def histogram(data, nbins, range=None):
"""
Comes from Konrad Hinsen: Scientific Python
"""
data = Numeric.array(data, Numeric.Float)
if range is None:
min = Numeric.minimum.reduce(data)
max = Numeric.maximum.reduce(data)
else:
min, max = range
data = Numeric.repeat(
data,
Numeric.logical_and(Numeric.less_equal(data, max),
Numeric.greater_equal(data, min)))
# end if
bin_width = (max - min) / nbins
data = Numeric.floor((data - min) / bin_width).astype(Numeric.Int)
histo = Numeric.add.reduce(
Numeric.equal(Numeric.arange(nbins)[:, Numeric.NewAxis], data), -1)
histo[-1] = histo[-1] + Numeric.add.reduce(Numeric.equal(nbins, data))
bins = min + bin_width * (Numeric.arange(nbins) + 0.5)
return Numeric.transpose(Numeric.array([bins, histo]))
def histogram(data, nbins, range = None):
"""
Comes from Konrad Hinsen: Scientific Python
"""
data = Numeric.array(data, Numeric.Float)
if range is None:
min = Numeric.minimum.reduce(data)
max = Numeric.maximum.reduce(data)
else:
min, max = range
data = Numeric.repeat(data,
Numeric.logical_and(Numeric.less_equal(data, max),
Numeric.greater_equal(data,
min)))
# end if
bin_width = (max-min)/nbins
data = Numeric.floor((data - min)/bin_width).astype(Numeric.Int)
histo = Numeric.add.reduce(Numeric.equal(
Numeric.arange(nbins)[:,Numeric.NewAxis], data), -1)
histo[-1] = histo[-1] + Numeric.add.reduce(Numeric.equal(nbins, data))
bins = min + bin_width*(Numeric.arange(nbins)+0.5)
return Numeric.transpose(Numeric.array([bins, histo]))
def histogram(data, nbins, range = None):
"""
Create a histogram.
Comes from Konrad Hinsen: Scientific Python
@param data: data list or array
@type data: [any]
@param nbins: number of bins
@type nbins: int
@param range: data range to create histogram from (min val, max val)
@type range: (float, float) OR None
@return: array (2 x len(data) ) with start of bin and witdh of bin.
@rtype: array
"""
data = Numeric.array(data, Numeric.Float)
if range is None:
min = Numeric.minimum.reduce(data)
max = Numeric.maximum.reduce(data)
else:
min, max = range
data = Numeric.repeat(data,
Numeric.logical_and(Numeric.less_equal(data, max),
Numeric.greater_equal(data, min)))
bin_width = (max-min)/nbins
data = Numeric.floor((data - min)/bin_width).astype(Numeric.Int)
histo = Numeric.add.reduce(Numeric.equal(
Numeric.arange(nbins)[:,Numeric.NewAxis], data), -1)
histo[-1] = histo[-1] + Numeric.add.reduce(Numeric.equal(nbins, data))
bins = min + bin_width*(Numeric.arange(nbins)+0.5)
return Numeric.transpose(Numeric.array([bins, histo]))
def extractU(self, v):
"Extract curve in u-direction at parameter v."
if numerix.any(v < 0.) or numerix.any(v > 1.):
raise NURBSError, 'Out of parameter range [0,1]'
if v == 0.:
cntrl = self.cntrl[:, :, 0]
knots = self.uknots[:]
elif v == 1.:
cntrl = self.cntrl[:, :, -1]
knots = self.uknots[:]
else:
vknots = numerix.repeat(
numerix.asarray([v], numerix.Float),
[self.degree[0] * (self.cntrl.shape[1] + 1)])
coefs = numerix.resize(
self.cntrl, (4 * self.cntrl.shape[1], self.cntrl.shape[2]))
coefs, knots = bspkntins(self.degree[1], coefs, self.vknots,
vknots)
cntrl = numerix.resize(coefs,
(4, self.cntrl.shape[1], coefs.shape[1]))
i = 0
j = knots[0]
for k in knots[1:]:
if k == v:
break
elif k != j:
i += 1
j = k
return Crv.Crv(cntrl[:, :, i], self.uknots[:])
def extractV(self, u):
"Extract curve in v-direction at parameter u."
if numerix.any(u < 0.) or numerix.any(u > 1.):
raise NURBSError, 'Out of parameter range [0,1]'
if u == 0.:
cntrl = self.cntrl[:, 0, :]
knots = self.vknots[:]
elif u == 1.:
cntrl = self.cntrl[:, -1, :]
knots = self.vknots[:]
else:
uknots = numerix.repeat(
numerix.asarray([u], numerix.Float),
[self.degree[1] * (self.cntrl.shape[2] + 1)])
coefs = numerix.transpose(self.cntrl, (0, 2, 1))
coefs = numerix.resize(
coefs, (4 * self.cntrl.shape[2], self.cntrl.shape[1]))
coefs, knots = bspkntins(self.degree[0], coefs, self.uknots,
uknots)
coefs = numerix.resize(coefs,
(4, self.cntrl.shape[2], coefs.shape[1]))
cntrl = numerix.transpose(coefs, (0, 2, 1))
i = 0
j = knots[0]
for k in knots[1:]:
if k == u:
break
elif k != j:
i += 1
j = k
return Crv.Crv(cntrl[:, i, :], self.vknots[:])
def extractV(self, u):
"Extract curve in v-direction at parameter u."
if numerix.any(u < 0.) or numerix.any(u > 1.):
raise NURBSError, 'Out of parameter range [0,1]'
if u == 0.:
cntrl = self.cntrl[:,0,:]
knots = self.vknots[:]
elif u == 1.:
cntrl = self.cntrl[:,-1,:]
knots = self.vknots[:]
else:
uknots = numerix.repeat(numerix.asarray([u], numerix.Float),[self.degree[1]*(self.cntrl.shape[2] + 1)])
coefs = numerix.transpose(self.cntrl,(0, 2, 1))
coefs = numerix.resize(coefs,(4*self.cntrl.shape[2], self.cntrl.shape[1]))
coefs, knots = bspkntins(self.degree[0], coefs, self.uknots, uknots)
coefs = numerix.resize(coefs, (4, self.cntrl.shape[2], coefs.shape[1]))
cntrl = numerix.transpose(coefs,(0,2,1))
i = 0
j = knots[0]
for k in knots[1:]:
if k == u:
break
elif k != j:
i += 1
j = k
return Crv.Crv(cntrl[:,i,:], self.vknots[:])
def histogram(data, nbins, range=None):
"""
Create a histogram.
Comes from Konrad Hinsen: Scientific Python
@param data: data list or array
@type data: [any]
@param nbins: number of bins
@type nbins: int
@param range: data range to create histogram from (min val, max val)
@type range: (float, float) OR None
@return: array (2 x len(data) ) with start of bin and witdh of bin.
@rtype: array
"""
data = Numeric.array(data, Numeric.Float)
if range is None:
min = Numeric.minimum.reduce(data)
max = Numeric.maximum.reduce(data)
else:
min, max = range
data = Numeric.repeat(
data,
Numeric.logical_and(Numeric.less_equal(data, max),
Numeric.greater_equal(data, min)))
bin_width = (max - min) / nbins
data = Numeric.floor((data - min) / bin_width).astype(Numeric.Int)
histo = Numeric.add.reduce(
Numeric.equal(Numeric.arange(nbins)[:, Numeric.NewAxis], data), -1)
histo[-1] = histo[-1] + Numeric.add.reduce(Numeric.equal(nbins, data))
bins = min + bin_width * (Numeric.arange(nbins) + 0.5)
return Numeric.transpose(Numeric.array([bins, histo]))
def extractU(self, v):
"Extract curve in u-direction at parameter v."
if numerix.any(v < 0.) or numerix.any(v > 1.):
raise NURBSError, 'Out of parameter range [0,1]'
if v == 0.:
cntrl = self.cntrl[:,:,0]
knots = self.uknots[:]
elif v == 1.:
cntrl = self.cntrl[:,:,-1]
knots = self.uknots[:]
else:
vknots = numerix.repeat(numerix.asarray([v], numerix.Float),[self.degree[0]*(self.cntrl.shape[1] + 1)])
coefs = numerix.resize(self.cntrl,(4*self.cntrl.shape[1], self.cntrl.shape[2]))
coefs, knots = bspkntins(self.degree[1], coefs, self.vknots, vknots)
cntrl = numerix.resize(coefs, (4, self.cntrl.shape[1], coefs.shape[1]))
i = 0
j = knots[0]
for k in knots[1:]:
if k == v:
break
elif k != j:
i += 1
j = k
return Crv.Crv(cntrl[:,:,i], self.uknots[:])
