, xmax = days[ 0 ], days[ -1 ]
ax.set_xlim( [ xmin, xmax ] )
ax.grid(True)
safe_span(ax)
one = ax.text( .50, .50, name,
horizontalalignment='center',
verticalalignment='center',
transform = ax.transAxes )
one.remove( )
log.info( pformat( one ) )
ax.text( .60, .60, name + "two",
horizontalalignment='center',
verticalalignment='center',
transform = ax.transAxes )
set_daily_locators( ax )
config_yaxis( ax )
return canvas
def draw_tile(name):
fig = Figure((2.56, 2.56), 300)
canvas = FigureCanvas(fig)
ax = fig.add_axes((0, 0, 1, 1))
SAFE = (70, 140)
ax.set_ylim([0, 500])
preferspan = ax.axhspan(SAFE[0],
SAFE[1],
facecolor='g',
alpha=0.2,
edgecolor='#003333',
linewidth=1)
# XXX: gets a list of days.
timestamps = datetime.date.today()
halfday = dates.relativedelta(hours=12)
soleday = dates.relativedelta(days=1)
xmin, xmax = (timestamps, timestamps + soleday)
ax.set_xlim([xmin, xmax])
#fig.autofmt_xdate( )
#plot_glucose_stems( ax, ts )
plt.setp(ax.get_xminorticklabels(), visible=False)
plt.setp(ax.get_xmajorticklabels(), visible=False)
plt.setp(ax.get_ymajorticklabels(), visible=False)
plt.setp(ax.get_yminorticklabels(), visible=False)
ax.text(.50,
.50,
name,
horizontalalignment='center',
verticalalignment='center',
transform=ax.transAxes)
ax.grid(True)
fig.savefig(name, transparent=True)
def x_axis_panel(xlim=(0, 1000), numticks=5):
fig = Figure((2.56, 2.56), 300)
ax = fig.add_axes((0, 0, 1, 1))
ax.grid(True)
config_yaxis(ax)
config_xaxis(ax, numticks)
safe_span(ax)
canvas = FigureCanvas(fig)
return get_image_buffer(canvas)
def __init__(self, ghgw, hspace=0.35, wspace=0.2, rwidth=3.0, rheight=2.8):
self.gh = ghgw[0]
self.gw = ghgw[1]
# Setup the figure looking nice
self.fig = matplotlib.figure.Figure(
figsize=(rwidth * self.gw, rheight * self.gh),
subplotpars=matplotlib.figure.SubplotParams(hspace=hspace,
wspace=wspace))
self.canvas = FigureCanvas(self.fig)
def debug(msg):
fig = Figure((2.56, 2.56), 300, linewidth=.5)
canvas = FigureCanvas(fig)
ax = fig.add_axes((0, 0, 1, 1))
config_yaxis(ax, formatter=False)
config_xaxis(ax, 5)
ax.grid(True)
ax.text(0, 1, msg, verticalalignment='top', transform=ax.transAxes)
return get_image_buffer(canvas)
def dot(color='r'):
fig = Figure((.12, .12), 300)
canvas = FigureCanvas(fig)
ax = fig.add_axes((0, 0, 1, 1), frameon=False)
ax.set_ylim([0, 1])
ax.set_xlim([0, 1])
ax.plot(.5, .5, 'ro')
ax.grid(False)
ax.tick_params('both', width=0, length=0)
return get_image_buffer(canvas)
def giant_timeseries(ts):
fig = Figure((20.3, 3.5), 300)
canvas = FigureCanvas(fig)
ax = fig.add_subplot(111)
preferspan = ax.axhspan(SAFE[0],
SAFE[1],
facecolor='g',
alpha=0.35,
edgecolor='#003333',
linewidth=1)
# visualize glucose using stems
# XXX: gets a list of days.
timestamps = glucose.get_days(ts.time)
delta = dates.relativedelta(days=1, hours=12)
oneday = dates.relativedelta(days=1)
xmin, xmax = (timestamps[0], timestamps[-1])
ax.set_xlim([xmin, xmax])
markers, stems, baselines = ax.stem(ts.time, ts.value, linefmt='b:')
plt.setp(markers, color='red', linewidth=.5, marker='o')
plt.setp(baselines, marker='None')
fig.autofmt_xdate()
ax.set_title('glucose history')
ax.grid(True)
ax.set_xlabel('time')
majorLocator = dates.DayLocator()
majorFormatter = dates.AutoDateFormatter(majorLocator)
minorLocator = dates.HourLocator(interval=6)
minorFormatter = dates.AutoDateFormatter(minorLocator)
ax.xaxis.set_major_locator(majorLocator)
ax.xaxis.set_major_formatter(majorFormatter)
ax.xaxis.set_minor_locator(minorLocator)
ax.xaxis.set_minor_formatter(minorFormatter)
labels = ax.get_xminorticklabels()
plt.setp(labels, rotation=30, fontsize='small')
plt.setp(ax.get_xmajorticklabels(), rotation=30, fontsize='medium')
xmin, xmax = ax.get_xlim()
log.info(pformat({
'xlim': [dates.num2date(xmin),
dates.num2date(xmax)],
}))
ax.set_ylabel('glucose mm/dL')
return canvas
def y_axis_panel( ): """Just get the yaxis""" """TODO: more sensitive ticks?""" fig = Figure( ( .64, 5.12 ), 300 ) canvas = FigureCanvas(fig) ax = fig.add_axes((.9,1./3.,1.,.5)) ax.grid(True) config_yaxis( ax ) safe_span(ax) ax.xaxis.set_visible(False) return canvas
def y_axis_panel(size=(.64, 3.84)):
"""Just get the yaxis"""
"""TODO: more sensitive ticks?"""
fig = Figure(size, 300)
canvas = FigureCanvas(fig)
ax = fig.add_axes((.9, 1 / 6., 1., 2 / 3.0))
ax.grid(True)
config_yaxis(ax)
safe_span(ax)
ax.xaxis.set_visible(False)
return get_image_buffer(canvas)
def jpg(self):
"""
Returns a StringIO JPG plot for the sensor
"""
fig = self.matplot()
canvas = FigureCanvas(fig)
try:
jpg_output = StringIO()
except NameError:
jpg_output = BytesIO()
canvas.print_jpg(jpg_output)
return jpg_output.getvalue()
def exp( data ):
fig = Figure( ( 2.56, 2.56 ), 300 )
canvas = FigureCanvas(fig)
d = data.time[ 0 ]
day = glucose.glucose_for_day( data, d )
name = str( d )
ax = fig.add_axes((0,0,1,1))
ax.text( .50, .50, name,
horizontalalignment='center',
verticalalignment='center',
transform = ax.transAxes )
ax.grid(True)
return canvas
def png(self):
"""
Returns a StringIO PNG plot for the sensor
"""
fig = self.matplot()
canvas = FigureCanvas(fig)
try:
png_output = StringIO()
except NameError:
png_output = BytesIO()
canvas.print_png(png_output)
return png_output.getvalue()
def daily_axis( ts ): # http://matplotlib.sourceforge.net/mpl_toolkits/axes_grid/users/overview.html fig = Figure( ( 2.56, 2.56 ), 300 ) canvas = FigureCanvas(fig) ax = fig.add_subplot(111) safe_span(ax) timestamps = glucose.get_days( ts.time ) xmin, xmax = timestamps[ 0 ], timestamps[ -1 ] ax.set_xlim( [ xmin, xmax ] ) ax.set_ylim( [ ts.value.min( ) *.85 , 600 ] ) log.info( pformat( timestamps ) ) #fig.autofmt_xdate( ) ax.grid(True) return canvas
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 daily_axis(ts):
# http://matplotlib.sourceforge.net/mpl_toolkits/axes_grid/users/overview.html
fig = Figure((2.56, 2.56), 300)
canvas = FigureCanvas(fig)
ax = fig.add_subplot(111)
preferspan = ax.axhspan(SAFE[0],
SAFE[1],
facecolor='g',
alpha=0.2,
edgecolor='#003333',
linewidth=1)
timestamps = glucose.get_days(ts.time)
xmin, xmax = timestamps[0], timestamps[-1]
ax.set_xlim([xmin, xmax])
ax.set_ylim([ts.value.min() * .85, 600])
log.info(pformat(timestamps))
#fig.autofmt_xdate( )
ax.grid(True)
return canvas
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')
signal= cplx_randn(SIGLEN)
sc_half_seq= cplx_randn(SCLEN)
sc_seq= np.concatenate((sc_half_seq[-CPLEN:], sc_half_seq, sc_half_seq))
start= (len(signal) - len(sc_seq)) // 2
end= start + len(sc_seq)
signal[start:end]+= sc_seq
for (fqname, fqoff) in (('nooff', 0), ('fqoff', 0.01)):
df= np.exp(1j * np.linspace(0, fqoff * SIGLEN, len(signal)))
fqadj= signal * df
detection= fqadj[SCLEN:] * fqadj[:-SCLEN].conj()
detection= np.convolve(detection, np.ones(SCLEN) / SCLEN, mode='valid')
for (name, src) in (('abs', abs(detection)), ('arg', np.angle(detection))):
fig= Figure()
canvas= FigureCanvas(fig)
ax= fig.add_subplot('111')
sl= len(src)
ax.plot(
np.linspace(-sl/2, sl/2, sl),
src, 'b'
)
canvas.print_pdf('sc_detector_output_{}_{}.pdf'.format(fqname, name))
def tiled_axis(ts, filename=None):
fig = Figure((2.56 * 4, 2.56 * 4), 300)
canvas = FigureCanvas(fig)
#ax = fig.add_subplot(111)
grid = ImageGrid(
fig,
111, # similar to subplot(111)
nrows_ncols=(3, 1),
axes_pad=0.5,
add_all=True,
label_mode="L",
)
# pad half a day so that major ticks show up in the middle, not on the edges
delta = dates.relativedelta(days=2, hours=12)
# XXX: gets a list of days.
timestamps = glucose.get_days(ts.time)
xmin, xmax = (timestamps[0] - delta, timestamps[-1] + delta)
fig.autofmt_xdate()
def make_plot(ax, limit):
preferspan = ax.axhspan(SAFE[0],
SAFE[1],
facecolor='g',
alpha=0.2,
edgecolor='#003333',
linewidth=1)
def draw_glucose(ax, limit):
xmin, xmax = limit
# visualize glucose using stems
ax.set_xlim([xmin, xmax])
markers, stems, baselines = ax.stem(ts.time, ts.value, linefmt='b:')
plt.setp(markers, color='red', linewidth=.5, marker='o')
plt.setp(baselines, marker='None')
def draw_title(ax, limit):
ax.set_title('glucose history')
def get_axis(ax, limit):
xmin, xmax = limit
ax.set_xlim([xmin, xmax])
ax.grid(True)
#ax.set_ylim( [ ts.value.min( ) *.85 , 600 ] )
#ax.set_xlabel('time')
majorLocator = dates.DayLocator()
majorFormatter = dates.AutoDateFormatter(majorLocator)
minorLocator = dates.HourLocator(interval=6)
minorFormatter = dates.AutoDateFormatter(minorLocator)
#ax.xaxis.set_major_locator(majorLocator)
#ax.xaxis.set_major_formatter(majorFormatter)
ax.xaxis.set_minor_locator(minorLocator)
ax.xaxis.set_minor_formatter(minorFormatter)
labels = ax.get_xminorticklabels()
plt.setp(labels, rotation=30, fontsize='small')
plt.setp(ax.get_xmajorticklabels(), rotation=30, fontsize='medium')
xmin, xmax = ax.get_xlim()
log.info(
pformat({
'xlim': [dates.num2date(xmin),
dates.num2date(xmax)],
'xticks': dates.num2date(ax.get_xticks()),
}))
for i, day in enumerate(timestamps):
ax = grid[i]
get_axis(ax, [day, day + delta])
name = '%s-%d.png' % (day.isoformat(), i)
#fig.savefig( name )
canvas.print_figure(name)
# fig.clf()
#make_plot( ax,
#ax.set_ylabel('glucose mm/dL')
return canvas
def x_axis_panel( ): fig = Figure( ( 2.56, 2.56 ), 300 ) canvas = FigureCanvas(fig)