def plotst(y, titlestr): n = min(minimum.reduce(y)) m = max(maximum.reduce(y)) nlevels = 40 clevel = linspace(n, m, nlevels) ticks, mticks = scale1(clevel[0], clevel[-1]) time = linspace(start / srate, end / srate, y.shape[1]) fr = linspace(lo, hi, y.shape[0]) if ref: subplot(211) c = contourf(time, fr, y, clevel, cmap = cm.jet) cax = gca() title(titlestr, fontsize = 15) colorbar(format = '%.2g', ticks = ticks) newright = cax.get_position()[2] if ref: from matplotlib.colorbar import make_axes subplot(212) plot(time, r) # ensure the x axis takes up the same amount of space ax = gca() p = ax.get_position() p[2] = newright ax.set_position(p) # ensure the x axis has the same range a = list(ax.axis()) a[0:2] = cax.axis()[0:2] ax.axis(a)
def plot(self, z, cmap=meg_cmap, zrange="zero", label=False, showsens=False):
"""The array z of values to be plotted must be in the same
order as the array returned by get_names(). zrange can be
'auto', 'zero' which is auto but symmetric around 0, or
a pair of min, max."""
make_spline(self.x, self.y, array(z, "d"))
r = range(self.M)
for i in r:
xx = self.X[i]
for j in r:
yy = self.Y[j]
if not self.mask[j, i]:
self.Z[j, i] = interpolate(xx, yy, self.x, self.y)
Z = ma.array(self.Z, mask=self.mask)
if zrange == "auto" or zrange == "zero":
zmin = ma.minimum.reduce(Z)
zmax = ma.maximum.reduce(Z)
if zrange == "zero":
# If it crosses zero make it symmetrical.
if (zmin < 0) and (0 < zmax):
maxmax = max(-zmin, zmax)
zmin = -maxmax
zmax = maxmax
else:
zmin = zrange[0]
zmax = zrange[1]
# First make nice tics for this range.
# Then switch to the new limits given by the tics
# so the contour plot will use the whole range.
ticks, mticks = scale1(zmin, zmax)
zmin, zmax = ticks[0], ticks[-1]
nlevels = 100
levels = linspace(zmin, zmax, nlevels)
# plot the boundary and maybe the sensors
plot(self.boundx, self.boundy, color="black", zorder=1, linewidth=3)
if showsens:
scatter(self.x, self.y, s=15, c=(0, 1, 0), zorder=2, marker="o", linewidth=0.5)
# contourf(self.X, self.Y, Z, levels, cmap = cmap)
# contourf(self.X, self.Y, Z, levels, cmap = matplotlib.cm.hot)
contourf(self.X, self.Y, Z, levels)
im = gci() # save the ContourSet to return
contour(self.X, self.Y, Z, 10, colors="black")
if label:
for name in self.sensors:
s = self.topo[name]
text(s.x, s.y, name)
l = 1.02
x = -0.01
y = -0.04
axis([x, x + l, y, y + l])
axis("off")
axis("scaled")
return im, ticks
