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[add] untested implementations of standard deviation and probability value determination methods to class ProbabilityDensityFunction

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Sebastian Wehling-Benatelli 2016-03-04 06:27:11 +01:00
parent 78a5a5117a
commit e6b5848f36
1 changed files with 28 additions and 8 deletions
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36
pylot/core/util/pdf.py
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@ -3,6 +3,7 @@
import numpy as np import numpy as np
from obspy import UTCDateTime from obspy import UTCDateTime
from pylot.core.util.utils import find_nearest
from pylot.core.util.version import get_git_version as _getVersionString from pylot.core.util.version import get_git_version as _getVersionString
__version__ = _getVersionString() __version__ = _getVersionString()
@ -133,13 +134,13 @@ class ProbabilityDensityFunction(object):
'both operands must be of type ProbabilityDensityFunction' 'both operands must be of type ProbabilityDensityFunction'
raise NotImplementedError('implementation of resulting axis unclear - feature pending!') raise NotImplementedError('implementation of resulting axis unclear - feature pending!')
x0, incr, npts, 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') * incr # pdf = np.convolve(pdf_self, pdf_other, 'same') * incr
#
# shift axis values for correct plotting # # shift axis values for correct plotting
npts *= 2 # npts *= 2
x0 *= 2 # x0 *= 2
return ProbabilityDensityFunction(x0, incr, npts, pdf) # return ProbabilityDensityFunction(x0, incr, npts, pdf)
def __sub__(self, other): def __sub__(self, other):
assert isinstance(other, ProbabilityDensityFunction), \ assert isinstance(other, ProbabilityDensityFunction), \
@ -236,8 +237,27 @@ class ProbabilityDensityFunction(object):
return rval * self.incr return rval * self.incr
def standard_deviation(self): def standard_deviation(self):
pass mu = self.expectation()
rval = 0
for n, x in enumerate(self.axis):
rval += (x - mu) ** 2 * self.data[n]
return rval * self.incr
def prob_lt_val(self, value):
if value <= self.axis[0] or value > self.axis[-1]:
raise ValueError('value out of bounds: {0}'.format(value))
return self.data[self.axis <= value].sum() * self.incr
def prob_gt_val(self, value):
if value < self.axis[0] or value >= self.axis[-1]:
raise ValueError('value out of bounds: {0}'.format(value))
return self.data[self.axis >= value].sum() * self.incr
def prob_val(self, value):
if not (self.axis[0] <= value <= self.axis[-1]):
Warning('{0} not on axis'.format(value))
return None
return self.data[find_nearest(self.axis, value)] * self.incr
def commonlimits(self, incr, other, max_npts=1e5): def commonlimits(self, incr, other, max_npts=1e5):
''' '''