def quiver_demo(**kwargs):
'''
quiver_demo(length = 1.0,
normalize = True,
facecolor = 'b',
edgecolor = None,
arrow_length_ratio = 0.3,
shaftsize = 0.01,
headsize = 0.01)
'''
from ifigure.interactive import quiver, threed, figure, lighting, view, isec, nsec
x, y, z = np.meshgrid(np.arange(-0.8, 1, 0.2),
np.arange(-0.8, 1, 0.2),
np.arange(-0.8, 1, 0.8))
u = np.sin(np.pi * x) * np.cos(np.pi * y) * np.cos(np.pi * z)
v = -np.cos(np.pi * x) * np.sin(np.pi * y) * np.cos(np.pi * z)
w = (np.sqrt(2.0 / 3.0) * np.cos(np.pi * x) * np.cos(np.pi * y) *
np.sin(np.pi * z))
figure()
nsec(2)
isec(0)
threed('on')
lighting(light = 0.5, ambient = 0.7)
view('noclip')
quiver(x, y, z, u, v, w, length = 0.3, facecolor = 'b')
isec(1)
threed('on')
lighting(light = 0.5, ambient = 0.7)
view('noclip')
quiver(x, y, z, u, v, w, cz = True, cdata = y, length = 0.3)
def onPlotTimeDep(self, e=None, *args, **kargs):
def plot_data(time, data):
x = np.array(time, dtype='float').flatten()
y = np.array(data, dtype='float').flatten()
x = [t for t in x if not np.isnan(t)]
y = [t for t in y if not np.isnan(t)]
return np.array(x), np.array(y)
help = self.td._var0._help
data = self.td._var0
import ifigure.interactive as plt
plt.figure()
time = data['18']['data']
new_plot = True
for key in help:
if not key in data: continue
if key == '18': continue
x, y = help[key]
if y.startswith('-'):
if not new_plot: plt.addpage()
try:
xdata, ydata = plot_data(time, data[key]['data'])
plt.plot(xdata, ydata)
plt.title(x)
new_plot = False
except:
print('failed to generate picture for', key)
new_plot = True
pass
def surf_demo2(**kwargs):
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
from ifigure.interactive import surf, threed, figure, isec, nsec
figure(gl=True)
nsec(3)
isec(0)
threed('on')
u = np.linspace(0, 2 * np.pi, 100)
v = np.linspace(0, np.pi, 100)
x = 10 * np.outer(np.cos(u), np.sin(v))
y = 10 * np.outer(np.sin(u), np.sin(v))
z = 10 * np.outer(np.ones(np.size(u)), np.cos(v))
surf(x, y, z, cz=False, facecolor='b', edgecolor='k')
isec(1)
threed('on')
surf(x, y, z, cstride=4, cz=True, edgecolor='k')
isec(2)
threed('on')
surf(x, y, z, cz=True, cdata=y, edgecolor=None)
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 quiver_demo(**kwargs):
'''
quiver_demo(length = 1.0,
normalize = True,
facecolor = 'b',
edgecolor = None,
arrow_length_ratio = 0.3,
shaftsize = 0.01,
headsize = 0.01)
'''
from ifigure.interactive import quiver, threed, figure, lighting, view, isec, nsec
x, y, z = np.meshgrid(np.arange(-0.8, 1, 0.2), np.arange(-0.8, 1, 0.2),
np.arange(-0.8, 1, 0.8))
u = np.sin(np.pi * x) * np.cos(np.pi * y) * np.cos(np.pi * z)
v = -np.cos(np.pi * x) * np.sin(np.pi * y) * np.cos(np.pi * z)
w = (np.sqrt(2.0 / 3.0) * np.cos(np.pi * x) * np.cos(np.pi * y) *
np.sin(np.pi * z))
figure()
nsec(2)
isec(0)
threed('on')
lighting(light=0.5, ambient=0.7)
view('noclip')
quiver(x, y, z, u, v, w, length=0.3, facecolor='b')
isec(1)
threed('on')
lighting(light=0.5, ambient=0.7)
view('noclip')
quiver(x, y, z, u, v, w, cz=True, cdata=y, length=0.3)
def onSlice(self, event):
from ifigure.interactive import figure, plot, nsec, isec, update, title, xlabel, ylabel
if event.mpl_xydata[0] is None:
return
for a in self._artists:
axes = a.axes
if axes is None:
return
data1, data2 = self.get_slice(event.mpl_xy[0],
event.mpl_xy[1], a)
if data1 is None:
continue
if data2 is None:
continue
figure()
nsec(2)
ou = update()
isec(0)
plot(data1[0], data1[1])
title('y slice : y = '+str(event.mpl_xydata[1]))
xlabel('x')
isec(1)
plot(data2[0], data2[1])
title('x slice : x = '+str(event.mpl_xydata[0]))
xlabel('y')
update(ou)
def onPlotTimeDep(self, e=None, *args, **kargs):
def plot_data(time, data):
x = np.array(time, dtype='float').flatten()
y = np.array(data, dtype='float').flatten()
x = [t for t in x if not np.isnan(t)]
y = [t for t in y if not np.isnan(t)]
return np.array(x), np.array(y)
help = self.td._var0._help
data = self.td._var0
import ifigure.interactive as plt
plt.figure()
time = data['18']['data']
new_plot = True
for key in help:
if not key in data: continue
if key == '18': continue
x, y = help[key]
if y.startswith('-'):
if not new_plot: plt.addpage()
try:
xdata, ydata = plot_data(time, data[key]['data'])
plt.plot(xdata, ydata)
plt.title(x)
new_plot = False
except:
print('failed to generate picture for', key)
new_plot = True
pass
def surf_demo2(**kwargs):
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
from ifigure.interactive import surf, threed, figure, isec, nsec
figure(gl = True)
nsec(3)
isec(0)
threed('on')
u = np.linspace(0, 2 * np.pi, 100)
v = np.linspace(0, np.pi, 100)
x = 10 * np.outer(np.cos(u), np.sin(v))
y = 10 * np.outer(np.sin(u), np.sin(v))
z = 10 * np.outer(np.ones(np.size(u)), np.cos(v))
surf(x, y, z, cz = False, facecolor='b', edgecolor = 'k')
isec(1)
threed('on')
surf(x, y, z, cstride=4, cz = True, edgecolor = 'k')
isec(2)
threed('on')
surf(x, y, z, cz = True, cdata = y, edgecolor = None)
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 plot_tiles():
'''
line plot of tile data
'''
x, y, z = read_tile_data()
figure()
threed('on')
plot(x, y, z)
def plot_tiles():
'''
line plot of tile data
'''
x, y, z = read_tile_data()
figure()
threed('on')
plot(x, y, z)
def image_demo(): from ifigure.interactive import image, figure x = np.linspace(-5, 5, 41) y = np.linspace(-5, 5, 41) X, Y = np.meshgrid(x, y) r = np.sqrt(X*X + Y*Y) z = np.cos(r/10.*6*3.14)*np.exp(-r/3) figure() image(x, y, z)
def image_demo():
from ifigure.interactive import image, figure
x = np.linspace(-5, 5, 41)
y = np.linspace(-5, 5, 41)
X, Y = np.meshgrid(x, y)
r = np.sqrt(X * X + Y * Y)
z = np.cos(r / 10. * 6 * 3.14) * np.exp(-r / 3)
figure()
image(x, y, z)
def surf_demo(**kwargs):
from ifigure.interactive import surf, threed, figure, hold, lighting
figure()
threed('on')
# X = np.arange(-5, 5, 0.25)
# Y = np.arange(-5, 5, 0.25)
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)
lighting(light=0.5, ambient=0.7)
surf(X, Y, Z, cmap='coolwarm', shade='linear', **kwargs)
def surf_demo(**kwargs):
from ifigure.interactive import surf, threed, figure, hold, lighting
figure()
threed('on')
# X = np.arange(-5, 5, 0.25)
# Y = np.arange(-5, 5, 0.25)
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)
lighting(light = 0.5, ambient = 0.7)
surf(X, Y, Z, cmap='coolwarm', shade = 'linear', **kwargs)
def contourf_demo(**kwargs):
import mpl_toolkits.mplot3d.axes3d as axes3d
from ifigure.interactive import contourf, threed, figure
X, Y, Z = axes3d.get_test_data(0.05)
v = figure(gl=True)
threed('on')
contourf(X, Y, Z)
def test_ax():
v = figure()
ax = v.get_axes()
pl = v.plot(np.arange(30))
ret = check_prop_read(ax)
check_prop_write(ax, ret)
def trisurf3d_demo(**kwargs):
from matplotlib import cm
import numpy as np
from ifigure.interactive import figure, threed, trisurf, nsec, isec, lighting
# preparing the data, the same as mplot3d demo
n_angles = 36
n_radii = 8
radii = np.linspace(0.125, 1.0, n_radii)
angles = np.linspace(0, 2 * np.pi, n_angles, endpoint=False)
angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1)
x = np.append(0, (radii * np.cos(angles)).flatten())
y = np.append(0, (radii * np.sin(angles)).flatten())
z = np.sin(-x * y)
v = figure()
nsec(3)
isec(0)
threed('on')
trisurf(x, y, z, cmap=cm.jet, linewidth=0.2, cz=True)
isec(1)
threed('on')
trisurf(x, y, z, linewidth=0.2, color='b')
lighting(light=0.5, ambient=0.5)
isec(2)
threed('on')
trisurf(x,
y,
z * 0,
cmap=cm.jet,
linewidth=0.2,
cz=True,
cdata=z,
edgecolor=None)
def test_ax():
v = figure()
ax = v.get_axes()
pl = v.plot(np.arange(30))
ret = check_prop_read(ax)
check_prop_write(ax, ret)
def open_meshviewer():
viewer = figure(); viewer.threed(True)
viewer.xlabel('x')
viewer.ylabel('y')
viewer.zlabel('z')
w = viewer.attach_to_main()
return w
def trisurf3d_demo(**kwargs):
from matplotlib import cm
import numpy as np
from ifigure.interactive import figure, threed, trisurf , nsec, isec, lighting
# preparing the data, the same as mplot3d demo
n_angles = 36
n_radii = 8
radii = np.linspace(0.125, 1.0, n_radii)
angles = np.linspace(0, 2*np.pi, n_angles, endpoint=False)
angles = np.repeat(angles[...,np.newaxis], n_radii, axis=1)
x = np.append(0, (radii*np.cos(angles)).flatten())
y = np.append(0, (radii*np.sin(angles)).flatten())
z = np.sin(-x*y)
v = figure()
nsec(3)
isec(0)
threed('on')
trisurf(x, y, z, cmap=cm.jet, linewidth=0.2, cz = True)
isec(1)
threed('on')
trisurf(x, y, z, linewidth=0.2, color='b')
lighting(light = 0.5, ambient = 0.5)
isec(2)
threed('on')
trisurf(x, y, z*0, cmap=cm.jet, linewidth=0.2,
cz = True, cdata = z, edgecolor = None)
def contourf_demo(**kwargs):
import mpl_toolkits.mplot3d.axes3d as axes3d
from ifigure.interactive import contourf, threed, figure
X, Y, Z = axes3d.get_test_data(0.05)
v = figure(gl = True)
threed('on')
contourf(X, Y, Z)
def plot_shape(dof, ptx, shape, viewer = None):
try:
viewer.Validate()
except:
from ifigure.interactive import figure
viewer = figure()
ll = shape.shape[1]
n = int(np.ceil(np.sqrt(ll)))
viewer.cls()
viewer.nsec(n, int(np.ceil(float(ll)/float(n))))
for i in range(ll):
x = ptx[:, 0]; y= ptx[:, 1]
viewer.isec(i)
if len(shape.shape) == 3:
viewer.tripcolor(ptx[:,0], ptx[:,1], ptx[:,1]*0)
u=shape[:, i, 0]; v = shape[:, i, 1]
viewer.quiver(x, y, u, v)
else:
viewer.tripcolor(ptx[:,0], ptx[:,1], shape[:,i])
idx = np.where(np.abs(shape[:,i]) < 1e-10)[0]
if len(idx)>0: viewer.plot(ptx[idx,0], ptx[idx,1], 'gs')
viewer.plot([dof[i][0]], [dof[i][1]], 'or')
def _doPlotExpr(self, value):
model = self.parent.model.param.getvar('mfem_model')
if model is None: return
expr = str(value[0])
phys = str(value[3])
use_2dplot = model['Phys'][phys].dim == 1
from petram.utils import eval_expr
try:
engine = self.parent.engine
d = eval_expr(model, engine, expr, value[1], phys=phys)
except:
dialog.showtraceback(parent=self,
txt='Failed to evauate expression',
title='Error',
traceback=traceback.format_exc())
return
from ifigure.interactive import figure
v = figure()
v.update(False)
v.suptitle(expr)
if use_2dplot:
for k in d.keys():
v.plot(d[k][0][:, 0, 0].flatten(), d[k][1][:, 0].flatten())
v.update(True)
else:
from petram.pi.dlg_plot_sol import setup_figure
setup_figure(v, self.GetParent())
for k in d.keys():
v.solid(d[k][0], cz=True, cdata=d[k][1])
v.update(True)
v.view('noclip')
v.lighting(light=0.5)
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 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 trisurf3d_demo2(**kwargs):
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.tri as mtri
from ifigure.interactive import figure
# preparing the data, the same as mplot3d demo
u = (np.linspace(0, 2.0 * np.pi, endpoint=True, num=50) * np.ones(
(10, 1))).flatten()
v = np.repeat(np.linspace(-0.5, 0.5, endpoint=True, num=10),
repeats=50).flatten()
# This is the Mobius mapping, taking a u, v pair and returning an x, y, z
# triple
x = (1 + 0.5 * v * np.cos(u / 2.0)) * np.cos(u)
y = (1 + 0.5 * v * np.cos(u / 2.0)) * np.sin(u)
z = 0.5 * v * np.sin(u / 2.0)
# Triangulate parameter space to determine the triangles
tri = mtri.Triangulation(u, v)
v = figure(gl=True)
v.nsec(2)
v.isec(0)
v.threed('on')
v.trisurf(x, y, z, triangles=tri.triangles, cmap=plt.cm.Spectral, cz=True)
# First create the x and y coordinates of the points.
n_angles = 36
n_radii = 8
min_radius = 0.25
radii = np.linspace(min_radius, 0.95, n_radii)
angles = np.linspace(0, 2 * np.pi, n_angles, endpoint=False)
angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1)
angles[:, 1::2] += np.pi / n_angles
x = (radii * np.cos(angles)).flatten()
y = (radii * np.sin(angles)).flatten()
z = (np.cos(radii) * np.cos(angles * 3.0)).flatten()
# Create the Triangulation; no triangles so Delaunay triangulation created.
triang = mtri.Triangulation(x, y)
# Mask off unwanted triangles.
xmid = x[triang.triangles].mean(axis=1)
ymid = y[triang.triangles].mean(axis=1)
mask = np.where(xmid * xmid + ymid * ymid < min_radius * min_radius, 1, 0)
triang.set_mask(mask)
v.isec(1)
v.threed('on')
v.trisurf(triang,
z,
cmap=plt.cm.CMRmap,
cz=True,
shade='linear',
edgecolor=None)
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 plot_faces(mesh, faces, refine=3, win=None, fc='b'):
if win is None:
win = figure()
data = get_face_data(mesh, faces, refine=3)
for k in data:
ptx_x, ivert_x, iverte_x, attrs_x = data[k]
win.solid(ptx_x, ivert_x, facecolor=fc, array_idx=attrs_x)
win.solid(ptx_x, iverte_x, facecolor='k')
return win
def solid_stl_demo(**kwargs):
from stl import mesh
from ifigure.interactive import solid, figure, threed
import ifigure, os
from os.path import dirname
path = dirname(dirname(dirname(ifigure.__file__)))
mymesh = mesh.Mesh.from_file(os.path.join(path, 'example', 'D_antenna.stl'))
v = figure()
threed('on')
solid(mymesh.vectors, alpha = 0.5, **kwargs)
def revolve_demo(**kwargs):
m = np.linspace(0, np.pi * 2, 30)
r = 1.0 + 0.2 * np.cos(m)
z = 0.25 * np.sin(m)
from ifigure.interactive import revolve, figure, threed
v = figure(gl=True)
threed('on')
revolve(r, z, raxis=[0.5, 1], rtheta=[0, 2 * np.pi / 3])
v.xlim(-1.5, 1.5)
v.ylim(-1.5, 1.5)
v.zlim(-1.5, 1.5)
def solid_stl_demo(**kwargs):
from stl import mesh
from ifigure.interactive import solid, figure, threed
import ifigure, os
from os.path import dirname
path = dirname(dirname(dirname(ifigure.__file__)))
mymesh = mesh.Mesh.from_file(os.path.join(path, 'example',
'D_antenna.stl'))
v = figure()
threed('on')
solid(mymesh.vectors, alpha=0.5, **kwargs)
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 revolve_demo(**kwargs):
m = np.linspace(0, np.pi*2, 30)
r = 1.0 + 0.2*np.cos(m)
z = 0.25 * np.sin(m)
from ifigure.interactive import revolve, figure, threed
v = figure(gl = True)
threed('on')
revolve(r, z, raxis = [0.5, 1], rtheta = [0, 2*np.pi/3])
v.xlim(-1.5, 1.5)
v.ylim(-1.5, 1.5)
v.zlim(-1.5, 1.5)
def trisurf3d_demo2(**kwargs):
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.tri as mtri
from ifigure.interactive import figure
# preparing the data, the same as mplot3d demo
u = (np.linspace(0, 2.0 * np.pi, endpoint=True, num=50) * np.ones((10, 1))).flatten()
v = np.repeat(np.linspace(-0.5, 0.5, endpoint=True, num=10), repeats=50).flatten()
# This is the Mobius mapping, taking a u, v pair and returning an x, y, z
# triple
x = (1 + 0.5 * v * np.cos(u / 2.0)) * np.cos(u)
y = (1 + 0.5 * v * np.cos(u / 2.0)) * np.sin(u)
z = 0.5 * v * np.sin(u / 2.0)
# Triangulate parameter space to determine the triangles
tri = mtri.Triangulation(u, v)
v = figure(gl = True)
v.nsec(2)
v.isec(0)
v.threed('on')
v.trisurf(x, y, z, triangles=tri.triangles, cmap=plt.cm.Spectral, cz = True)
# First create the x and y coordinates of the points.
n_angles = 36
n_radii = 8
min_radius = 0.25
radii = np.linspace(min_radius, 0.95, n_radii)
angles = np.linspace(0, 2*np.pi, n_angles, endpoint=False)
angles = np.repeat(angles[...,np.newaxis], n_radii, axis=1)
angles[:,1::2] += np.pi/n_angles
x = (radii*np.cos(angles)).flatten()
y = (radii*np.sin(angles)).flatten()
z = (np.cos(radii)*np.cos(angles*3.0)).flatten()
# Create the Triangulation; no triangles so Delaunay triangulation created.
triang = mtri.Triangulation(x, y)
# Mask off unwanted triangles.
xmid = x[triang.triangles].mean(axis=1)
ymid = y[triang.triangles].mean(axis=1)
mask = np.where(xmid*xmid + ymid*ymid < min_radius*min_radius, 1, 0)
triang.set_mask(mask)
v.isec(1)
v.threed('on')
v.trisurf(triang, z, cmap=plt.cm.CMRmap, cz = True, shade = 'linear',
edgecolor = None)
def onSlice(self, event):
from ifigure.interactive import figure, plot, nsec, isec, update, title, xlabel, ylabel
if event.mpl_xydata[0] is None: return
for a in self._artists:
axes = a.axes
if axes is None: return
data1, data2 = self.get_slice(event.mpl_xy[0],
event.mpl_xy[1], a)
if data1 is None: continue
if data2 is None: continue
figure()
nsec(2)
ou = update()
isec(0)
plot(data1[0], data1[1])
title('y slice : y = '+str(event.mpl_xydata[1]))
xlabel('x')
isec(1)
plot(data2[0], data2[1])
title('x slice : x = '+str(event.mpl_xydata[0]))
xlabel('y')
update(ou)
def image_video_demo():
from ifigure.interactive import image, figure
x = np.linspace(-5, 5, 41)
y = np.linspace(-5, 5, 41)
X, Y = np.meshgrid(x, y)
z = []
for shift in np.linspace(-2., 2, 10):
r = np.sqrt((X - shift)**2 + Y * Y)
d = np.cos(r / 10. * 6 * 3.14) * np.exp(-r / 3)
z.append(d[np.newaxis, :, :])
z = np.vstack(z)
from ifigure.widgets.video_viewer import VideoViewer
v = figure(viewer=VideoViewer)
v.image(x, y, z)
def image_video_demo():
from ifigure.interactive import image, figure
x = np.linspace(-5, 5, 41)
y = np.linspace(-5, 5, 41)
X, Y = np.meshgrid(x, y)
z = []
for shift in np.linspace(-2., 2, 10):
r = np.sqrt((X-shift)**2 + Y*Y)
d = np.cos(r/10.*6*3.14)*np.exp(-r/3)
z.append(d[np.newaxis, :,:])
z = np.vstack(z)
from ifigure.widgets.video_viewer import VideoViewer
v = figure(viewer = VideoViewer)
v.image(x, y, z)
def plot_inverted(self, evt):
from petram.mesh.mesh_inspect import plot_elements
editor = evt.GetEventObject().GetTopLevelParent()
viewer = editor.GetParent()
mesh = viewer.model.variables.getvar('mesh')
inverted = self._invalid_data[2]
from ifigure.interactive import figure
from petram.mfem_viewer import setup_figure
win = figure()
setup_figure(win)
win.view('noclip')
plot_elements(mesh, inverted, refine=10, win=win)
def _on_scope(self, obj, threed=False):
# print self.getvar('mds_path')
# print self._td.get_full_path(), self._path
from ifigure.interactive import figure
book = figure()
viewer = book.get_root_parent().app.find_bookviewer(book)
p = book.get_page(0)
a = p.get_axes(0)
a.set_3d(threed)
name=a.get_next_name(obj.get_namebase())
a.add_child(name, obj)
obj.realize()
ifigure.events.SendPVAddFigobj(a)
ifigure.events.SendChangedEvent(a, w = viewer.canvas)
def _on_scope(self, obj, threed=False):
# print self.getvar('mds_path')
# print self._td.get_full_path(), self._path
from ifigure.interactive import figure
book = figure()
viewer = book.get_root_parent().app.find_bookviewer(book)
p = book.get_page(0)
a = p.get_axes(0)
a.set_3d(threed)
name = a.get_next_name(obj.get_namebase())
a.add_child(name, obj)
obj.realize()
ifigure.events.SendPVAddFigobj(a)
ifigure.events.SendChangedEvent(a, w=viewer.canvas)
def tripcolor_phasor_demo2(): ''' Example using wave viewer ''' from ifigure.interactive import figure v = np.linspace(0.1, 10, 80) t = np.linspace(0, 3.1415, 80) V, T = np.meshgrid(v,t) x = (V*np.cos(T)).flatten() y = (V*np.sin(T)).flatten() r = np.sqrt(x*x + y*y) z = np.exp(1j*r/10.*6*3.14)*np.exp(-r/3) from ifigure.widgets.wave_viewer import WaveViewer v = figure(viewer = WaveViewer) v.tripcolor(x, y, z)
def tripcolor_phasor_demo2():
'''
Example using wave viewer
'''
from ifigure.interactive import figure
v = np.linspace(0.1, 10, 80)
t = np.linspace(0, 3.1415, 80)
V, T = np.meshgrid(v, t)
x = (V * np.cos(T)).flatten()
y = (V * np.sin(T)).flatten()
r = np.sqrt(x * x + y * y)
z = np.exp(1j * r / 10. * 6 * 3.14) * np.exp(-r / 3)
from ifigure.widgets.wave_viewer import WaveViewer
v = figure(viewer=WaveViewer)
v.tripcolor(x, y, z)
def plot_faces_containing_elements(mesh, faces, refine=5, fcs=None, win=None):
if fcs is None:
fcs = 'bg'
if win is None:
win = figure()
data1, data2 = get_faces_containing_elements_data(mesh,
faces,
refine=refine)
for k in data1:
ptx_x, ivert_x, iverte_x, attrs_x = data1[k]
win.solid(ptx_x, ivert_x, facecolor=fcs[0], array_idx=attrs_x)
win.solid(ptx_x, iverte_x, facecolor='k')
for k in data2:
ptx_x, ivert_x, iverte_x, attrs_x = data2[k]
win.solid(ptx_x, ivert_x, facecolor=fcs[1], array_idx=attrs_x)
win.solid(ptx_x, iverte_x, facecolor='k')
return win
from petram.mfem_viewer import MFEMViewer
if not obj.get_pymodel().has_child('mfembook'):
from ifigure.interactive import figure
v = figure()
v.book.rename('mfembook')
v.book.set_keep_data_in_tree(True)
v.isec(0)
v.threed('on')
v.view('noclip')
v.book.Close()
v.book.move(obj.get_pymodel())
obj.get_pymodel().mfembook.Open(MFEMViewer)
import wx
wx.CallAfter(obj.get_pymodel().mfembook.find_bookviewer().Raise)
def onPlotEq(self, e=None, viewer=None):
self_obj = self.td
if self_obj.getvar0() is None:
return
path = self_obj.get_full_path()
x = self_obj.get_contents("table", "rgrid")
y = self_obj.get_contents("table", "zgrid")
z = self_obj.get_contents("table", "psirz")
try:
xlim = self_obj.get_contents("table", "xlim")
ylim = self_obj.get_contents("table", "ylim")
rb = self_obj.get_contents("table", "rbbbs")
zb = self_obj.get_contents("table", "zbbbs")
fpol = self_obj.get_contents("table", "fpol")
ssimag = self_obj.get_contents("table", "ssimag")
ssibdry = self_obj.get_contents("table", "ssibdry")
btrz = self_obj.get_contents("table", "btrz")
brrz = self_obj.get_contents("table", "brrz")
bzrz = self_obj.get_contents("table", "bzrz")
jtrz = self_obj.get_contents("table", "jtrz")
bnorm = sqrt(btrz**2 + brrz**2 + bzrz**2)
bp = sqrt(brrz**2 + bzrz**2)
bangle = np.arctan2(bp, bnorm)
# isPlasma = self_obj.get_contents("table", "isPlasma")
no_lim_b = False
except:
no_lim_b = True
rmaxis = self_obj.get_contents("table", "rmaxis")
zmaxis = self_obj.get_contents("table", "zmaxis")
if viewer is None:
from ifigure.interactive import figure
plt = figure()
else:
plt = viewer
plt.cls()
plt.update(False)
plt.subplot(4, 3, [0, 1, 2, 3], [4, 5, 6, 7])
plt.isec(4)
plt.image(x, y, z, alpha=0.5)
plt.contour(x, y, z, 30)
if eval('self_obj[:]["table"]["nlim"]') != 0:
plt.plot(xlim, ylim)
if eval('self_obj[:]["table"]["nbbbs"]') != 0:
plt.plot(rb, zb)
plt.xlabel('R')
plt.ylabel('Z')
plt.title('PSI')
if not no_lim_b:
plt.isec(5)
plt.title('B-norm')
plt.image(x, y, bnorm, alpha=0.5)
plt.contour(x, y, bnorm, 30)
if self_obj[:]["table"]["nlim"] > 0:
plt.plot(xlim, ylim)
if self_obj[:]["table"]["nbbbs"] > 0:
plt.plot(rb, zb)
plt.xlabel('R')
plt.ylabel('Z')
plt.isec(0)
pres = self_obj.get_contents("table", "pres")
plt.plot(pres)
plt.title('pressure')
plt.xlabel('flux index')
plt.isec(1)
qpsi = self_obj.get_contents("table", "qpsi")
plt.plot(qpsi)
plt.title('qpsi')
plt.xlabel('flux index')
plt.isec(2)
fpol = self_obj.get_contents("table", "fpol")
plt.plot(fpol)
plt.title('f_pol')
plt.xlabel('flux index')
plt.update(True)
if no_lim_b:
return
from python_lib.analysis.efit_tools import flux_average, npsi2psi, npsi2npsit
npsis = np.linspace(0.02, 0.99, 20)
psis = [npsi2psi(self_obj, npsi) for npsi in npsis]
sqrt_npsit = [np.sqrt(npsi2npsit(self_obj, npsi)) for npsi in npsis]
jtor = [flux_average(x, y, z, rmaxis, zmaxis, jtrz, psi) for psi in psis]
plt.isec(3)
plt.plot(sqrt_npsit, jtor)
plt.title('j_tor')
plt.xlabel('sqrt_toroidal_flux')
plt.update(True)
def plot_tiles2():
x, y, z = read_tile_data()
figure()
threed('on')
plot(x, y, z, facecolor = [1, 0, 0, 1])
def solid_demo(**kwargs):
'''
solid_demo2(cz = True, linewidths = 1.0, edgecolor='red')
solid_demo2(facecolor='b', linewidths = 1.0, edgecolor='red')
'''
from ifigure.interactive import solid, figure, threed, isec, nsec, lighting
import ifigure, os
# preparing the data, the same as mplot3d demo
theta = np.linspace(0, 2.0 * np.pi, endpoint=True, num=50)
r = np.linspace(0.01, 4.0, endpoint=True, num=50)
# This is the Mobius mapping, taking a u, v pair and returning an x, y, z
# triple
THETA, R = np.meshgrid(theta, r)
X = R*np.cos(THETA)
Y = R*np.sin(THETA)
Z = np.exp(- R*R)
import matplotlib.tri as mtri
tri = mtri.Triangulation(X.flatten(), Y.flatten())
# Triangulate parameter space to determine the triangles
if 'cz' in kwargs and kwargs['cz']:
v = np.dstack((tri.x[tri.triangles],
tri.y[tri.triangles],
Z.flatten()[tri.triangles],))
v = np.vstack((tri.x, tri.y, Z.flatten()))
kwargs['cdata'] = 5*Z.flatten()[tri.triangles]
kwargs['cdata'] = 5*Z.flatten()
kwargs['cz'] = True
# or #
v = np.dstack((tri.x[tri.triangles],
tri.y[tri.triangles],
Z.flatten()[tri.triangles],
5 * Z.flatten()[tri.triangles],))
v = np.vstack((tri.x, tri.y, Z.flatten(), 5*Z.flatten()))
elif 'twod' in kwargs and kwargs['twod']:
v = np.dstack((tri.x[tri.triangles],
tri.y[tri.triangles]),)
v = np.vstack((tri.x, tri.y, ))
kwargs.pop('twod')
kwargs['zvalue'] = 1.0
else:
v = np.dstack((tri.x[tri.triangles],
tri.y[tri.triangles],
Z.flatten()[tri.triangles],))
v = np.vstack((tri.x, tri.y, Z.flatten()))
idxset=tri.triangles
v = v.transpose()
print v.shape, idxset.shape
viewer = figure()
nsec(3)
isec(0)
threed('on')
solid(v, idxset, edgecolor = 'k', facecolor = 'b')
lighting(light = 0.5, ambient = 0.5)
isec(1)
threed('on')
solid(v, idxset, cz = True)
lighting(light = 0.5, ambient = 0.5)
isec(2)
threed('on')
solid(v, idxset, cz = True, cdata = v[...,0], shade='linear')
lighting(light = 0.5, ambient = 0.5)
def onPlotMid(self, e=None):
self_obj = self.td
if self_obj.getvar0() is None: return
proj=self_obj.get_root_parent()
from ifigure.interactive import figure
v = figure()
v.nsec(1,5)
path=self_obj.get_full_path()
x = self_obj[:]["table"]["rgrid"]
y = self_obj[:]["table"]["zgrid"]
psi = self_obj[:]["table"]["psirz"]
ssimag = self_obj[:]["table"]["ssimag"]
ssibdry = self_obj[:]["table"]["ssibdry"]
fpol = self_obj[:]["table"]["fpol"]
pprime = self_obj[:]["table"]["pprime"]
ffprim = self_obj[:]["table"]["ffprim"]
pres = self_obj[:]["table"]["pres"]
qpsi = self_obj[:]["table"]["qpsi"]
zmaxis = self_obj[:]["table"]["zmaxis"]
btmid = self_obj[:]["table"]["btmid"]
#brmid = self_obj[:]["table"]["brmid"]
bzmid = self_obj[:]["table"]["bzmid"]
jtmid = self_obj[:]["table"]["jtmid"]
pressmid = self_obj[:]["table"]["pressmid"]
qmid = self_obj[:]["table"]["qmid"]
nr = psi.shape[1]
dr = x[1]-x[0]
dz = y[1]-y[0]
# br = psi[:][j+1]
j=psi.shape[0]/2
psi_mid = psi[:][j]
psi_mid = array([interp(zmaxis, y, psi[:,i]) for i in range(nr)])
v.update(False)
v.isec(0)
obj = v.plot(x,bzmid)
v.title("$B_{\mathrm{tor, z}}\/\mathrm{(T)}$")
obj._name = 'bz'
#obj=FigPlot(x,bzmid)
#axes.add_child('bz', obj)
obj=v.plot(x, btmid)
obj._name = 'bt'
# obj=FigPlot(x,sqrt(bt_mid*bt_mid+br_mid*br_mid+bz_mid*bz_mid))
# axes.add_child('ball', obj)
v.isec(1)
v.title("$J_{\mathrm{tor}}\/\mathrm{(MA/m^2)}$")
obj = v.plot(x,jtmid)
obj._name = 'jtor'
v.isec(2)
v.title("$P\/\mathrm{(MPa)}$")
obj = v.plot(x,pressmid/1e6)
obj._name = 'pres'
v.isec(3)
v.title("$\mathrm{safety\,factor}$")
obj = v.plot(x,qmid)
obj._name = 'qpsi'
v.isec(4)
v.title("pitch angle")
obj = v.plot(x,-np.arctan2(bzmid, btmid)*180/np.pi)
obj._name = 'gamma'
v.update(True)
def onPlotMid(self, e=None):
self_obj = self.td
if self_obj.getvar0() is None:
return
proj = self_obj.get_root_parent()
from ifigure.interactive import figure
v = figure()
v.nsec(1, 5)
path = self_obj.get_full_path()
x = self_obj[:]["table"]["rgrid"]
y = self_obj[:]["table"]["zgrid"]
psi = self_obj[:]["table"]["psirz"]
ssimag = self_obj[:]["table"]["ssimag"]
ssibdry = self_obj[:]["table"]["ssibdry"]
fpol = self_obj[:]["table"]["fpol"]
pprime = self_obj[:]["table"]["pprime"]
ffprim = self_obj[:]["table"]["ffprim"]
pres = self_obj[:]["table"]["pres"]
qpsi = self_obj[:]["table"]["qpsi"]
zmaxis = self_obj[:]["table"]["zmaxis"]
btmid = self_obj[:]["table"]["btmid"]
#brmid = self_obj[:]["table"]["brmid"]
bzmid = self_obj[:]["table"]["bzmid"]
jtmid = self_obj[:]["table"]["jtmid"]
pressmid = self_obj[:]["table"]["pressmid"]
qmid = self_obj[:]["table"]["qmid"]
nr = psi.shape[1]
dr = x[1] - x[0]
dz = y[1] - y[0]
# br = psi[:][j+1]
j = psi.shape[0] // 2
psi_mid = psi[:][j]
psi_mid = array([interp(zmaxis, y, psi[:, i]) for i in range(nr)])
v.update(False)
v.isec(0)
obj = v.plot(x, bzmid)
v.title("$B_{\mathrm{tor, z}}\/\mathrm{(T)}$")
obj._name = 'bz'
# obj=FigPlot(x,bzmid)
#axes.add_child('bz', obj)
obj = v.plot(x, btmid)
obj._name = 'bt'
# obj=FigPlot(x,sqrt(bt_mid*bt_mid+br_mid*br_mid+bz_mid*bz_mid))
# axes.add_child('ball', obj)
v.isec(1)
v.title("$J_{\mathrm{tor}}\/\mathrm{(MA/m^2)}$")
obj = v.plot(x, jtmid)
obj._name = 'jtor'
v.isec(2)
v.title("$P\/\mathrm{(MPa)}$")
obj = v.plot(x, pressmid / 1e6)
obj._name = 'pres'
v.isec(3)
v.title("$\mathrm{safety\,factor}$")
obj = v.plot(x, qmid)
obj._name = 'qpsi'
v.isec(4)
v.title("pitch angle")
obj = v.plot(x, -np.arctan2(bzmid, btmid) * 180 / np.pi)
obj._name = 'gamma'
v.update(True)
def onPlotEq(self, e=None, viewer=None):
self_obj = self.td
if self_obj.getvar0() is None: return
path=self_obj.get_full_path()
x = self_obj.get_contents("table", "rgrid")
y = self_obj.get_contents("table", "zgrid")
z = self_obj.get_contents("table", "psirz")
try:
xlim = self_obj.get_contents("table", "xlim")
ylim = self_obj.get_contents("table", "ylim")
rb = self_obj.get_contents("table", "rbbbs")
zb = self_obj.get_contents("table", "zbbbs")
fpol = self_obj.get_contents("table", "fpol")
ssimag = self_obj.get_contents("table", "ssimag")
ssibdry = self_obj.get_contents("table", "ssibdry")
btrz = self_obj.get_contents("table", "btrz")
brrz = self_obj.get_contents("table", "brrz")
bzrz = self_obj.get_contents("table", "bzrz")
jtrz = self_obj.get_contents("table", "jtrz")
bnorm = sqrt(btrz**2+brrz**2+bzrz**2)
bp = sqrt(brrz**2+bzrz**2)
bangle = np.arctan2(bp, bnorm)
# isPlasma = self_obj.get_contents("table", "isPlasma")
no_lim_b = False
except:
no_lim_b = True
rmaxis = self_obj.get_contents("table", "rmaxis")
zmaxis = self_obj.get_contents("table", "zmaxis")
if viewer is None:
from ifigure.interactive import figure
plt = figure()
else:
plt =viewer
plt.cls()
plt.update(False)
plt.subplot(4, 3,[0,1,2, 3], [4,5, 6, 7])
plt.isec(4)
plt.image(x,y,z, alpha=0.5)
plt.contour(x,y,z,30)
if eval('self_obj[:]["table"]["nlim"]') !=0:
plt.plot(xlim, ylim)
if eval('self_obj[:]["table"]["nbbbs"]') !=0:
plt.plot(rb, zb)
plt.xlabel('R')
plt.ylabel('Z')
plt.title('PSI')
if not no_lim_b:
plt.isec(5)
plt.title('B-norm')
plt.image(x,y, bnorm, alpha=0.5)
plt.contour(x,y,bnorm,30)
if self_obj[:]["table"]["nlim"] > 0:
plt.plot(xlim, ylim)
if self_obj[:]["table"]["nbbbs"] > 0:
plt.plot(rb, zb)
plt.xlabel('R')
plt.ylabel('Z')
plt.isec(0)
pres = self_obj.get_contents("table", "pres")
plt.plot(pres)
plt.title('pressure')
plt.xlabel('flux index')
plt.isec(1)
qpsi = self_obj.get_contents("table", "qpsi")
plt.plot(qpsi)
plt.title('qpsi')
plt.xlabel('flux index')
plt.isec(2)
fpol = self_obj.get_contents("table", "fpol")
plt.plot(fpol)
plt.title('f_pol')
plt.xlabel('flux index')
plt.update(True)
if not no_lim_b: return
from python_lib.analysis.efit_tools import flux_average, npsi2psi, npsi2npsit
npsis = np.linspace(0.02, 0.99, 20)
psis = [npsi2psi(self_obj, npsi) for npsi in npsis]
sqrt_npsit = [np.sqrt(npsi2npsit(self_obj, npsi)) for npsi in npsis]
jtor = [flux_average(x, y, z, rmaxis, zmaxis, jtrz, psi)
for psi in psis]
plt.isec(3)
plt.plot(npsis, jtor)
plt.title('f_pol')
plt.xlabel('sqrt_toroidal_flux')
plt.update(True)
def solid_demo(**kwargs):
'''
solid_demo2(cz = True, linewidths = 1.0, edgecolor='red')
solid_demo2(facecolor='b', linewidths = 1.0, edgecolor='red')
'''
from ifigure.interactive import solid, figure, threed, isec, nsec, lighting
import ifigure, os
# preparing the data, the same as mplot3d demo
theta = np.linspace(0, 2.0 * np.pi, endpoint=True, num=50)
r = np.linspace(0.01, 4.0, endpoint=True, num=50)
# This is the Mobius mapping, taking a u, v pair and returning an x, y, z
# triple
THETA, R = np.meshgrid(theta, r)
X = R * np.cos(THETA)
Y = R * np.sin(THETA)
Z = np.exp(-R * R)
import matplotlib.tri as mtri
tri = mtri.Triangulation(X.flatten(), Y.flatten())
# Triangulate parameter space to determine the triangles
if 'cz' in kwargs and kwargs['cz']:
v = np.dstack((
tri.x[tri.triangles],
tri.y[tri.triangles],
Z.flatten()[tri.triangles],
))
v = np.vstack((tri.x, tri.y, Z.flatten()))
kwargs['cdata'] = 5 * Z.flatten()[tri.triangles]
kwargs['cdata'] = 5 * Z.flatten()
kwargs['cz'] = True
# or #
v = np.dstack((
tri.x[tri.triangles],
tri.y[tri.triangles],
Z.flatten()[tri.triangles],
5 * Z.flatten()[tri.triangles],
))
v = np.vstack((tri.x, tri.y, Z.flatten(), 5 * Z.flatten()))
elif 'twod' in kwargs and kwargs['twod']:
v = np.dstack((tri.x[tri.triangles], tri.y[tri.triangles]), )
v = np.vstack((
tri.x,
tri.y,
))
kwargs.pop('twod')
kwargs['zvalue'] = 1.0
else:
v = np.dstack((
tri.x[tri.triangles],
tri.y[tri.triangles],
Z.flatten()[tri.triangles],
))
v = np.vstack((tri.x, tri.y, Z.flatten()))
idxset = tri.triangles
v = v.transpose()
print v.shape, idxset.shape
viewer = figure()
nsec(3)
isec(0)
threed('on')
solid(v, idxset, edgecolor='k', facecolor='b')
lighting(light=0.5, ambient=0.5)
isec(1)
threed('on')
solid(v, idxset, cz=True)
lighting(light=0.5, ambient=0.5)
isec(2)
threed('on')
solid(v, idxset, cz=True, cdata=v[..., 0], shade='linear')
lighting(light=0.5, ambient=0.5)
self.add_menu(extra_menu, wx.ID_ANY,
"Plot Spectra...",
"plot spectra of panel #1",
self.onPlotSpectra)
self.nsec(2)
self.cls()
self.data = self.AddSignalScript(experiment = exp,
signals = {'y': node},
kind = 'plot')
def onPlotSpectra(self, evt):
try:
p = self.data.get_child(0)
x = p.getvar('x')
y = p.getvar('y')
self.isec(1)
self.spec(x, y)
except:
import traceback
traceback.print_exc()
evt.Skip()
if not obj.get_parent().has_child('mdsscope_extramenu_book'):
v = figure()
v.book.rename('mdsscope_extramenu_book')
v.book.set_keep_data_in_tree(True)
v.book.Close()
obj.get_parent().mdsscope_extramenu_book.Open(MDSScopeExtraMenuGUI)