def _create_pie(self, cr, uid, ids, report, fields, results, context):
pdf_string = cStringIO.StringIO()
can = canvas.init(fname=pdf_string, format='pdf')
ar = area.T(size=(350, 350),
legend=legend.T(),
x_grid_style=None,
y_grid_style=None)
colors = map(lambda x: fill_style.Plain(bgcolor=x),
misc.choice_colors(len(results)))
if reduce(lambda x, y: x + y, map(lambda x: x[1], results)) == 0.0:
raise UserError(
_("The sum of the data (2nd field) is null.\nWe can't draw a pie chart !"
))
plot = pie_plot.T(data=results,
arc_offsets=[0, 10, 0, 10],
shadow=(2, -2, fill_style.gray50),
label_offset=25,
arrow_style=arrow.a3,
fill_styles=colors)
ar.add_plot(plot)
ar.draw(can)
can.close()
self.obj = external_pdf(pdf_string.getvalue())
self.obj.render()
pdf_string.close()
return True
def __init__(self, data, file_name, title, author=None, format="ps"):
#定义图标格式theme.get_options()中定义众多默认值,也可以指定phonto name和 format
#"d:co:f:", ["format=", "output=", "color=","scale=", "font-family=", "font-size=","line-width=", "debug-level=",
#"title=", "author=", "creation_date=", "creator=", "bbox="]
args = ["--title=%s" % title, "--color=yes", "--font-size=10", "--output=%s.%s" %(file_name, format), "--debug-level=0"]
theme.get_options(argv=args)
#canvas函数，定义canvas名称和格式， 读取theme中定义的环境变量如title
self.can = canvas.init(fname=file_name+"."+format, format=format)
self.data = data
def __init__(self, data, file_name, title, author=None, format="ps"):
#定义图标格式theme.get_options()中定义众多默认值,也可以指定phonto name和 format
#"d:co:f:", ["format=", "output=", "color=","scale=", "font-family=", "font-size=","line-width=", "debug-level=",
#"title=", "author=", "creation_date=", "creator=", "bbox="]
args = [
"--title=%s" % title, "--color=yes", "--font-size=10",
"--output=%s.%s" % (file_name, format), "--debug-level=0"
]
theme.get_options(argv=args)
#canvas函数，定义canvas名称和格式， 读取theme中定义的环境变量如title
self.can = canvas.init(fname=file_name + "." + format, format=format)
self.data = data
def detailchart(self, chartable):
theme.reinitialize()
min_y = 0
max_y = 0
capture = chartable.get('capture')
for sortname, sortfn in self.sorts:
data = capture[sortname]
m = median(data)
if m > max_y:
max_y = m
max_x = max(self.limits)
min_x = min(self.limits)
ipoints = 10.0
x_interval = (max_x - min_x) / ipoints
y_interval = (max_y - min_y) / ipoints
xaxis = axis.X(label='Limit',
tic_interval = x_interval,
format='/4{}%d')
yaxis = axis.Y(label='Seconds',
tic_interval = y_interval,
format='/4{}%0.3f')
ar = area.T(
x_range = (min_x, max_x),
y_range = (min_y, max_y),
x_axis = xaxis,
y_axis = yaxis,
legend = legend.T(),
)
tb = text_box.T(loc=(140,90), text='Rlen\n%s' % chartable['rlen'])
for sortname, sortfn in self.sorts:
data = capture[sortname]
linedata = [ (self.limits[x], data[x]) for x in range(len(data)) ]
ar.add_plot(
line_plot.T(label="%s" % sortname, data=linedata)
)
fd = open('detail-%s-%s.pdf' % (self.dbkey, chartable['rlen']), 'w')
can = canvas.init(fd, 'pdf')
ar.draw(can)
tb.draw(can)
can.close()
def detailchart(self, chartable):
theme.reinitialize()
min_y = 0
max_y = 0
capture = chartable.get('capture')
for sortname, sortfn in self.sorts:
data = capture[sortname]
m = median(data)
if m > max_y:
max_y = m
max_x = max(self.limits)
min_x = min(self.limits)
ipoints = 10.0
x_interval = (max_x - min_x) / ipoints
y_interval = (max_y - min_y) / ipoints
xaxis = axis.X(label='Limit',
tic_interval = x_interval,
format='/4{}%d')
yaxis = axis.Y(label='Seconds',
tic_interval = y_interval,
format='/4{}%0.3f')
ar = area.T(
x_range = (min_x, max_x),
y_range = (min_y, max_y),
x_axis = xaxis,
y_axis = yaxis,
legend = legend.T(),
)
tb = text_box.T(loc=(140,90), text='Rlen\n%s' % chartable['rlen'])
for sortname, sortfn in self.sorts:
data = capture[sortname]
linedata = [ (self.limits[x], data[x]) for x in range(len(data)) ]
ar.add_plot(
line_plot.T(label="%s" % sortname, data=linedata)
)
fd = open('detail-%s-%s.pdf' % (self.dbkey, chartable['rlen']), 'w')
can = canvas.init(fd, 'pdf')
ar.draw(can)
tb.draw(can)
can.close()
def _create_pie(self, cr, uid, ids, report, fields, results, context):
pdf_string = cStringIO.StringIO()
can = canvas.init(fname=pdf_string, format='pdf')
ar = area.T(size=(350,350), legend=legend.T(),
x_grid_style = None, y_grid_style = None)
colors = map(lambda x:fill_style.Plain(bgcolor=x), misc.choice_colors(len(results)))
if reduce(lambda x,y : x+y, map(lambda x : x[1],results)) == 0.0:
raise UserError(_("The sum of the data (2nd field) is null.\nWe can't draw a pie chart !"))
plot = pie_plot.T(data=results, arc_offsets=[0,10,0,10],
shadow = (2, -2, fill_style.gray50),
label_offset = 25,
arrow_style = arrow.a3,
fill_styles=colors)
ar.add_plot(plot)
ar.draw(can)
can.close()
self.obj = external_pdf(pdf_string.getvalue())
self.obj.render()
pdf_string.close()
return True
def create_graph(label_x, label_y, data_x, alldata_y, filename, title,
start_date, end_date, start_y, end_y):
"""
main func
"""
# alter file name (linpng do not seems to like spaces in filenames
filename = filename.replace(' ', '_')
# Graph style
theme.get_options()
theme.use_color = True
theme.default_font_size = 12
theme.default_font_family = "AvantGarde-Book"
theme.reinitialize()
colors = [
color.blue,
color.red,
color.green,
color.magenta,
color.cyan1,
color.orange,
]
can = canvas.init("%s" % filename)
# Draw graph title
newtitle = "/hL/20%s" % title
left = WIDTH / 2 - font.text_width(newtitle) / 2
can.show(left, HEIGHT + DELTA, newtitle)
int_to_date = lambda x: '/a60{}' + time.strftime("%H:%M", time.localtime(x)
)
xaxis = axis.X(format=int_to_date,
label="/20%s" % label_x,
label_offset=(0, -DELTA),
minor_tic_interval=X_MINOR_TICK_INTERVAL,
tic_interval=X_TICK_INTERVAL)
yaxis = axis.Y(
label="/20%s" % label_y,
label_offset=(-DELTA, 0),
minor_tic_interval=(end_y - start_y) / 20,
tic_interval=(end_y - start_y) / 5,
)
ar = area.T(size=(WIDTH, HEIGHT),
x_axis=xaxis,
y_axis=yaxis,
x_grid_style=line_style.gray70_dash3,
x_range=(start_date, end_date),
y_range=(start_y, end_y),
x_grid_interval=X_GRID_INTERVAL,
y_grid_interval=(end_y - start_y) / 5)
i = 0
# Draw a line for each columns
for title, data_y in alldata_y.iteritems():
plot = line_plot.T(label=title,
data=zip(data_x, data_y),
line_style=line_style.T(color=colors[i], width=1))
ar.add_plot(plot)
i += 1
ar.draw()
can.close()
return True
def create_graph(label_x, label_y, data_x, alldata_y, filename, title, start_date, end_date):
# alter file name (linpng do not seems to like spaces in filenames
filename = filename.replace(' ', '_')
# Graph style
theme.get_options()
theme.use_color = True
theme.default_font_size = 12
theme.default_font_family = "AvantGarde-Book"
theme.reinitialize()
colors = [
color.blue,
color.red,
color.green,
color.magenta,
color.cyan1,
color.orange,
]
can = canvas.init("%s"%filename)
# Draw graph title
newtitle = "/hL/20%s"%title
left = WIDTH / 2 - font.text_width(newtitle)/2
can.show(left, HEIGHT + DELTA, newtitle)
zip(data_x)
int_to_date = lambda x: '/a60{}' + time.strftime("%H:%M", time.localtime(x))
xaxis = axis.X(
format = int_to_date,
label = "/20%s" % label_x,
label_offset = (0, -DELTA),
minor_tic_interval = X_MINOR_TICK_INTERVAL,
tic_interval = X_TICK_INTERVAL
)
yaxis = axis.Y(
label = "/20%s" % label_y,
label_offset = (-DELTA, 0),
minor_tic_interval = Y_MINOR_TICK_INTERVAL,
tic_interval = Y_TICK_INTERVAL
)
ar = area.T(
size = (WIDTH, HEIGHT),
x_axis = xaxis,
y_axis = yaxis,
x_grid_style = line_style.gray70_dash3,
x_range = (start_date, end_date),
y_range = (0, Y_MAX),
x_grid_interval = X_GRID_INTERVAL,
y_grid_interval = Y_GRID_INTERVAL
)
i = 0
# Draw a line for each columns
for title, data_y in alldata_y.iteritems():
plot = line_plot.T(
label = title,
data = zip(data_x,data_y),
line_style = line_style.T(
color = colors[i],
width = 1
)
)
ar.add_plot(plot)
i += 1
ar.draw()
can.close()
return True
def comparisonchart(self, sortname1, sortname2):
linedata = []
test_total = 0
test_wrong = 0
for rlendata in self.main:
rlen = rlendata['rlen']
capture = rlendata['capture']
values1 = capture[sortname1]
values2 = capture[sortname2]
doc_ratio = rlen / float(self.numdocs)
cutoff = None
wins = []
#test = sortname1 == 'fwscan' and sortname2 in ('nbest', 'timsort')
#test_fn = fwscan_wins
test = sortname1 == 'nbest' and sortname2 == 'timsort'
test_fn = nbest_ascending_wins
for x in xrange(0, min(len(values1), len(values2))):
t1 = values1[x]
t2 = values2[x]
limit = self.limits[x]
limitratio = limit / float(self.numdocs)
won = t1 < t2
if won:
wins.append(limit)
wrongmsg = "wrong %s? rlen %s, limit %s (%0.5f > %0.5f)%s"
if test:
test_total += 1
curvewin = test_fn(limit, rlen, self.numdocs)
if won and (not curvewin):
extra = ''
if (t1 / t2) < .90: # more than 10% difference
extra = " * (%0.2f)" % (t1/t2)
print wrongmsg % ('curvelose', rlen, limit, t2, t1,
extra)
test_wrong +=1
elif (not won) and curvewin:
extra = ''
if (t2 / t1) < .90: # more than 10% difference
extra = " * (%0.2f)" % (t2/t1)
print wrongmsg % ('curvewin', rlen, limit, t1, t2,
extra)
test_wrong +=1
for limit in wins:
limitratio = limit / float(self.numdocs)
linedata.append((doc_ratio, limitratio))
if test:
if test_total:
test_right = test_total - test_wrong
test_percent = test_right / float(test_total)
print "test percentage %0.2f: (%s wrong out of %s)" % (
test_percent, test_wrong, test_total)
comparename = 'compare-%s-%s-beats-%s' % (self.dbkey,
sortname1, sortname2)
xaxis=axis.X(label='Doc Ratio (rlen//numdocs)',
tic_interval=.1,
format='/4{}%0.2f')
yaxis=axis.Y(label='Limit Ratio (limit//numdocs)',
tic_interval=.1,
format='/4{}%0.2f')
ar = area.T(
x_range = (0, 1),
y_range = (0, 1),
x_axis = xaxis,
y_axis = yaxis,
legend = legend.T(),
)
ar.add_plot(
line_plot.T(label="%s \nbeats \n%s" % (sortname1, sortname2),
data=linedata),
)
tb = text_box.T(loc=(140,90), text='Numdocs\n%s' % self.numdocs)
fd = open('%s.pdf' % comparename, 'w')
can = canvas.init(fd, 'pdf')
ar.draw(can)
tb.draw(can)
can.close()
def queuedPies( queued, title, radius, names, titles, size, availCpus, colours, userColour ):
# re-order the sorted 'queued' so that the labels fit on the pie better
queued = bigSmallOrder( queued )
cpusUsed = 0
doPlot = 0
data = []
colour = []
cnt = 0
plotNum = 0
# limit plots to a maximum, otherwise we could be plotting 10000 cores
# worth of jobs on a 1 core machine ie. too many plots to render and draw
maxPlots = 100
# loop, adding a new 'queued' plot for each bob worth of nodes
for j in range(len(queued)):
cpus, cpusList, username = queued[j]
#print 'cpus, username', cpus, username
cpusUsed += cpus
remainder = 0
if cpusUsed >= availCpus:
# print 'cpusUsed >= totalCpus', cpusUsed, '>=', totalCpus, ', cpusAvailable', availCpus
doPlot = 1
remainder = cpusUsed - availCpus
# print 'remainder', remainder
if j == len(queued)-1:
doPlot = 1
percent = 100.0*float(cpus - remainder)/float(availCpus)
stri = username + ' %d%%' % ( percent + 0.5 )
if len(cpusList) == 1:
stri += ' (1 job)'
else:
stri += ' (%d jobs)' % len(cpusList)
data.append( ( stri, percent ) )
if username in userColour.keys():
c = userColour[username]
else:
# used to round-robin the colours, but with many jobs coming and
# going it's just a vast amount of colour churn - every update
# changes the colours of many running jobs.
# so instead choose one colour per user and stick to it. if users
# don't like their colour then tough luck
if username not in userColourHash.keys():
h = hashlib.md5(username).hexdigest()
h = int(h, 16) % len(colours) # random colour number
userColourHash[username] = int(h) # cast to int from long
c = userColourHash[username]
#print c, len(colour), len(colours)
colour.append( colours[c] )
while doPlot and plotNum < maxPlots:
plotNum += 1
#print 'doing plot, data', data
arcOffsets = []
for i in range(len(data)):
arcOffsets.append( 0 )
tmpFilename = tempfile.mktemp()
n = string.split( tmpFilename, '/' ) # pull off the initial /tmp/
names.append( n[-1] )
titles.append( title )
can = canvas.init( tmpFilename + '.png' )
ar = area.T(size=size, legend=None, x_grid_style = None, y_grid_style = None)
# percentages are always out of a total of 100 for these pies
queuePlot = myPie( data=data, arc_offsets=arcOffsets, fill_styles=colour,
#shadow = (2, -2, fill_style.gray50),
#center=( 800, 500 - plotNum*200 ), # radius=100*(totalQueuedCpus/totalCpus),
label_fill_style = None, label_offset = 25,
radius = radius, # start_angle = 180,
arrow_style = arrow.a0 )
ar.add_plot(queuePlot)
ar.draw(can)
can.close() # flush to file ASAP
cpusUsed = 0
doPlot = 0
data = []
colour = []
doPlot = 0
# handle spillover from one queued pie to another
# allow one persons queued jobs to be >> machine size...
if remainder:
cpus = remainder
cpusUsed += cpus
remainder = 0
if cpusUsed >= availCpus:
doPlot = 1
remainder = cpusUsed - availCpus
percent = 100.0*float(cpus - remainder)/float(availCpus)
stri = username + ' %d%%' % ( percent + 0.5 )
# no job numbers in remainder mode...
#if len(cpusList) == 1:
# stri += ' (1 job)'
#else:
# stri += ' (%d jobs)' % len(cpusList)
data.append( ( stri, percent ) )
colour.append( colours[c] )
if j == len(queued)-1: # last data
doPlot = 1
def plotPie( r, s, q, b, availCpus ):
if not doPie:
return [], [], []
if availCpus <= 0:
availCpus = 1
# return [], [], {}
# availCpus is the total number of online/up cpus.
# NOTE: offlined nodes that are still running jobs can push the total to >100% !
running, totalCpus, totalGpus = r
suspended, totalSuspendedCpus, totalSuspendedGpus = s
queued, totalQueuedCpus = q
blocked, totalBlockedCpus = b
#print 'running', r
#print 'suspended', s
#print 'queued', q
#print 'blocked', b
#sys.exit(1)
theme.use_color = 1
theme.scale_factor = 1
theme.default_font_size = 12
theme.reinitialize()
# filenames in /tmp/ where the png's are written
names = []
# titles of the plots ie. Running, Queued, or Blocked
titles = []
tmpFilename = tempfile.mktemp()
n = string.split( tmpFilename, '/' ) # pull off the initial /tmp/
names.append( n[-1] )
titles.append( 'Running' )
can = canvas.init( tmpFilename + '.png' )
size=( 600, 450 )
ar = area.T(size=size, legend=None, x_grid_style = None, y_grid_style = None)
colours = [ fill_style.red, fill_style.darkseagreen, fill_style.blue,
fill_style.aquamarine1, fill_style.gray70,
fill_style.darkorchid, fill_style.yellow, fill_style.green,
fill_style.gray50, fill_style.goldenrod,
fill_style.brown, fill_style.gray20 ]
pieColours = [ 'red', 'darkseagreen', 'blue', rgbToHex( ( 0.498039, 1.0, 0.831373 ), scaleBy=255 ), # aquamarine1
rgbToHex( ( 0.7, 0.7, 0.7 ), scaleBy=255 ), # gray70
'darkorchid', 'yellow', 'green', rgbToHex( ( 0.5, 0.5, 0.5 ), scaleBy=255 ), # gray50
'goldenrod', 'brown', rgbToHex( ( 0.2, 0.2, 0.2 ), scaleBy=255 ) ] # gray20
# re-order the sorted 'running' so that the labels fit on the pie better
if len(running) > 1:
lastC, lastClist, lastU = running[-1]
if lastU == 'idle': # but keep 'idle' last
running = bigSmallOrder( running[:-1] )
running.append( ( lastC, lastClist, lastU ) )
else:
running = bigSmallOrder( running )
# need to generate colours for both running and suspended pies because we
# can draw those jobs on the node grid. prob wouldn't hurt to extend this to
# all jobs?
all = []
all.extend(running)
all.extend(suspended)
#all.extend(queued)
#all.extend(blocked)
# prescribe the colours for current biggest users. eg. biggest user is always in red
userColour = {} # dict of colours that have been used for specific users
cnt = 0
for cpus, cpusList, username in all:
if username != 'idle':
# username could be both in running and suspended, so only take the first (running)
if username not in userColour.keys():
userColour[username] = cnt
cnt += 1
if cnt == len(colours):
break
# the rest of the colours are hashes of the username
for cpus, cpusList, username in all:
if username not in userColourHash.keys():
h = hashlib.md5(username).hexdigest()
h = int(h, 16) % len(colours) # random colour number
userColourHash[username] = int(h) # cast to int from long
if username not in userColour.keys():
userColour[username] = userColourHash[username]
data = []
arcOffsets = []
colour = []
for cpus, cpusList, username in running:
percent = 100.0*float(cpus)/float(availCpus)
stri = username + ' %d%%' % ( percent + 0.5 )
if username != 'idle':
if len(cpusList) == 1:
stri += ' (1 job)'
else:
stri += ' (%d jobs)' % len(cpusList)
data.append( ( stri, percent ) )
if username != 'idle':
arcOffsets.append( 0 )
colour.append( colours[userColour[username]] )
else:
arcOffsets.append( 20 )
colour.append( fill_style.white )
# offline nodes that are running jobs can make the total of the pie sum to more
# than 100, so use the standard auto-scaling pie chart here.
runPlot = pie_plot.T( data=data, arc_offsets=arcOffsets, fill_styles=colour,
#shadow = (2, -2, fill_style.gray50),
label_fill_style = None, label_offset = 25,
arrow_style = arrow.a0 )
ar.add_plot(runPlot)
ar.draw(can)
can.close() # flush to file ASAP
queuedPies( suspended, 'Suspended', 75, names, titles, size, availCpus, colours, userColour )
queuedPies( queued, 'Queued', 60, names, titles, size, availCpus, colours, userColour )
queuedPies( blocked, 'Blocked/Held', 40, names, titles, size, availCpus, colours, userColour )
# map userColour numbers to colour names
c = {}
for k, v in userColour.iteritems():
c[k] = pieColours[v]
return names, titles, c
def comparisonchart(self, sortname1, sortname2):
linedata = []
test_total = 0
test_wrong = 0
for rlendata in self.main:
rlen = rlendata['rlen']
capture = rlendata['capture']
values1 = capture[sortname1]
values2 = capture[sortname2]
doc_ratio = rlen / float(self.numdocs)
cutoff = None
wins = []
#test = sortname1 == 'fwscan' and sortname2 in ('nbest', 'timsort')
#test_fn = fwscan_wins
test = sortname1 == 'nbest' and sortname2 == 'timsort'
test_fn = nbest_ascending_wins
for x in xrange(0, min(len(values1), len(values2))):
t1 = values1[x]
t2 = values2[x]
limit = self.limits[x]
limitratio = limit / float(self.numdocs)
won = t1 < t2
if won:
wins.append(limit)
wrongmsg = "wrong %s? rlen %s, limit %s (%0.5f > %0.5f)%s"
if test:
test_total += 1
curvewin = test_fn(limit, rlen, self.numdocs)
if won and (not curvewin):
extra = ''
if (t1 / t2) < .90: # more than 10% difference
extra = " * (%0.2f)" % (t1 / t2)
print wrongmsg % ('curvelose', rlen, limit, t2, t1,
extra)
test_wrong += 1
elif (not won) and curvewin:
extra = ''
if (t2 / t1) < .90: # more than 10% difference
extra = " * (%0.2f)" % (t2 / t1)
print wrongmsg % ('curvewin', rlen, limit, t1, t2,
extra)
test_wrong += 1
for limit in wins:
limitratio = limit / float(self.numdocs)
linedata.append((doc_ratio, limitratio))
if test:
if test_total:
test_right = test_total - test_wrong
test_percent = test_right / float(test_total)
print "test percentage %0.2f: (%s wrong out of %s)" % (
test_percent, test_wrong, test_total)
comparename = 'compare-%s-%s-beats-%s' % (self.dbkey, sortname1,
sortname2)
xaxis = axis.X(label='Doc Ratio (rlen//numdocs)',
tic_interval=.1,
format='/4{}%0.2f')
yaxis = axis.Y(label='Limit Ratio (limit//numdocs)',
tic_interval=.1,
format='/4{}%0.2f')
ar = area.T(
x_range=(0, 1),
y_range=(0, 1),
x_axis=xaxis,
y_axis=yaxis,
legend=legend.T(),
)
ar.add_plot(
line_plot.T(label="%s \nbeats \n%s" % (sortname1, sortname2),
data=linedata), )
tb = text_box.T(loc=(140, 90), text='Numdocs\n%s' % self.numdocs)
fd = open('%s.pdf' % comparename, 'w')
can = canvas.init(fd, 'pdf')
ar.draw(can)
tb.draw(can)
can.close()
def _create_bars(self, cr, uid, ids, report, fields, results, context):
env = openerp.api.Environment(cr, uid, context or {})
pdf_string = cStringIO.StringIO()
can = canvas.init(fname=pdf_string, format='pdf')
can.show(80, 380, '/16/H' + report['title'])
process_date = {
'D': lambda x: reduce(lambda xx, yy: xx + '-' + yy,
x.split('-')[1:3]),
'M': lambda x: x.split('-')[1],
'Y': lambda x: x.split('-')[0]
}
ar = area.T(size=(350, 350),
x_axis=axis.X(label=fields[0]['name'], format="/a-30{}%s"),
y_axis=axis.Y(
label=', '.join(map(lambda x: x['name'], fields[1:]))))
idx = 0
date_idx = None
fct = {}
for f in fields:
field_id = (f['field_child3'] and f['field_child3'][0]) or (
f['field_child2'] and f['field_child2'][0]) or (
f['field_child1']
and f['field_child1'][0]) or (f['field_child0']
and f['field_child0'][0])
if field_id:
ttype = env['ir.model.fields'].browse(field_id).ttype
if ttype == 'date':
date_idx = idx
fct[idx] = process_date[report['frequency']]
else:
fct[idx] = lambda x: x
else:
fct[idx] = lambda x: x
idx += 1
# plot are usually displayed year by year
# so we do so if the first field is a date
data_by_year = {}
if date_idx is not None:
for r in results:
key = process_date['Y'](r[date_idx])
if key not in data_by_year:
data_by_year[key] = []
for i in range(len(r)):
r[i] = fct[i](r[i])
data_by_year[key].append(r)
else:
data_by_year[''] = results
nb_bar = len(data_by_year) * (len(fields) - 1)
colors = map(lambda x: fill_style.Plain(bgcolor=x),
misc.choice_colors(nb_bar))
abscissa = {}
for line in data_by_year.keys():
fields_bar = []
# sum data and save it in a list. An item for a fields
for d in data_by_year[line]:
for idx in range(len(fields) - 1):
fields_bar.append({})
if d[0] in fields_bar[idx]:
fields_bar[idx][d[0]] += d[idx + 1]
else:
fields_bar[idx][d[0]] = d[idx + 1]
for idx in range(len(fields) - 1):
data = {}
for k in fields_bar[idx].keys():
if k in data:
data[k] += fields_bar[idx][k]
else:
data[k] = fields_bar[idx][k]
data_cum = []
prev = 0.0
keys = data.keys()
keys.sort()
# cumulate if necessary
for k in keys:
data_cum.append([k, float(data[k]) + float(prev)])
if fields[idx + 1]['cumulate']:
prev += data[k]
idx0 = 0
plot = bar_plot.T(
label=fields[idx + 1]['name'] + ' ' + str(line),
data=data_cum,
cluster=(idx0 * (len(fields) - 1) + idx, nb_bar),
fill_style=colors[idx0 * (len(fields) - 1) + idx])
ar.add_plot(plot)
abscissa.update(fields_bar[idx])
idx0 += 1
abscissa = map(lambda x: [x, None], abscissa)
abscissa.sort()
ar.x_coord = category_coord.T(abscissa, 0)
ar.draw(can)
can.close()
self.obj = external_pdf(pdf_string.getvalue())
self.obj.render()
pdf_string.close()
return True
def _create_bars(self, cr, uid, ids, report, fields, results, context):
env = odoo.api.Environment(cr, uid, context or {})
pdf_string = cStringIO.StringIO()
can = canvas.init(fname=pdf_string, format='pdf')
can.show(80,380,'/16/H'+report['title'])
process_date = {
'D': lambda x: reduce(lambda xx, yy: xx + '-' + yy, x.split('-')[1:3]),
'M': lambda x: x.split('-')[1],
'Y': lambda x: x.split('-')[0]
}
ar = area.T(size=(350,350),
x_axis=axis.X(label = fields[0]['name'], format="/a-30{}%s"),
y_axis=axis.Y(label = ', '.join(map(lambda x : x['name'], fields[1:]))))
idx = 0
date_idx = None
fct = {}
for f in fields:
field_id = (f['field_child3'] and f['field_child3'][0]) or (f['field_child2'] and f['field_child2'][0]) or (f['field_child1'] and f['field_child1'][0]) or (f['field_child0'] and f['field_child0'][0])
if field_id:
ttype = env['ir.model.fields'].browse(field_id).ttype
if ttype == 'date':
date_idx = idx
fct[idx] = process_date[report['frequency']]
else:
fct[idx] = lambda x : x
else:
fct[idx] = lambda x : x
idx+=1
# plot are usually displayed year by year
# so we do so if the first field is a date
data_by_year = {}
if date_idx is not None:
for r in results:
key = process_date['Y'](r[date_idx])
if key not in data_by_year:
data_by_year[key] = []
for i in range(len(r)):
r[i] = fct[i](r[i])
data_by_year[key].append(r)
else:
data_by_year[''] = results
nb_bar = len(data_by_year)*(len(fields)-1)
colors = map(lambda x:fill_style.Plain(bgcolor=x), misc.choice_colors(nb_bar))
abscissa = {}
for line in data_by_year.keys():
fields_bar = []
# sum data and save it in a list. An item for a fields
for d in data_by_year[line]:
for idx in range(len(fields)-1):
fields_bar.append({})
if d[0] in fields_bar[idx]:
fields_bar[idx][d[0]] += d[idx+1]
else:
fields_bar[idx][d[0]] = d[idx+1]
for idx in range(len(fields)-1):
data = {}
for k in fields_bar[idx].keys():
if k in data:
data[k] += fields_bar[idx][k]
else:
data[k] = fields_bar[idx][k]
data_cum = []
prev = 0.0
keys = data.keys()
keys.sort()
# cumulate if necessary
for k in keys:
data_cum.append([k, float(data[k])+float(prev)])
if fields[idx+1]['cumulate']:
prev += data[k]
idx0 = 0
plot = bar_plot.T(label=fields[idx+1]['name']+' '+str(line), data = data_cum, cluster=(idx0*(len(fields)-1)+idx,nb_bar), fill_style=colors[idx0*(len(fields)-1)+idx])
ar.add_plot(plot)
abscissa.update(fields_bar[idx])
idx0 += 1
abscissa = map(lambda x : [x, None], abscissa)
abscissa.sort()
ar.x_coord = category_coord.T(abscissa,0)
ar.draw(can)
can.close()
self.obj = external_pdf(pdf_string.getvalue())
self.obj.render()
pdf_string.close()
return True
def create_graph(label_x, label_y, data_x, alldata_y, filename, title, start_date, end_date, start_y, end_y):
"""
main func
"""
# alter file name (linpng do not seems to like spaces in filenames
filename = filename.replace(" ", "_")
# Graph style
theme.get_options()
theme.use_color = True
theme.default_font_size = 12
theme.default_font_family = "AvantGarde-Book"
theme.reinitialize()
colors = [
color.blue,
color.red,
color.green,
color.magenta,
color.cyan1,
color.orange,
color.darkblue,
color.darkred,
color.darkgreen,
color.darkmagenta,
color.darkcyan,
color.gold,
color.lightblue1,
color.orangered,
color.lightgreen,
color.pink,
color.lightcyan,
color.goldenrod,
color.mistyrose,
color.honeydew,
color.gainsboro,
color.yellow,
color.peachpuff,
color.turquoise,
color.chartreuse1,
color.pink,
color.brown,
color.blue,
color.red,
color.green,
color.magenta,
color.cyan1,
color.orange,
color.darkblue,
color.darkred,
color.darkgreen,
color.darkmagenta,
color.darkcyan,
color.gold,
color.lightblue1,
color.orangered,
color.lightgreen,
color.pink,
color.lightcyan,
color.goldenrod,
color.mistyrose,
color.honeydew,
color.gainsboro,
color.yellow,
color.peachpuff,
color.turquoise,
color.chartreuse1,
color.pink,
color.brown,
]
can = canvas.init("%s" % filename)
# Draw graph title
newtitle = "/hL/20%s" % title
left = WIDTH / 2 - font.text_width(newtitle) / 2
can.show(left, HEIGHT + DELTA, newtitle)
int_to_date = lambda x: "/a60{}" + time.strftime("%H:%M", time.localtime(x))
xaxis = axis.X(
format=int_to_date,
label="/20%s" % label_x,
label_offset=(0, -DELTA),
minor_tic_interval=X_MINOR_TICK_INTERVAL,
tic_interval=X_TICK_INTERVAL,
)
yaxis = axis.Y(
label="/20%s" % label_y,
label_offset=(-DELTA, 0),
minor_tic_interval=(end_y - start_y) / 20,
tic_interval=(end_y - start_y) / 5,
)
ar = area.T(
size=(WIDTH, HEIGHT),
x_axis=xaxis,
y_axis=yaxis,
x_grid_style=line_style.gray70_dash3,
x_range=(start_date, end_date),
y_range=(start_y, end_y),
x_grid_interval=X_GRID_INTERVAL,
y_grid_interval=(end_y - start_y) / 5,
)
i = 0
# Draw a line for each columns
for title, data_y in alldata_y.iteritems():
plot = line_plot.T(label=title, data=zip(data_x, data_y), line_style=line_style.T(color=colors[i], width=1))
ar.add_plot(plot)
i += 1
ar.draw()
can.close()
return True
