def partfunction(self, data):
if data.first:
data.first = 0
min = data.min
max = data.max
if self.extendtick is not None and len(
self.ticklist) > self.extendtick:
min, max = self.extendminmax(min, max,
self.ticklist[self.extendtick],
data.extendmin, data.extendmax)
if self.extendlabel is not None and len(
self.labellist) > self.extendlabel:
min, max = self.extendminmax(min, max,
self.labellist[self.extendlabel],
data.extendmin, data.extendmax)
ticks = []
for i in range(len(self.ticklist)):
ticks = tick.mergeticklists(
ticks,
self.getticks(min, max, self.ticklist[i], ticklevel=i))
for i in range(len(self.labellist)):
ticks = tick.mergeticklists(
ticks,
self.getticks(min, max, self.labellist[i], labellevel=i))
return ticks
return None
def partfunction(self, data):
if data.first:
data.first = 0
min = data.min
max = data.max
if self.extendtick is not None and len(self.ticklist) > self.extendtick:
min, max = self.extendminmax(min, max, self.ticklist[self.extendtick], data.extendmin, data.extendmax)
if self.extendlabel is not None and len(self.labellist) > self.extendlabel:
min, max = self.extendminmax(min, max, self.labellist[self.extendlabel], data.extendmin, data.extendmax)
ticks = []
for i in range(len(self.ticklist)):
ticks = tick.mergeticklists(ticks, self.getticks(min, max, self.ticklist[i], ticklevel=i))
for i in range(len(self.labellist)):
ticks = tick.mergeticklists(ticks, self.getticks(min, max, self.labellist[i], labellevel=i))
return ticks
return None
def getticks(self, min, max, preexp, ticklevel=None, labellevel=None):
ticks = []
minimin = 0
maximax = 0
for f in preexp.pres:
thisticks = []
imin = int(math.ceil(math.log(min / float(f)) /
math.log(preexp.exp) - 0.5 * self.epsilon))
imax = int(math.floor(math.log(max / float(f)) /
math.log(preexp.exp) + 0.5 * self.epsilon))
for i in range(imin, imax + 1):
pos = f * tick.rational((preexp.exp, 1), power=i)
thisticks.append(tick.tick((pos.num, pos.denom), ticklevel = ticklevel, labellevel = labellevel))
ticks = tick.mergeticklists(ticks, thisticks)
return ticks
def _create(self, data, positioner, graphtexrunner, parter, rater, errorname):
errorname = " for axis %s" % errorname
if data.min is None or data.max is None:
raise RuntimeError("incomplete axis range%s" % errorname)
if data.max == data.min:
if self.fallbackrange is not None:
try:
data.min, data.max = data.min - 0.5*self.fallbackrange, data.min + 0.5*self.fallbackrange
except TypeError:
data.min, data.max = self.fallbackrange[0], self.fallbackrange[1]
else:
raise RuntimeError("zero axis range%s" % errorname)
def layout(data):
self.adjustaxis(data, data.ticks, graphtexrunner, errorname)
self.texter.labels(data.ticks)
if self.divisor:
for t in data.ticks:
t *= tick.rational(self.divisor)
canvas = painter.axiscanvas(self.painter, graphtexrunner)
if self.painter is not None:
self.painter.paint(canvas, data, self, positioner)
return canvas
if parter is None:
data.ticks = self.manualticks
return layout(data)
# a variant is a data copy with local modifications to test several partitions
class variant:
def __init__(self, data, **kwargs):
self.data = data
for key, value in kwargs.items():
setattr(self, key, value)
def __getattr__(self, key):
return getattr(data, key)
def __cmp__(self, other):
# we can also sort variants by their rate
return cmp(self.rate, other.rate)
# build a list of variants
bestrate = None
if self.divisor is not None:
if data.min is not None:
data_min_divided = data.min/self.divisor
else:
data_min_divided = None
if data.max is not None:
data_max_divided = data.max/self.divisor
else:
data_max_divided = None
partfunctions = parter.partfunctions(data_min_divided, data_max_divided,
self.min is None, self.max is None)
else:
partfunctions = parter.partfunctions(data.min, data.max,
self.min is None, self.max is None)
variants = []
for partfunction in partfunctions:
worse = 0
while worse < self.maxworse:
worse += 1
ticks = partfunction()
if ticks is None:
break
ticks = [t for t in tick.mergeticklists(self.manualticks, ticks, mergeequal=0)
if t.ticklevel is not None or t.labellevel is not None]
if ticks:
rate = rater.rateticks(self, ticks, self.density)
if self.reverse:
rate += rater.raterange(self.convert(data, ticks[0]) -
self.convert(data, ticks[-1]), 1)
else:
rate += rater.raterange(self.convert(data, ticks[-1]) -
self.convert(data, ticks[0]), 1)
if bestrate is None or rate < bestrate:
bestrate = rate
worse = 0
variants.append(variant(data, rate=rate, ticks=ticks))
if not variants:
raise RuntimeError("no axis partitioning found%s" % errorname)
if len(variants) == 1 or self.painter is None:
# When the painter is None, we could sort the variants here by their rating.
# However, we didn't did this so far and there is no real reason to change that.
data.ticks = variants[0].ticks
return layout(data)
# build the layout for best variants
for variant in variants:
variant.storedcanvas = None
variants.sort()
while not variants[0].storedcanvas:
variants[0].storedcanvas = layout(variants[0])
ratelayout = rater.ratelayout(variants[0].storedcanvas, self.density)
if ratelayout is None:
del variants[0]
if not variants:
raise NoValidPartitionError("no valid axis partitioning found%s" % errorname)
else:
variants[0].rate += ratelayout
variants.sort()
self.adjustaxis(data, variants[0].ticks, graphtexrunner, errorname)
data.ticks = variants[0].ticks
return variants[0].storedcanvas
def _create(self, data, positioner, graphtextengine, parter, rater,
errorname):
errorname = " for axis %s" % errorname
if data.min is None or data.max is None:
raise RuntimeError("incomplete axis range%s" % errorname)
if data.max == data.min:
if self.fallbackrange is not None:
try:
data.min, data.max = data.min - 0.5 * self.fallbackrange, data.min + 0.5 * self.fallbackrange
except TypeError:
data.min, data.max = self.fallbackrange[
0], self.fallbackrange[1]
else:
raise RuntimeError("zero axis range%s" % errorname)
if self.divisor is not None:
rational_divisor = tick.rational(self.divisor)
convert_tick = lambda x: float(x) * self.divisor
else:
convert_tick = lambda x: x
def layout(data):
if data.ticks:
self.adjustaxis(data, [
convert_tick(data.ticks[0]),
convert_tick(data.ticks[-1])
], graphtextengine, errorname)
self.texter.labels(data.ticks)
if self.divisor:
for t in data.ticks:
t *= rational_divisor
canvas = painter.axiscanvas(self.painter, graphtextengine)
if self.painter is not None:
self.painter.paint(canvas, data, self, positioner)
return canvas
if parter is None:
data.ticks = self.manualticks
return layout(data)
# a variant is a data copy with local modifications to test several partitions
@functools.total_ordering
class variant:
def __init__(self, data, **kwargs):
self.data = data
for key, value in list(kwargs.items()):
setattr(self, key, value)
def __getattr__(self, key):
return getattr(data, key)
def __lt__(self, other):
# we can also sort variants by their rate
return self.rate < other.rate
def __eq__(self, other):
# we can also sort variants by their rate
return self.rate == other.rate
# build a list of variants
bestrate = None
if self.divisor is not None:
if data.min is not None:
data_min_divided = data.min / self.divisor
else:
data_min_divided = None
if data.max is not None:
data_max_divided = data.max / self.divisor
else:
data_max_divided = None
partfunctions = parter.partfunctions(data_min_divided,
data_max_divided,
self.min is None,
self.max is None)
else:
partfunctions = parter.partfunctions(data.min, data.max,
self.min is None,
self.max is None)
variants = []
for partfunction in partfunctions:
worse = 0
while worse < self.maxworse:
worse += 1
ticks = partfunction()
if ticks is None:
break
ticks = tick.mergeticklists(self.manualticks,
ticks,
mergeequal=0)
if ticks:
rate = rater.rateticks(self, ticks, self.density)
if rate is not None:
if self.reverse:
rate += rater.raterange(
self.convert(data, convert_tick(ticks[0])) -
self.convert(data, convert_tick(ticks[-1])), 1)
else:
rate += rater.raterange(
self.convert(data, convert_tick(ticks[-1])) -
self.convert(data, convert_tick(ticks[0])), 1)
if bestrate is None or rate < bestrate:
bestrate = rate
worse = 0
variants.append(variant(data, rate=rate, ticks=ticks))
if not variants:
raise RuntimeError("no axis partitioning found%s" % errorname)
if len(variants) == 1 or self.painter is None:
# When the painter is None, we could sort the variants here by their rating.
# However, we didn't did this so far and there is no real reason to change that.
data.ticks = variants[0].ticks
return layout(data)
# build the layout for best variants
for variant in variants:
variant.storedcanvas = None
variants.sort()
while not variants[0].storedcanvas:
variants[0].storedcanvas = layout(variants[0])
ratelayout = rater.ratelayout(variants[0].storedcanvas,
self.density)
if ratelayout is None:
del variants[0]
if not variants:
raise NoValidPartitionError(
"no valid axis partitioning found%s" % errorname)
else:
variants[0].rate += ratelayout
variants.sort()
self.adjustaxis(data, variants[0].ticks, graphtextengine, errorname)
data.ticks = variants[0].ticks
return variants[0].storedcanvas
def _create(self, data, positioner, graphtexrunner, parter, rater,
errorname):
errorname = " for axis %s" % errorname
if data.min is None or data.max is None:
raise RuntimeError("incomplete axis range%s" % errorname)
def layout(data):
self.adjustaxis(data, data.ticks, graphtexrunner, errorname)
self.texter.labels(data.ticks)
if self.divisor:
for t in data.ticks:
t *= tick.rational(self.divisor)
canvas = painter.axiscanvas(self.painter, graphtexrunner)
if self.painter is not None:
self.painter.paint(canvas, data, self, positioner)
return canvas
if parter is None:
data.ticks = self.manualticks
return layout(data)
# a variant is a data copy with local modifications to test several partitions
class variant:
def __init__(self, data, **kwargs):
self.data = data
for key, value in kwargs.items():
setattr(self, key, value)
def __getattr__(self, key):
return getattr(data, key)
def __cmp__(self, other):
# we can also sort variants by their rate
return cmp(self.rate, other.rate)
# build a list of variants
bestrate = None
if self.divisor is not None:
partfunctions = parter.partfunctions(data.min / self.divisor,
data.max / self.divisor,
self.min is None,
self.max is None)
else:
partfunctions = parter.partfunctions(data.min, data.max,
self.min is None,
self.max is None)
variants = []
for partfunction in partfunctions:
worse = 0
while worse < self.maxworse:
worse += 1
ticks = partfunction()
if ticks is None:
break
ticks = tick.mergeticklists(self.manualticks,
ticks,
mergeequal=0)
if ticks:
rate = rater.rateticks(self, ticks, self.density)
if self.reverse:
rate += rater.raterange(
self.convert(data, ticks[0]) -
self.convert(data, ticks[-1]), 1)
else:
rate += rater.raterange(
self.convert(data, ticks[-1]) -
self.convert(data, ticks[0]), 1)
if bestrate is None or rate < bestrate:
bestrate = rate
worse = 0
variants.append(variant(data, rate=rate, ticks=ticks))
if not variants:
raise RuntimeError("no axis partitioning found%s" % errorname)
if len(variants) == 1 or self.painter is None:
# When the painter is None, we could sort the variants here by their rating.
# However, we didn't did this so far and there is no real reason to change that.
data.ticks = variants[0].ticks
return layout(data)
# build the layout for best variants
for variant in variants:
variant.storedcanvas = None
variants.sort()
while not variants[0].storedcanvas:
variants[0].storedcanvas = layout(variants[0])
ratelayout = rater.ratelayout(variants[0].storedcanvas,
self.density)
if ratelayout is None:
del variants[0]
if not variants:
raise NoValidPartitionError(
"no valid axis partitioning found%s" % errorname)
else:
variants[0].rate += ratelayout
variants.sort()
self.adjustaxis(data, variants[0].ticks, graphtexrunner, errorname)
data.ticks = variants[0].ticks
return variants[0].storedcanvas