def _autoscale(self, vars, datamin=None, datamax=None):
from fipy.tools import numerix
if datamin is None:
datamin = 1e300
for var in vars:
datamin = min(datamin, numerix.nanmin(var))
if datamax is None:
from fipy.tools import numerix
datamax = -1e300
for var in vars:
datamax = max(datamax, numerix.nanmax(var))
return datamin, datamax
def _autoscale(self, vars, datamin=None, datamax=None):
from fipy.tools import numerix
if datamin is None:
datamin = 1e300
for var in vars:
datamin = min(datamin, numerix.nanmin(var))
if datamax is None:
from fipy.tools import numerix
datamax = -1e300
for var in vars:
datamax = max(datamax, numerix.nanmax(var))
return datamin, datamax
def plot(self, matrix, RHSvector, log='auto'):
import tempfile
import os
if "print" in os.environ['FIPY_DISPLAY_MATRIX'].lower().split():
print("-" * 75)
print(self.title)
print("-" * 75)
print("L:")
print(matrix)
print("b:", RHSvector)
(f, mtxName) = tempfile.mkstemp(suffix='.mtx')
matrix.exportMmf(mtxName)
mtx = mmio.mmread(mtxName)
os.remove(mtxName)
pyplot.ion()
c = mtx.tocoo()
y = c.row
x = c.col
z = c.data
N = matrix._shape[0]
b = RHSvector
if numerix.shape(b) == ():
b = numerix.zeros((N, ), 'l')
if len(z) == 0:
y = numerix.zeros((1, ), 'l')
x = numerix.zeros((1, ), 'l')
z = numerix.zeros((1, ), 'l')
def signed_to_logs(v):
return (numerix.where(v > 0, numerix.log10(v), numerix.nan),
numerix.where(v < 0, numerix.log10(-v), numerix.nan))
def logs_to_signed(v, plus, minus):
v = numerix.where(v > 0, plus, -minus)
v = numerix.where(numerix.isnan(v), 0., v)
return v
zPlus, zMinus = signed_to_logs(z)
bPlus, bMinus = signed_to_logs(b)
logs = (zPlus, zMinus, bPlus, bMinus)
log = ((log == True)
or (log == 'auto' and
(numerix.nanmax(numerix.concatenate(logs)) -
numerix.nanmin(numerix.concatenate(logs)) > 2)))
if log:
zMin = numerix.nanmin(numerix.concatenate(logs))
zMax = numerix.nanmax(numerix.concatenate(logs))
zMin -= 0.5
numdec = numerix.floor(zMax) - numerix.ceil(zMin)
if numdec < 0:
zMax += 0.5
for v in logs:
v -= zMin
zRange = zMax - zMin
if zRange == 0:
zRange = numerix.nanmax(zPlus) + 1
z = logs_to_signed(z, zPlus, zMinus)
b = logs_to_signed(b, bPlus, bMinus)
fmt = SignedLogFormatter(threshold=zMin)
loc = SignedLogLocator(threshold=zMin)
else:
zRange = max(abs(numerix.concatenate((z, b))))
if zRange == 0:
zRange = 1
fmt = None
loc = None
pyplot.ioff()
fig = pyplot.figure(self.id)
fig.clf()
usetex = rcParams['text.usetex']
rcParams['text.usetex'] = False
cmap = cm.RdBu
norm = Normalize(vmin=-zRange, vmax=zRange)
x0 = self.margin
L_ax = fig.add_axes([
x0 / self.aspect, self.margin, self.L_width / self.aspect,
self.L_width
])
L_ax.text(0.5,
-0.1,
"L",
transform=L_ax.transAxes,
horizontalalignment='center',
verticalalignment='baseline')
x0 += self.L_width + self.buffer
c_ax = fig.add_axes([
x0 / self.aspect, self.margin, self.c_width / self.aspect,
self.L_width
])
x0 += self.c_width + self.buffer
b_ax = fig.add_axes([
x0 / self.aspect, self.margin, self.b_width / self.aspect,
self.L_width
],
sharey=L_ax)
b_ax.text(0.5,
-0.1,
"b",
transform=b_ax.transAxes,
horizontalalignment='center',
verticalalignment='baseline')
def scatterRectangles(x, y, z, norm=None, cmap=None):
patches = [
Rectangle(numerix.array([X - 0.5, Y - 0.5]),
1.,
1.,
edgecolor='none') for X, Y in zip(x, y)
]
collection = PatchCollection(patches,
norm=norm,
cmap=cmap,
edgecolors='none')
collection.set_array(z)
return collection
L_ax.add_collection(
scatterRectangles(x=x, y=y, z=z, norm=norm, cmap=cmap))
b_ax.add_collection(
scatterRectangles(x=numerix.zeros((N, ), 'l'),
y=numerix.arange(N),
z=b,
norm=norm,
cmap=cmap))
ColorbarBase(ax=c_ax,
cmap=cmap,
norm=norm,
orientation='vertical',
format=fmt,
ticks=loc)
pyplot.setp((b_ax.get_xticklabels(), b_ax.get_yticklabels(),
b_ax.get_xticklines(), b_ax.get_yticklines()),
visible=False)
L_ax.set_xlim(xmin=-0.5, xmax=N - 0.5)
L_ax.set_ylim(ymax=-0.5, ymin=N - 0.5)
b_ax.set_xlim(xmin=-0.5, xmax=0.5)
b_ax.set_ylim(ymax=-0.5, ymin=N - 0.5)
fig.suptitle(self.title, x=0.5, y=0.95, fontsize=14)
pyplot.draw()
rcParams['text.usetex'] = usetex
def plot(self, matrix, RHSvector, log='auto'):
import tempfile
import os
if "print" in os.environ['FIPY_DISPLAY_MATRIX'].lower().split():
print("-"*75)
print(self.title)
print("-"*75)
print("L:")
print(matrix)
print("b:", RHSvector)
(f, mtxName) = tempfile.mkstemp(suffix='.mtx')
matrix.exportMmf(mtxName)
mtx = mmio.mmread(mtxName)
os.remove(mtxName)
pyplot.ion()
c = mtx.tocoo()
y = c.row
x = c.col
z = c.data
N = matrix._shape[0]
b = RHSvector
if numerix.shape(b) == ():
b = numerix.zeros((N,), 'l')
if len(z) == 0:
y = numerix.zeros((1,), 'l')
x = numerix.zeros((1,), 'l')
z = numerix.zeros((1,), 'l')
def signed_to_logs(v):
return (numerix.where(v > 0, numerix.log10(v), numerix.nan),
numerix.where(v < 0, numerix.log10(-v), numerix.nan))
def logs_to_signed(v, plus, minus):
v = numerix.where(v > 0, plus, -minus)
v = numerix.where(numerix.isnan(v), 0., v)
return v
zPlus, zMinus = signed_to_logs(z)
bPlus, bMinus = signed_to_logs(b)
logs = (zPlus, zMinus, bPlus, bMinus)
log = ((log == True)
or (log == 'auto'
and (numerix.nanmax(numerix.concatenate(logs))
- numerix.nanmin(numerix.concatenate(logs)) > 2)))
if log:
zMin = numerix.nanmin(numerix.concatenate(logs))
zMax = numerix.nanmax(numerix.concatenate(logs))
zMin -= 0.5
numdec = numerix.floor(zMax) - numerix.ceil(zMin)
if numdec < 0:
zMax += 0.5
for v in logs:
v -= zMin
zRange = zMax - zMin
if zRange == 0:
zRange = numerix.nanmax(zPlus) + 1
z = logs_to_signed(z, zPlus, zMinus)
b = logs_to_signed(b, bPlus, bMinus)
fmt = SignedLogFormatter(threshold=zMin)
loc = SignedLogLocator(threshold=zMin)
else:
zRange = max(abs(numerix.concatenate((z, b))))
if zRange == 0:
zRange = 1
fmt = None
loc = None
pyplot.ioff()
fig = pyplot.figure(self.id)
fig.clf()
usetex = rcParams['text.usetex']
rcParams['text.usetex'] = False
cmap = cm.RdBu
norm = Normalize(vmin=-zRange, vmax=zRange)
x0 = self.margin
L_ax = fig.add_axes([x0 / self.aspect, self.margin, self.L_width / self.aspect, self.L_width])
L_ax.text(0.5, -0.1, "L",
transform=L_ax.transAxes, horizontalalignment='center', verticalalignment='baseline')
x0 += self.L_width + self.buffer
c_ax = fig.add_axes([x0 / self.aspect, self.margin, self.c_width / self.aspect, self.L_width])
x0 += self.c_width + self.buffer
b_ax = fig.add_axes([x0 / self.aspect, self.margin, self.b_width / self.aspect, self.L_width],
sharey=L_ax)
b_ax.text(0.5, -0.1, "b",
transform=b_ax.transAxes, horizontalalignment='center', verticalalignment='baseline')
def scatterRectangles(x, y, z, norm=None, cmap=None):
patches = [Rectangle(numerix.array([X - 0.5, Y - 0.5]), 1., 1.,
edgecolor='none') for X, Y in zip(x, y)]
collection = PatchCollection(patches, norm=norm, cmap=cmap,
edgecolors='none')
collection.set_array(z)
return collection
L_ax.add_collection(scatterRectangles(x=x, y=y, z=z,
norm=norm, cmap=cmap))
b_ax.add_collection(scatterRectangles(x=numerix.zeros((N,), 'l'), y=numerix.arange(N), z=b,
norm=norm, cmap=cmap))
ColorbarBase(ax=c_ax, cmap=cmap, norm=norm, orientation='vertical',
format=fmt, ticks=loc)
pyplot.setp((b_ax.get_xticklabels(),
b_ax.get_yticklabels(),
b_ax.get_xticklines(),
b_ax.get_yticklines()), visible=False)
L_ax.set_xlim(xmin=-0.5, xmax=N-0.5)
L_ax.set_ylim(ymax=-0.5, ymin=N-0.5)
b_ax.set_xlim(xmin=-0.5, xmax=0.5)
b_ax.set_ylim(ymax=-0.5, ymin=N-0.5)
fig.suptitle(self.title, x=0.5, y=0.95, fontsize=14)
pyplot.draw()
rcParams['text.usetex'] = usetex
def plot(self, matrix, RHSvector, log='auto'):
import tempfile
import os
(f, mtxName) = tempfile.mkstemp(suffix='.mtx')
matrix.exportMmf(mtxName)
mtx = mmio.mmread(mtxName)
## f.close()
os.remove(mtxName)
pylab.ion()
c = mtx.tocoo()
y = c.row
x = c.col
z = c.data
b = RHSvector
if len(z) == 0:
y = zeros((1,))
x = zeros((1,))
z = zeros((1,))
zPlus = where(z > 0, log10(z), nan)
zMinus = where(z < 0, log10(-z), nan)
bPlus = where(b > 0, log10(b), nan)
bMinus = where(b < 0, log10(-b), nan)
if (log == True
or (log == 'auto'
and (max(zPlus) - min(zPlus) > 2
or max(zMinus) - min(zMinus) > 2
or max(bPlus) - min(bPlus) > 2
or max(bMinus) - min(bMinus) > 2))):
log = True
else:
log = False
if log:
zMin = nanmin((nanmin(zPlus), nanmin(zMinus), nanmin(bPlus), nanmin(bMinus)))
zMax = nanmax((nanmax(zPlus), nanmax(zMinus), nanmax(bPlus), nanmax(bMinus)))
## zThreshold = 0.5 # (zMax - zMin) / 5.
zMin -= 0.5
numdec = math.floor(zMax)-math.ceil(zMin)
if numdec < 0:
zMax += 0.5
zPlus -= zMin
zMinus -= zMin
bPlus -= zMin
bMinus -= zMin
zRange = zMax - zMin
if zRange == 0:
zRange = nanmax(zPlus) + 1
z = where(z > 0, zPlus, -zMinus)
z = where(isnan(z), 0., z)
b = where(b > 0, bPlus, -bMinus)
b = where(isnan(b), 0., b)
fmt = SignedLogFormatter(threshold=zMin)
loc = SignedLogLocator(threshold=zMin)
else:
zRange = max(max(abs(z)), max(abs(b)))
if zRange == 0:
zRange = 1
fmt = None
loc = None
N = matrix._getShape()[0]
saveSize = pylab.rcParams['figure.figsize']
size = pylab.rcParams['figure.dpi'] **2 * saveSize[0] * saveSize[1] / N**2
pylab.ioff()
pylab.figure(self.id)
pylab.clf()
pylab.delaxes()
ax1 = pylab.axes([self.margin, self.margin, self.width, self.width])
Mscat = pylab.scatter(x, y, c=z,
vmin=-zRange, vmax=zRange, edgecolors='none',
cmap=pylab.get_cmap('RdBu'), marker='s', s=size)
ax2 = pylab.axes([self.width + self.margin, self.margin, (self.width / self.aspect) / N, self.width],
sharey=ax1)
bscat = pylab.scatter(zeros((N,)), arange(N), c=b,
vmin=-zRange, vmax=zRange, edgecolors='none',
cmap=pylab.get_cmap('RdBu'), marker='s', s=size)
pylab.setp((ax2.get_xticklabels(),
ax2.get_yticklabels(),
ax2.get_xticklines(),
ax2.get_yticklines()), visible=False)
pylab.axes(ax1)
pylab.axis([-0.5, N - 0.5, N - 0.5, -0.5])
pylab.colorbar(format=fmt, ticks=loc)
pylab.title(self.title)
pylab.draw()
