def GetData(self, name):
"""Return the data with the name.
For a 1D dataset, returns a tuple (None if not defined)
(data, serr, nerr, perr)
For a 2D dataset, returns
(data, xrange, yrange)
For a text dataset, return a list of text
For a date dataset, return a list of python datetime objects
Return copies, so that the original data can't be indirectly modified
"""
d = self.document.getData(name)
if d.displaytype == 'text':
return d.data[:]
elif d.displaytype == 'date':
return [utils.floatToDateTime(x) for x in d.data]
elif d.dimensions == 2:
return (d.data.copy(), d.xrange, d.yrange)
else:
data = serr = nerr = perr = None
if d.data is not None:
data = d.data.copy()
if d.serr is not None:
serr = d.serr.copy()
if d.nerr is not None:
nerr = d.nerr.copy()
if d.perr is not None:
perr = d.perr.copy()
return (data, serr, nerr, perr)
def GetData(self, name):
"""Return the data with the name.
For a 1D dataset, returns a tuple (None if not defined)
(data, serr, nerr, perr)
For a 2D dataset, returns
(data, xrange, yrange)
For a text dataset, return a list of text
For a date dataset, return a list of python datetime objects
Return copies, so that the original data can't be indirectly modified
"""
d = self.document.getData(name)
if d.displaytype == 'text':
return d.data[:]
elif d.displaytype == 'date':
return [utils.floatToDateTime(x) for x in d.data]
elif d.dimensions == 2:
return (d.data.copy(), d.xrange, d.yrange)
else:
data = serr = nerr = perr = None
if d.data is not None:
data = d.data.copy()
if d.serr is not None:
serr = d.serr.copy()
if d.nerr is not None:
nerr = d.nerr.copy()
if d.perr is not None:
perr = d.perr.copy()
return (data, serr, nerr, perr)
def bestTickFinder(self, minval, maxval, numticks, extendbounds,
intervals, intervals_sec):
"""Try to find best choice of numticks ticks between minval and maxval
intervals is an array similar to self.intervals
intervals_sec is an array similar to self.intervals_sec
Returns a tuple (minval, maxval, estimatedsize, ticks, textformat)"""
delta = maxval - minval
# iterate over different intervals and find one closest to what we want
estimated = delta / intervals_sec
tick1 = max(estimated.searchsorted(numticks)-1, 0)
tick2 = min(tick1+1, len(estimated)-1)
del1 = abs(estimated[tick1] - numticks)
del2 = abs(estimated[tick2] - numticks)
if del1 < del2:
best = tick1
else:
best = tick2
besttt, format = intervals[best]
mindate = utils.floatToDateTime(minval)
maxdate = utils.floatToDateTime(maxval)
# round min and max to nearest
minround = utils.tupleToDateTime(utils.roundDownToTimeTuple(mindate, besttt))
maxround = utils.tupleToDateTime(utils.roundDownToTimeTuple(maxdate, besttt))
if minround == mindate:
mintick = minround
else:
# rounded down, so move on to next tick
mintick = utils.addTimeTupleToDateTime(minround, besttt)
maxtick = maxround
# extend bounds if requested
deltamin = utils.datetimeToFloat(mindate)-utils.datetimeToFloat(mintick)
if extendbounds and (deltamin != 0. and deltamin < delta*0.15):
mindate = utils.addTimeTupleToDateTime(minround,
[-x for x in besttt])
mintick = mindate
deltamax = utils.datetimeToFloat(maxdate)-utils.datetimeToFloat(maxtick)
if extendbounds and (deltamax != 0. and deltamax < delta*0.15):
maxdate = utils.addTimeTupleToDateTime(maxtick, besttt)
maxtick = maxdate
# make ticks
ticks = []
dt = mintick
while dt <= maxtick:
ticks.append( utils.datetimeToFloat(dt))
dt = utils.addTimeTupleToDateTime(dt, besttt)
return ( utils.datetimeToFloat(mindate),
utils.datetimeToFloat(maxdate),
intervals_sec[best],
N.array(ticks), format )
def bestTickFinder(self, minval, maxval, numticks, extendmin, extendmax,
intervals, intervals_sec):
"""Try to find best choice of numticks ticks between minval and maxval
intervals is an array similar to self.intervals
intervals_sec is an array similar to self.intervals_sec
Returns a tuple (minval, maxval, estimatedsize, ticks, textformat)"""
delta = maxval - minval
# iterate over different intervals and find one closest to what we want
estimated = delta / intervals_sec
tick1 = max(estimated.searchsorted(numticks) - 1, 0)
tick2 = min(tick1 + 1, len(estimated) - 1)
del1 = abs(estimated[tick1] - numticks)
del2 = abs(estimated[tick2] - numticks)
if del1 < del2:
best = tick1
else:
best = tick2
besttt, format = intervals[best]
mindate = utils.floatToDateTime(minval)
maxdate = utils.floatToDateTime(maxval)
# round min and max to nearest
minround = utils.tupleToDateTime(
utils.roundDownToTimeTuple(mindate, besttt))
maxround = utils.tupleToDateTime(
utils.roundDownToTimeTuple(maxdate, besttt))
if minround == mindate:
mintick = minround
else:
# rounded down, so move on to next tick
mintick = utils.addTimeTupleToDateTime(minround, besttt)
maxtick = maxround
# extend bounds if requested
deltamin = utils.datetimeToFloat(mindate) - utils.datetimeToFloat(
mintick)
if extendmin and (deltamin != 0. and deltamin < delta * 0.15):
mindate = utils.addTimeTupleToDateTime(minround,
[-x for x in besttt])
mintick = mindate
deltamax = utils.datetimeToFloat(maxdate) - utils.datetimeToFloat(
maxtick)
if extendmax and (deltamax != 0. and deltamax < delta * 0.15):
maxdate = utils.addTimeTupleToDateTime(maxtick, besttt)
maxtick = maxdate
# make ticks
ticks = []
dt = mintick
while dt <= maxtick:
ticks.append(utils.datetimeToFloat(dt))
dt = utils.addTimeTupleToDateTime(dt, besttt)
return (utils.datetimeToFloat(mindate), utils.datetimeToFloat(maxdate),
intervals_sec[best], N.array(ticks), format)
