def _h_arrows(self, length):
""" length is in arrow width units """
# It might be possible to streamline the code
# and speed it up a bit by using complex (x,y)
# instead of separate arrays; but any gain would be slight.
minsh = self.minshaft * self.headlength
N = len(length)
length = length.reshape(N, 1)
# x, y: normal horizontal arrow
x = npy.array([0, -self.headaxislength, -self.headlength, 0],
npy.float64)
x = x + npy.array([0, 1, 1, 1]) * length
y = 0.5 * npy.array([1, 1, self.headwidth, 0], npy.float64)
y = npy.repeat(y[npy.newaxis, :], N, axis=0)
# x0, y0: arrow without shaft, for short vectors
x0 = npy.array(
[0, minsh - self.headaxislength, minsh - self.headlength, minsh],
npy.float64)
y0 = 0.5 * npy.array([1, 1, self.headwidth, 0], npy.float64)
ii = [0, 1, 2, 3, 2, 1, 0]
X = x.take(ii, 1)
Y = y.take(ii, 1)
Y[:, 3:] *= -1
X0 = x0.take(ii)
Y0 = y0.take(ii)
Y0[3:] *= -1
shrink = length / minsh
X0 = shrink * X0[npy.newaxis, :]
Y0 = shrink * Y0[npy.newaxis, :]
short = npy.repeat(length < minsh, 7, axis=1)
#print 'short', length < minsh
# Now select X0, Y0 if short, otherwise X, Y
X = ma.where(short, X0, X)
Y = ma.where(short, Y0, Y)
if self.pivot[:3] == 'mid':
X -= 0.5 * X[:, 3, npy.newaxis]
elif self.pivot[:3] == 'tip':
X = X - X[:, 3, npy.newaxis] #numpy bug? using -= does not
# work here unless we multiply
# by a float first, as with 'mid'.
tooshort = length < self.minlength
if tooshort.any():
# Use a heptagonal dot:
th = npy.arange(0, 7, 1, npy.float64) * (npy.pi / 3.0)
x1 = npy.cos(th) * self.minlength * 0.5
y1 = npy.sin(th) * self.minlength * 0.5
X1 = npy.repeat(x1[npy.newaxis, :], N, axis=0)
Y1 = npy.repeat(y1[npy.newaxis, :], N, axis=0)
tooshort = ma.repeat(tooshort, 7, 1)
X = ma.where(tooshort, X1, X)
Y = ma.where(tooshort, Y1, Y)
return X, Y
def _h_arrows(self, length):
""" length is in arrow width units """
# It might be possible to streamline the code
# and speed it up a bit by using complex (x,y)
# instead of separate arrays; but any gain would be slight.
minsh = self.minshaft * self.headlength
N = len(length)
length = length.reshape(N, 1)
# x, y: normal horizontal arrow
x = npy.array([0, -self.headaxislength,
-self.headlength, 0], npy.float64)
x = x + npy.array([0,1,1,1]) * length
y = 0.5 * npy.array([1, 1, self.headwidth, 0], npy.float64)
y = npy.repeat(y[npy.newaxis,:], N, axis=0)
# x0, y0: arrow without shaft, for short vectors
x0 = npy.array([0, minsh-self.headaxislength,
minsh-self.headlength, minsh], npy.float64)
y0 = 0.5 * npy.array([1, 1, self.headwidth, 0], npy.float64)
ii = [0,1,2,3,2,1,0]
X = x.take(ii, 1)
Y = y.take(ii, 1)
Y[:, 3:] *= -1
X0 = x0.take(ii)
Y0 = y0.take(ii)
Y0[3:] *= -1
shrink = length/minsh
X0 = shrink * X0[npy.newaxis,:]
Y0 = shrink * Y0[npy.newaxis,:]
short = npy.repeat(length < minsh, 7, axis=1)
#print 'short', length < minsh
# Now select X0, Y0 if short, otherwise X, Y
X = ma.where(short, X0, X)
Y = ma.where(short, Y0, Y)
if self.pivot[:3] == 'mid':
X -= 0.5 * X[:,3, npy.newaxis]
elif self.pivot[:3] == 'tip':
X = X - X[:,3, npy.newaxis] #numpy bug? using -= does not
# work here unless we multiply
# by a float first, as with 'mid'.
tooshort = length < self.minlength
if tooshort.any():
# Use a heptagonal dot:
th = npy.arange(0,7,1, npy.float64) * (npy.pi/3.0)
x1 = npy.cos(th) * self.minlength * 0.5
y1 = npy.sin(th) * self.minlength * 0.5
X1 = npy.repeat(x1[npy.newaxis, :], N, axis=0)
Y1 = npy.repeat(y1[npy.newaxis, :], N, axis=0)
tooshort = ma.repeat(tooshort, 7, 1)
X = ma.where(tooshort, X1, X)
Y = ma.where(tooshort, Y1, Y)
return X, Y
def transform(self, a):
sign = npy.sign(npy.asarray(a))
masked = ma.masked_inside(a, -self.linthresh, self.linthresh, copy=False)
log = sign * ma.log(npy.abs(masked)) / self._log_base
if masked.mask.any():
return npy.asarray(ma.where(masked.mask,
a * self._linadjust,
log))
else:
return npy.asarray(log)
