def specgram_demo(): ''' the demo in matplotlib. But calls interactive.specgram ''' from pylab import arange, sin, where, logical_and, randn, pi dt = 0.0005 t = arange(0.0, 20.0, dt) s1 = sin(2*pi*100*t) s2 = 2*sin(2*pi*400*t) # create a transient "chirp" mask = where(logical_and(t>10, t<12), 1.0, 0.0) s2 = s2 * mask # add some noise into the mix nse = 0.01*randn(len(t)) x = s1 + s2 + nse # the signal NFFT = 1024 # the length of the windowing segments Fs = int(1.0/dt) # the sampling frequency from ifigure.interactive import figure, specgram, nsec, plot, isec, clog, hold figure() hold(True) nsec(2) isec(0) plot(t, x) isec(1) specgram(x, NFFT=NFFT, Fs=Fs, noverlap=900) clog()
def spec_demo():
'''
the demo in matplotlib. But calls
interactive.specgram
'''
from pylab import arange, sin, where, logical_and, randn, pi
dt = 0.0005
t = arange(0.0, 20.0, dt)
s1 = sin(2 * pi * 100 * t)
s2 = 2 * sin(2 * pi * 400 * t)
# create a transient "chirp"
mask = where(logical_and(t > 10, t < 12), 1.0, 0.0)
s2 = s2 * mask
# add some noise into the mix
nse = 0.01 * randn(len(t))
x = s1 + s2 + nse # the signal
NFFT = 1024 # the length of the windowing segments
Fs = int(1.0 / dt) # the sampling frequency
from ifigure.interactive import figure, spec, nsec, plot, isec, clog, hold
figure()
hold(True)
nsec(2)
isec(0)
plot(t, x)
isec(1)
spec(t, x, NFFT=NFFT, noverlap=900)
clog()
def plot_tiles3():
x, y, z = read_tile_data(list=True)
figure()
threed('on')
hold('on')
for k in range(100):
m = k + 100
plot(x[m], y[m], z[m], facecolor=[1, 0, 0, 1])
def plot_tiles3():
x, y, z = read_tile_data(list = True)
figure()
threed('on')
hold('on')
for k in range(100):
m = k+100
plot(x[m], y[m], z[m], facecolor = [1, 0, 0, 1])
def contour_demo2(**kwargs):
import mpl_toolkits.mplot3d.axes3d as axes3d
from ifigure.interactive import contourf, threed, figure, hold
X, Y, Z = axes3d.get_test_data(0.05)
v = figure(gl=True)
threed('on')
hold('on')
contourf(X, Y, Z)
contourf(X, Y, Z, zdir='x', offset=-40)
def contour_demo2(**kwargs):
import mpl_toolkits.mplot3d.axes3d as axes3d
from ifigure.interactive import contourf, threed, figure, hold
X, Y, Z = axes3d.get_test_data(0.05)
v = figure(gl = True)
threed('on')
hold('on')
contourf(X, Y, Z)
contourf(X, Y, Z, zdir = 'x', offset = -40)
def image_demo():
from ifigure.interactive import image, threed, figure, hold
figure(gl = True)
threed('on')
hold('on')
X = np.linspace(-5, 5, 40)
Y = np.linspace(-5, 5, 40)
X, Y = np.meshgrid(X, Y)
R = np.sqrt(X**2 + Y**2)
Z = np.sin(R)
image(Z, cmap='coolwarm', im_center = [0,0,1])
image(Z, cmap='coolwarm', im_center = [0,0,1],
im_axes = ([0,0,1], [0,1,0]))
image(Z, cmap='coolwarm', im_center = [0,0,1],
im_axes = ([1/np.sqrt(2), 0,1/np.sqrt(2)],
[0, 1, 0]))
def image_demo():
from ifigure.interactive import image, threed, figure, hold
figure(gl=True)
threed('on')
hold('on')
X = np.linspace(-5, 5, 40)
Y = np.linspace(-5, 5, 40)
X, Y = np.meshgrid(X, Y)
R = np.sqrt(X**2 + Y**2)
Z = np.sin(R)
image(Z, cmap='coolwarm', im_center=[0, 0, 1])
image(Z,
cmap='coolwarm',
im_center=[0, 0, 1],
im_axes=([0, 0, 1], [0, 1, 0]))
image(Z,
cmap='coolwarm',
im_center=[0, 0, 1],
im_axes=([1 / np.sqrt(2), 0, 1 / np.sqrt(2)], [0, 1, 0]))