mirror of
https://github.com/wassname/simpeg.git
synced 2026-06-28 13:20:13 +08:00
Rowan Cockett
92 lines
4.1 KiB
Python
92 lines
4.1 KiB
Python
import numpy as np
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import matplotlib.pyplot as plt
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import matplotlib
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from mpl_toolkits.mplot3d import Axes3D
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from utils import mkvc
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class LomView(object):
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"""
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Provides viewing functions for TensorMesh
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This class is inherited by TensorMesh
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"""
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def __init__(self):
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pass
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def plotGrid(self, length=0.05):
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"""Plot the nodal, cell-centered and staggered grids for 1,2 and 3 dimensions."""
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NN = self.r(self.gridN, 'N', 'N', 'M')
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if self.dim == 2:
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fig = plt.figure(2)
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fig.clf()
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ax = plt.subplot(111)
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X1 = np.c_[mkvc(NN[0][:-1, :]), mkvc(NN[0][1:, :]), mkvc(NN[0][:-1, :])*np.nan].flatten()
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Y1 = np.c_[mkvc(NN[1][:-1, :]), mkvc(NN[1][1:, :]), mkvc(NN[1][:-1, :])*np.nan].flatten()
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X2 = np.c_[mkvc(NN[0][:, :-1]), mkvc(NN[0][:, 1:]), mkvc(NN[0][:, :-1])*np.nan].flatten()
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Y2 = np.c_[mkvc(NN[1][:, :-1]), mkvc(NN[1][:, 1:]), mkvc(NN[1][:, :-1])*np.nan].flatten()
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X = np.r_[X1, X2]
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Y = np.r_[Y1, Y2]
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plt.plot(X, Y)
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plt.hold(True)
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Nx = self.r(self.normals, 'F', 'Fx', 'V')
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Ny = self.r(self.normals, 'F', 'Fy', 'V')
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Tx = self.r(self.tangents, 'E', 'Ex', 'V')
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Ty = self.r(self.tangents, 'E', 'Ey', 'V')
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plt.plot(self.gridN[:, 0], self.gridN[:, 1], 'bo')
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nX = np.c_[self.gridFx[:, 0], self.gridFx[:, 0] + Nx[0]*length, self.gridFx[:, 0]*np.nan].flatten()
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nY = np.c_[self.gridFx[:, 1], self.gridFx[:, 1] + Nx[1]*length, self.gridFx[:, 1]*np.nan].flatten()
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plt.plot(self.gridFx[:, 0], self.gridFx[:, 1], 'rs')
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plt.plot(nX, nY, 'r-')
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nX = np.c_[self.gridFy[:, 0], self.gridFy[:, 0] + Ny[0]*length, self.gridFy[:, 0]*np.nan].flatten()
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nY = np.c_[self.gridFy[:, 1], self.gridFy[:, 1] + Ny[1]*length, self.gridFy[:, 1]*np.nan].flatten()
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#plt.plot(self.gridFy[:, 0], self.gridFy[:, 1], 'gs')
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plt.plot(nX, nY, 'g-')
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tX = np.c_[self.gridEx[:, 0], self.gridEx[:, 0] + Tx[0]*length, self.gridEx[:, 0]*np.nan].flatten()
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tY = np.c_[self.gridEx[:, 1], self.gridEx[:, 1] + Tx[1]*length, self.gridEx[:, 1]*np.nan].flatten()
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plt.plot(self.gridEx[:, 0], self.gridEx[:, 1], 'r^')
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plt.plot(tX, tY, 'r-')
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nX = np.c_[self.gridEy[:, 0], self.gridEy[:, 0] + Ty[0]*length, self.gridEy[:, 0]*np.nan].flatten()
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nY = np.c_[self.gridEy[:, 1], self.gridEy[:, 1] + Ty[1]*length, self.gridEy[:, 1]*np.nan].flatten()
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#plt.plot(self.gridEy[:, 0], self.gridEy[:, 1], 'g^')
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plt.plot(nX, nY, 'g-')
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plt.axis('equal')
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elif self.dim == 3:
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fig = plt.figure(3)
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fig.clf()
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ax = fig.add_subplot(111, projection='3d')
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X1 = np.c_[mkvc(NN[0][:-1, :, :]), mkvc(NN[0][1:, :, :]), mkvc(NN[0][:-1, :, :])*np.nan].flatten()
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Y1 = np.c_[mkvc(NN[1][:-1, :, :]), mkvc(NN[1][1:, :, :]), mkvc(NN[1][:-1, :, :])*np.nan].flatten()
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Z1 = np.c_[mkvc(NN[2][:-1, :, :]), mkvc(NN[2][1:, :, :]), mkvc(NN[2][:-1, :, :])*np.nan].flatten()
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X2 = np.c_[mkvc(NN[0][:, :-1, :]), mkvc(NN[0][:, 1:, :]), mkvc(NN[0][:, :-1, :])*np.nan].flatten()
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Y2 = np.c_[mkvc(NN[1][:, :-1, :]), mkvc(NN[1][:, 1:, :]), mkvc(NN[1][:, :-1, :])*np.nan].flatten()
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Z2 = np.c_[mkvc(NN[2][:, :-1, :]), mkvc(NN[2][:, 1:, :]), mkvc(NN[2][:, :-1, :])*np.nan].flatten()
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X3 = np.c_[mkvc(NN[0][:, :, :-1]), mkvc(NN[0][:, :, 1:]), mkvc(NN[0][:, :, :-1])*np.nan].flatten()
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Y3 = np.c_[mkvc(NN[1][:, :, :-1]), mkvc(NN[1][:, :, 1:]), mkvc(NN[1][:, :, :-1])*np.nan].flatten()
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Z3 = np.c_[mkvc(NN[2][:, :, :-1]), mkvc(NN[2][:, :, 1:]), mkvc(NN[2][:, :, :-1])*np.nan].flatten()
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X = np.r_[X1, X2, X3]
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Y = np.r_[Y1, Y2, Y3]
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Z = np.r_[Z1, Z2, Z3]
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plt.plot(X, Y, 'b', zs=Z)
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ax.set_zlabel('x3')
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ax.grid(True)
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ax.hold(False)
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ax.set_xlabel('x1')
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ax.set_ylabel('x2')
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fig.show()
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