[edit] implemented method to derive limits for the special methods for addition and subtraction

This commit is contained in:
Sebastian Wehling-Benatelli 2016-02-12 09:50:59 +01:00
parent 2956f3b733
commit d5e16d64da

View File

@ -2,6 +2,7 @@
# -*- coding: utf-8 -*-
import numpy as np
from obspy import UTCDateTime
from pylot.core.util.version import get_git_version as _getVersionString
__version__ = _getVersionString()
@ -127,21 +128,21 @@ class ProbabilityDensityFunction(object):
assert isinstance(other, ProbabilityDensityFunction), \
'both operands must be of type ProbabilityDensityFunction'
incr, limits, pdf_self, pdf_other = self.rearrange(other)
x0, incr, npts, pdf_self, pdf_other = self.rearrange(other)
pdf = np.convolve(pdf_self, pdf_other, 'same') * self.delta()
pdf = np.convolve(pdf_self, pdf_other, 'same') * incr
return ProbabilityDensityFunction(incr, limits, pdf)
return ProbabilityDensityFunction(x0, incr, npts, pdf)
def __sub__(self, other):
assert isinstance(other, ProbabilityDensityFunction), \
'both operands must be of type ProbabilityDensityFunction'
x, pdf_self, pdf_other = self.rearrange(other, plus=False)
x0, incr, npts, pdf_self, pdf_other = self.rearrange(other, plus=False)
pdf = np.convolve(pdf_self, pdf_other[::-1], 'same') * self.delta()
pdf = np.correlate(pdf_self, pdf_other, 'same') * incr
return ProbabilityDensityFunction(x, pdf)
return ProbabilityDensityFunction(x0, incr, npts, pdf)
def __nonzero__(self):
return True
@ -176,11 +177,59 @@ class ProbabilityDensityFunction(object):
'''
margin = 1.5 * np.max(midpoint - lbound, rbound - midpoint)
x0 = midpoint - margin
npts = 2 * int(margin // incr)
npts = int(2 * margin // incr)
params = parameter[type](lbound, midpoint, rbound, decfact)
pdf = branches[type](create_axis(x0, incr, npts), midpoint, *params)
try:
pdf = branches[type](create_axis(x0, incr, npts), midpoint, *params)
except TypeError as e:
print('Warning:\n' + e.message + '\n' + 'trying timestamp instead')
assert isinstance(midpoint, UTCDateTime), 'object not capable of' \
' timestamp representation'
pdf = branches[type](create_axis(x0, incr, npts),
midpoint.timestamp, *params)
return ProbabilityDensityFunction(x0, incr, npts, pdf)
def findlimits(self, incr, l1, l2, r1, r2, max_npts=1e5):
'''
Takes an increment incr and two left and two right limits and returns
the left most limit and the minimum number of points needed to cover
the whole given interval.
:param incr:
:param l1:
:param l2:
:param r1:
:param r2:
:param max_npts:
:return:
'''
if l1 >= l2 and r1 >= r2:
x0 = l2
npts = int(r1 - x0 // incr)
elif l1 < l2 and r1 >= r2:
x0 = l1
npts = int(r1 - x0 // incr)
elif l1 >= l2 and r1 < r2:
x0 = l2
npts = int(r2 - x0 // incr)
elif l1 >= r2:
x0 = l2
npts = int(r1 - x0 // incr)
elif l2 >= r1:
x0 = l1
npts = int(r2 - x0 // incr)
else:
x0 = None
npts = None
if npts > max_npts:
raise ValueError('Maximum number of points exceeded:\n'
'max_npts - %d\n'
'npts - %d\n' % (max_npts, npts))
return x0, npts
def rearrange(self, other, plus=True):
'''
Method rearrange takes another Probability Density Function and returns
@ -195,34 +244,30 @@ class ProbabilityDensityFunction(object):
assert isinstance(other, ProbabilityDensityFunction), \
'both operands must be of type ProbabilityDensityFunction'
sd = self.delta()
od = other.delta()
smin = np.min(self.axis)
smax = np.max(self.axis)
omin = np.min(other.axis)
omax = np.max(other.axis)
samin = np.min(self.axis)
oamin = np.min(other.axis)
# test if 0 is a sampling node
nodes_test = (not samin % sd and not oamin % od)
# test if sampling rates match and if 0 is a sampling node
if sd == od and nodes_test:
if plus:
max = np.max(self.axis) + np.max(other.axis)
else:
max = np.max(np.max(self.axis), np.max(other.axis))
x = np.arange(-max, max + sd, sd)
if not self.incr == other.incr:
raise NotImplementedError('Upsampling of the lower sampled PDF not implemented yet!')
else:
raise ValueError('Sampling rates do not match or nodes shifted!')
incr = self.incr
pdf_self = np.zeros(x.size)
pdf_other = np.zeros(x.size)
x0, npts = self.findlimits(incr, smin, smax, omin, omax)
sstart = np.where(x == samin)
pdf_self = np.zeros(npts)
pdf_other = np.zeros(npts)
x = create_axis(x0, incr, npts)
sstart = np.where(x == smin)
s_end = sstart + self.data.size
ostart = np.where(x == oamin)
ostart = np.where(x == omin)
o_end = ostart + other.data.size
pdf_self[sstart:s_end] = self.data
pdf_other[ostart:o_end] = other.data
return x, pdf_self, pdf_other
return x0, incr, npts, pdf_self, pdf_other