# Python matplotlib.pyplot.tricontourf() Examples

The following are code examples for showing how to use matplotlib.pyplot.tricontourf(). They are from open source Python projects. You can vote up the examples you like or vote down the ones you don't like.

Example 1
def plot_fnc(m, surf1_idxs, surf2_idxs, x, outs):
def plot_at_pts(idxs, f):
pts_f = np.full(m[0].shape[0], np.nan)
pts_f[m[1][idxs]] = f

pts_f_not_nan = pts_f[np.logical_not(np.isnan(pts_f))]
min_f = np.min(pts_f_not_nan)
max_f = np.max(pts_f_not_nan)

plt.figure()
plt.tricontourf(
m[0][:,0], m[0][:,2], m[1], pts_f,
levels = np.linspace(min_f, max_f, 21),
extend = 'both'
)
plt.colorbar()

for d in range(3):
plot_at_pts(surf2_idxs, x[:,d].reshape((-1,3)))
for o in outs:
plot_at_pts(surf1_idxs, o.reshape(-1,3,3)[:,:,d])
plt.show() 
Example 2
def fem2contour(u):
mesh = u.function_space().mesh()
v2d = dolfin.vertex_to_dof_map(u.function_space())

# extract x and y coordinates of nodes
x = mesh.coordinates()[:,0]
y = mesh.coordinates()[:,1]
triangles = mesh.cells()

# Create triangulation.
triang = mtri.Triangulation(x, y, triangles)

# create array of node values from function
z = u.vector()[v2d]

# Plot the triangulation.
plt.figure()
plt.tricontourf(triang, z)
#plt.triplot(triang, 'k-')
#plt.title('Triangular grid') 
Example 3
def test_tricontour_non_finite_z():
# github issue 10167.
x = [0, 1, 0, 1]
y = [0, 0, 1, 1]
triang = mtri.Triangulation(x, y)
plt.figure()

with pytest.raises(ValueError, match='z array must not contain non-finite '
'values within the triangulation'):
plt.tricontourf(triang, [0, 1, 2, np.inf])

with pytest.raises(ValueError, match='z array must not contain non-finite '
'values within the triangulation'):
plt.tricontourf(triang, [0, 1, 2, -np.inf])

with pytest.raises(ValueError, match='z array must not contain non-finite '
'values within the triangulation'):
plt.tricontourf(triang, [0, 1, 2, np.nan])

with pytest.raises(ValueError, match='z must not contain masked points '
'within the triangulation'):
plt.tricontourf(triang, np.ma.array([0, 1, 2, 3], mask=[1, 0, 0, 0])) 
Example 4
def gauss_fault_slip(pts, fault_tris, gauss_z):
dof_pts = pts[fault_tris]
x = dof_pts[:,:,0]
z = dof_pts[:,:,2]
mean_z = np.mean(z)
slip = np.zeros((fault_tris.shape[0], 3, 3))
# slip[:,:,0] = (1 - np.abs(x)) * (1 - np.abs((z - mean_z) * 2.0))
# slip[:,:,1] = (1 - np.abs(x)) * (1 - np.abs((z - mean_z) * 2.0))
# slip[:,:,2] = (1 - np.abs(x)) * (1 - np.abs((z - mean_z) * 2.0))
slip[:,:,0] = gauss_slip_fnc(x, z, gauss_z)

# slip_pts = np.zeros(pts.shape[0])
# # slip_pts[fault_tris] = np.log10(np.abs(slip[:,:,0]))
# slip_pts[fault_tris] = slip[:,:,0]
# plt.tricontourf(pts[:,0], pts[:,2], fault_tris, slip_pts)
# plt.triplot(pts[:,0], pts[:,2], fault_tris)
# dof_pts = pts[fault_tris]
# plt.xlim([np.min(dof_pts[:,:,0]), np.max(dof_pts[:,:,0])])
# plt.ylim([np.min(dof_pts[:,:,2]), np.max(dof_pts[:,:,2])])
# plt.colorbar()
# plt.show()

# idxs = np.where(pts[:,2] == 0.0)[0]
# idxs = np.intersect1d(idxs, fault_tris.flatten())
# x = pts[idxs,0]
# s = slip_pts[idxs]
# plt.plot(x, s, '.')
# plt.show()
# for I in idxs:
#     tri_idxs, basis_idxs = np.where(fault_tris == I)
#     slip[tri_idxs, basis_idxs,0] = 0.0

return slip 
Example 5
def plot_fnc(triang, f):
levels = np.linspace(np.min(f) - 1e-12, np.max(f) + 1e-12, 21)
cntf = plt.tricontourf(triang, f, levels = levels, cmap = 'RdBu')
plt.tricontour(triang, f, levels = levels, linestyles = 'solid', colors = 'k', linewidths = 0.5)
plt.colorbar(cntf) 
Example 6
def plot_fnc(triang, f):
levels = np.linspace(np.min(f) - 1e-12, np.max(f) + 1e-12, 21)
cntf = plt.tricontourf(triang, f, levels = levels, cmap = 'RdBu')
plt.tricontour(triang, f, levels = levels, linestyles = 'solid', colors = 'k', linewidths = 0.5)
plt.colorbar(cntf) 
Example 7
def plot_surf_disp(m, side, field, name, vmin = None, vmax = None, filename = None, view_R = 1.0, proj = None, latlon_step = 0.5):
fC, R = get_fault_centered_view(m)

if vmin is None:
vmin = np.min(field)
if vmax is None:
vmax = np.max(field)
cmap = 'PuOr_r'
levels = np.linspace(vmin, vmax, 17)

plt.figure(figsize = (10,10))
fault_start_idx = m.get_start('fault')
for i in range(2):
which_tris = np.where(np.logical_or(side[:fault_start_idx] == 0, side[:fault_start_idx] == i + 1))[0]
reduced_m = mesh_fncs.remove_unused_pts((m.pts, m.tris[which_tris]))
soln_vals = np.empty(reduced_m[0].shape[0])
soln_vals[reduced_m[1]] = field[which_tris]

triang = tri.Triangulation(reduced_m[0][:,0], reduced_m[0][:,1], triangles = reduced_m[1])
tri_refi, interp_vals = triang, soln_vals
cntf = plt.tricontourf(tri_refi, interp_vals, cmap = cmap, levels = levels, extend = 'both')
plt.tricontour(
tri_refi, interp_vals, levels = levels,
colors = '#333333', linestyles = 'solid', linewidths = 0.75
)

plot_fault_trace(m)

cbar = plt.colorbar(cntf)
cbar.set_label('$\\text{displacement (m)}$')

map_axis(fC, R, view_R, proj, latlon_step)

plt.title(name)
if filename is not None:
plt.savefig(filename)
plt.show() 
Example 8
def f(idx, filepath):
""" Main rendering function """
plt.figure(figsize=(6, 6))
contour_levels = np.linspace(VMIN, VMAX, 11)
fig = plt.figure(figsize=(7, 7))
ax = plt.subplot(1, 1, 1, aspect=1)
mesh = plt.tricontourf(
pts[:, 0],
pts[:, 1],
tris,
slip_rate_log[idx, :],
contour_levels,
cmap="plasma",
vmin=VMIN,
vmax=VMAX,
extend="both",
)

plot_boundary(tris, outline=False)
plot_whiskers(idx)
plt.gca().set_aspect("equal")
plt.xlabel("x (km)")
plt.ylabel("y (km)")
plt.xticks([0, 400])
plt.yticks([0, 400, 800, 1200])
plt.xlim([np.min(pts[:, 0]) - BUFFER_KM, np.max(pts[:, 0]) + BUFFER_KM])
plt.ylim([np.min(pts[:, 1]) - BUFFER_KM, np.max(pts[:, 1]) + BUFFER_KM])
plt.title(format_title(t[idx]), fontsize=10)

m = plt.cm.ScalarMappable(cmap="plasma")
m.set_array(slip_rate_log)
m.set_clim(VMIN, VMAX)
cbar_axes = fig.add_axes([0.35, 0.1, 0.015, 0.3])
cbar = plt.colorbar(m, boundaries=contour_levels, cax=cbar_axes)
cbar.set_ticks(np.array([-11, -9, -7, -5, -3, -1]))
cbar.set_label("log v")
plt.tight_layout()
plt.savefig(filepath, dpi=300) 
Example 9
def test_tricontourf_decreasing_levels():
# github issue 5477.
x = [0.0, 1.0, 1.0]
y = [0.0, 0.0, 1.0]
z = [0.2, 0.4, 0.6]
plt.figure()
with pytest.raises(ValueError):
plt.tricontourf(x, y, z, [1.0, 0.0]) 
Example 10
 Project: python3_ios   Author: holzschu   File: test_triangulation.py    BSD 3-Clause "New" or "Revised" License 5 votes
def test_tricontourf_decreasing_levels():
# github issue 5477.
x = [0.0, 1.0, 1.0]
y = [0.0, 0.0, 1.0]
z = [0.2, 0.4, 0.6]
plt.figure()
with pytest.raises(ValueError):
plt.tricontourf(x, y, z, [1.0, 0.0]) 
Example 11
def test_tricontourf_decreasing_levels():
# github issue 5477.
x = [0.0, 1.0, 1.0]
y = [0.0, 0.0, 1.0]
z = [0.2, 0.4, 0.6]
plt.figure()
with pytest.raises(ValueError):
plt.tricontourf(x, y, z, [1.0, 0.0]) 
Example 12
def test_tricontourf_decreasing_levels():
# github issue 5477.
x = [0.0, 1.0, 1.0]
y = [0.0, 0.0, 1.0]
z = [0.2, 0.4, 0.6]
plt.figure()
with pytest.raises(ValueError):
plt.tricontourf(x, y, z, [1.0, 0.0]) 
Example 13
def test_tricontourf_decreasing_levels():
# github issue 5477.
x = [0.0, 1.0, 1.0]
y = [0.0, 0.0, 1.0]
z = [0.2, 0.4, 0.6]
plt.figure()
with pytest.raises(ValueError):
plt.tricontourf(x, y, z, [1.0, 0.0]) 
Example 14
 Project: lambda-tensorflow-object-detection   Author: mikylucky   File: test_triangulation.py    GNU General Public License v3.0 5 votes
def test_tricontourf_decreasing_levels():
# github issue 5477.
x = [0.0, 1.0, 1.0]
y = [0.0, 0.0, 1.0]
z = [0.2, 0.4, 0.6]
plt.figure()
with pytest.raises(ValueError):
plt.tricontourf(x, y, z, [1.0, 0.0]) 
Example 15
def plotResult(self, result):
t = self.triangulate()
plt.tricontourf(t, result, 15, cmap=plt.cm.rainbow)
plt.colorbar()
plt.show() 
Example 16
def plotResult(self, result):
t = self.triangulate()
plt.tricontourf(t, result, 15, cmap=plt.cm.rainbow)
plt.colorbar()
plt.show() 
Example 17
def tri_plot(tri, field, title="", levels=12, savefigs=False,
plt_type="contourf", filename="solution_plot.pdf"):
"""Plot contours over triangulation

Parameters
----------
tri : ndarray (float)
Array with number and nodes coordinates:
number coordX coordY BCX BCY
field : ndarray (float)
Array with data to be plotted for each node.
title : string (optional)
Title of the plot.
levels : int (optional)
Number of levels to be used in contourf.
savefigs : bool (optional)
Allow to save the figure.
plt_type : string (optional)
Plot the field as one of the options: pcolor or
contourf
filename : string (optional)
Filename to save the figures.
"""
if plt_type == "pcolor":
disp_plot = plt.tripcolor
elif plt_type == "contourf":
disp_plot = plt.tricontourf
plt.title(title)
plt.colorbar(orientation='vertical')
plt.axis("image")
if savefigs:
plt.savefig(filename) 
Example 18
def plot_contour(nodes, elems, vals,
title=None, clabel=None,
save=None, show=True, latex=False):
""" Contour plot; values given at nodes. """
fig = Figure(title=title, clabel=clabel, save=save, show=show, latex=latex)
fig.colorbar_ax = plt.tricontourf(nodes[:, 0], nodes[:, 1], elems, vals)
return fig 
Example 19
def plot_quiver(nodes, elems, vals, title=None, clabel=None,
save=None, show=True, latex=False):
""" Plots quivers with contour in the background.
Values given at nodes. """
fig = Figure(title=title, subplots=True, clabel=clabel,
save=save, show=show, latex=latex)

vals_norm = np.sqrt(vals[:, 0]**2 + vals[:, 1]**2) + 1e-10
# vals_norm_max = np.max(vals_norm)
fig.colorbar_ax = fig.ax.tricontourf(nodes[:, 0], nodes[:, 1], elems,
vals_norm)
fig.ax.quiver(nodes[:, 0], nodes[:, 1],
vals[:, 0]/vals_norm, vals[:, 1]/vals_norm) 
Example 20
def plot_fields(model, field, which = 'fault', levels = None, cmap = 'seismic',
symmetric_scale = False, ds = None, figsize = None, dims = [0,2],
xlim = None, ylim = None, figscale = (6,5), filepath = None):

field_reshape = field.reshape((model.m.n_tris(which) * 3, -1))
n_fields = field_reshape.shape[1]

if figsize is None:
figsize = (figscale[0] * n_fields,figscale[1])
plt.figure(figsize = figsize)

which_tris = model.m.get_tris(which)
plot_f = dofs_to_pts(model.m.pts, which_tris, model.basis_dim, field_reshape)
which_pts_idxs = np.unique(which_tris)
which_pts = model.m.pts[which_pts_idxs]
for d in (range(n_fields) if ds is None else ds):
plt.subplot(1, n_fields, d + 1)

f_levels = levels
if f_levels is None:
f_levels = get_levels(plot_f[which_pts_idxs,d], symmetric_scale)

# plt.triplot(
#     model.m.pts[:,dims[0]], model.m.pts[:,dims[1]], which_tris
# )
cntf = plt.tricontourf(
model.m.pts[:,dims[0]], model.m.pts[:,dims[1]], which_tris, plot_f[:,d],
cmap = cmap, levels = f_levels, extend = 'both'
)
if xlim is None:
plt.xlim([np.min(which_pts[:,dims[0]]), np.max(which_pts[:,dims[0]])])
else:
plt.xlim(xlim)
if ylim is None:
plt.ylim([np.min(which_pts[:,dims[1]]), np.max(which_pts[:,dims[1]])])
else:
plt.ylim(ylim)
plt.colorbar(cntf)
plt.tight_layout()
if filepath is not None:
plt.savefig(filepath, bbox_inches = 'tight')
plt.show() 
Example 21
def plot_streamlines(nodes, elems, vals, title=None, clabel=None,
save=None, show=True, num_intp=200, density=0.8, latex=False):
""" Plots streamlines with contour in the background.
Values given at nodes. """
fig = Figure(title=title, subplots=True, clabel=clabel,
save=save, show=show, latex=latex)

vals_norm = np.sqrt(vals[:, 0]**2 + vals[:, 1]**2) + 1e-10
# vals_norm_max = np.max(vals_norm)
fig.colorbar_ax = fig.ax.tricontourf(nodes[:, 0], nodes[:, 1], elems,
vals_norm)

Lx = nodes[:, 0].max()-nodes[:, 0].min()
Ly = nodes[:, 1].max()-nodes[:, 1].min()
dx = max(Lx, Ly)/num_intp
Nx = int(Lx/dx)
Ny = int(Ly/dx)

x_i, y_i = np.meshgrid(
np.linspace(dx+nodes[:, 0].min(),
nodes[:, 0].max()-dx, Nx),
np.linspace(dx+nodes[:, 1].min(),
nodes[:, 1].max()-dx, Ny))
triang = mtri.Triangulation(nodes[:, 0], nodes[:, 1], elems)
ux_interp = mtri.LinearTriInterpolator(triang, vals[:, 0])
uy_interp = mtri.LinearTriInterpolator(triang, vals[:, 1])
ux_i = ux_interp(x_i, y_i)
uy_i = uy_interp(x_i, y_i)

ux_i = np.array(ux_i.filled(0.))
uy_i = np.array(uy_i.filled(0.))

u_norm = np.sqrt(ux_i**2 + uy_i**2)

lw = np.zeros_like(ux_i)
lw[:] += 5*u_norm/(u_norm.max() + 1e-10)

linewidth=lw)