mirror of
https://github.com/wassname/simpeg.git
synced 2026-06-27 21:23:31 +08:00
Rowan Cockett
336 lines
14 KiB
Python
336 lines
14 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 SimPEG.utils import mkvc
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class TensorView(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 plotImage(self, I, imageType='CC', figNum=1,ax=None,direction='z',numbering=True,annotationColor='w',showIt=False):
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"""
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Mesh.plotImage(I)
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Plots scalar fields on the given mesh.
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Input:
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:param numpy.array I: scalar field
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Optional Input:
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:param str imageType: type of image ('CC','N','F','Fx','Fy','Fz','E','Ex','Ey','Ez') or combinations, e.g. ExEy or FxFz
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:param int figNum: number of figure to plot to
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:param matplotlib.axes.Axes ax: axis to plot to
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:param str direction: slice dimensions, 3D only ('x', 'y', 'z')
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:param bool numbering: show numbering of slices, 3D only
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:param str annotationColor: color of annotation, e.g. 'w', 'k', 'b'
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:param bool showIt: call plt.show()
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.. plot:: examples/mesh/plot_image_2D.py
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:include-source:
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.. plot:: examples/mesh/plot_image_3D.py
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:include-source:
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"""
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assert type(I) == np.ndarray, "I must be a numpy array"
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assert type(numbering) == bool, "numbering must be a bool"
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assert direction in ["x", "y","z"], "direction must be either x,y, or z"
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if imageType == 'CC':
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assert I.size == self.nC, "Incorrect dimensions for CC."
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elif imageType == 'N':
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assert I.size == self.nN, "Incorrect dimensions for N."
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elif imageType == 'Fx':
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if I.size != np.prod(self.nFx): I, fy, fz = self.r(I,'F','F','M')
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elif imageType == 'Fy':
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if I.size != np.prod(self.nFy): fx, I, fz = self.r(I,'F','F','M')
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elif imageType == 'Fz':
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if I.size != np.prod(self.nFz): fx, fy, I = self.r(I,'F','F','M')
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elif imageType == 'Ex':
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if I.size != np.prod(self.nEx): I, ey, ez = self.r(I,'E','E','M')
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elif imageType == 'Ey':
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if I.size != np.prod(self.nEy): ex, I, ez = self.r(I,'E','E','M')
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elif imageType == 'Ez':
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if I.size != np.prod(self.nEz): ex, ey, I = self.r(I,'E','E','M')
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elif imageType[0] == 'E':
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plotAll = len(imageType) == 1
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options = {"direction":direction,"numbering":numbering,"annotationColor":annotationColor,"showIt":showIt}
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fig = plt.figure(figNum)
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# Determine the subplot number: 131, 121
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numPlots = 130 if plotAll else len(imageType)/2*10+100
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pltNum = 1
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ex, ey, ez = self.r(I,'E','E','M')
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if plotAll or 'Ex' in imageType:
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ax_x = plt.subplot(numPlots+pltNum)
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self.plotImage(ex, imageType='Ex', ax=ax_x, **options)
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pltNum +=1
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if plotAll or 'Ey' in imageType:
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ax_y = plt.subplot(numPlots+pltNum)
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self.plotImage(ey, imageType='Ey', ax=ax_y, **options)
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pltNum +=1
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if plotAll or 'Ez' in imageType:
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ax_z = plt.subplot(numPlots+pltNum)
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self.plotImage(ez, imageType='Ez', ax=ax_z, **options)
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pltNum +=1
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return
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elif imageType[0] == 'F':
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plotAll = len(imageType) == 1
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options = {"direction":direction,"numbering":numbering,"annotationColor":annotationColor,"showIt":showIt}
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fig = plt.figure(figNum)
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# Determine the subplot number: 131, 121
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numPlots = 130 if plotAll else len(imageType)/2*10+100
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pltNum = 1
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fx, fy, fz = self.r(I,'F','F','M')
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if plotAll or 'Fx' in imageType:
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ax_x = plt.subplot(numPlots+pltNum)
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self.plotImage(fx, imageType='Fx', ax=ax_x, **options)
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pltNum +=1
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if plotAll or 'Fy' in imageType:
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ax_y = plt.subplot(numPlots+pltNum)
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self.plotImage(fy, imageType='Fy', ax=ax_y, **options)
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pltNum +=1
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if plotAll or 'Fz' in imageType:
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ax_z = plt.subplot(numPlots+pltNum)
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self.plotImage(fz, imageType='Fz', ax=ax_z, **options)
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pltNum +=1
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return
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else:
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raise Exception("imageType must be 'CC', 'N','Fx','Fy','Fz','Ex','Ey','Ez'")
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if ax is None:
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fig = plt.figure(figNum)
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fig.clf()
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ax = plt.subplot(111)
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else:
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assert isinstance(ax,matplotlib.axes.Axes), "ax must be an Axes!"
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fig = ax.figure
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if self.dim == 1:
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if imageType == 'CC':
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ph = ax.plot(self.vectorCCx, I, '-ro')
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elif imageType == 'N':
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ph = ax.plot(self.vectorNx, I, '-bs')
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ax.set_xlabel("x")
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ax.axis('tight')
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elif self.dim == 2:
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if imageType == 'CC':
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C = I[:].reshape(self.n, order='F')
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elif imageType == 'N':
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C = I[:].reshape(self.n+1, order='F')
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C = 0.25*(C[:-1, :-1] + C[1:, :-1] + C[:-1, 1:] + C[1:, 1:])
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elif imageType == 'Fx':
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C = I[:].reshape(self.nFx, order='F')
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C = 0.5*(C[:-1, :] + C[1:, :] )
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elif imageType == 'Fy':
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C = I[:].reshape(self.nFy, order='F')
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C = 0.5*(C[:, :-1] + C[:, 1:] )
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elif imageType == 'Ex':
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C = I[:].reshape(self.nEx, order='F')
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C = 0.5*(C[:,:-1] + C[:,1:] )
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elif imageType == 'Ey':
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C = I[:].reshape(self.nEy, order='F')
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C = 0.5*(C[:-1,:] + C[1:,:] )
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ph = ax.pcolormesh(self.vectorNx, self.vectorNy, C.T)
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ax.axis('tight')
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ax.set_xlabel("x")
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ax.set_ylabel("y")
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elif self.dim == 3:
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if direction == 'z':
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# get copy of image and average to cell-centres is necessary
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if imageType == 'CC':
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Ic = I[:].reshape(self.n, order='F')
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elif imageType == 'N':
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Ic = I[:].reshape(self.n+1, order='F')
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Ic = .125*(Ic[:-1,:-1,:-1]+Ic[1:,:-1,:-1] + Ic[:-1,1:,:-1]+ Ic[1:,1:,:-1]+ Ic[:-1,:-1,1:]+Ic[1:,:-1,1:] + Ic[:-1,1:,1:]+ Ic[1:,1:,1:] )
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elif imageType == 'Fx':
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Ic = I[:].reshape(self.nFx, order='F')
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Ic = .5*(Ic[:-1,:,:]+Ic[1:,:,:])
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elif imageType == 'Fy':
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Ic = I[:].reshape(self.nFy, order='F')
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Ic = .5*(Ic[:,:-1,:]+Ic[:,1:,:])
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elif imageType == 'Fz':
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Ic = I[:].reshape(self.nFz, order='F')
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Ic = .5*(Ic[:,:,:-1]+Ic[:,:,1:])
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elif imageType == 'Ex':
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Ic = I[:].reshape(self.nEx, order='F')
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Ic = .25*(Ic[:,:-1,:-1]+Ic[:,1:,:-1]+Ic[:,:-1,1:]+Ic[:,1:,:1])
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elif imageType == 'Ey':
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Ic = I[:].reshape(self.nEy, order='F')
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Ic = .25*(Ic[:-1,:,:-1]+Ic[1:,:,:-1]+Ic[:-1,:,1:]+Ic[1:,:,:1])
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elif imageType == 'Ez':
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Ic = I[:].reshape(self.nEz, order='F')
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Ic = .25*(Ic[:-1,:-1,:]+Ic[1:,:-1,:]+Ic[:-1,1:,:]+Ic[1:,:1,:])
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# determine number oE slices in x and y dimension
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nX = np.ceil(np.sqrt(self.nCz))
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nY = np.ceil(self.nCz/nX)
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# allocate space for montage
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nCx = self.nCx
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nCy = self.nCy
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C = np.zeros((nX*nCx,nY*nCy))
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for iy in range(int(nY)):
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for ix in range(int(nX)):
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iz = ix + iy*nX
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if iz < self.nCz:
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C[ix*nCx:(ix+1)*nCx, iy*nCy:(iy+1)*nCy] = Ic[:, :, iz]
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else:
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C[ix*nCx:(ix+1)*nCx, iy*nCy:(iy+1)*nCy] = np.nan
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C = np.ma.masked_where(np.isnan(C), C)
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xx = np.r_[0, np.cumsum(np.kron(np.ones((nX, 1)), self.hx).ravel())]
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yy = np.r_[0, np.cumsum(np.kron(np.ones((nY, 1)), self.hy).ravel())]
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# Plot the mesh
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ph = ax.pcolormesh(xx, yy, C.T)
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# Plot the lines
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gx = np.arange(nX+1)*(self.vectorNx[-1]-self.x0[0])
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gy = np.arange(nY+1)*(self.vectorNy[-1]-self.x0[1])
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# Repeat and seperate with NaN
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gxX = np.c_[gx, gx, gx+np.nan].ravel()
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gxY = np.kron(np.ones((nX+1, 1)), np.array([0, sum(self.hy)*nY, np.nan])).ravel()
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gyX = np.kron(np.ones((nY+1, 1)), np.array([0, sum(self.hx)*nX, np.nan])).ravel()
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gyY = np.c_[gy, gy, gy+np.nan].ravel()
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ax.plot(gxX, gxY, annotationColor+'-', linewidth=2)
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ax.plot(gyX, gyY, annotationColor+'-', linewidth=2)
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ax.axis('tight')
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if numbering:
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pad = np.sum(self.hx)*0.04
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for iy in range(int(nY)):
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for ix in range(int(nX)):
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iz = ix + iy*nX
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if iz < self.nCz:
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ax.text((ix+1)*(self.vectorNx[-1]-self.x0[0])-pad,(iy)*(self.vectorNy[-1]-self.x0[1])+pad,
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'#%i'%iz,color=annotationColor,verticalalignment='bottom',horizontalalignment='right',size='x-large')
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ax.set_title(imageType)
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if showIt: plt.show()
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return ph
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def plotGrid(self, nodes=False, faces=False, centers=False, edges=False, lines=True, showIt=False):
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"""Plot the nodal, cell-centered and staggered grids for 1,2 and 3 dimensions.
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:param bool nodes: plot nodes
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:param bool faces: plot faces
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:param bool centers: plot centers
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:param bool edges: plot edges
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:param bool lines: plot lines connecting nodes
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:param bool showIt: call plt.show()
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.. plot:: examples/mesh/plot_grid_2D.py
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:include-source:
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.. plot:: examples/mesh/plot_grid_3D.py
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:include-source:
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"""
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if self.dim == 1:
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fig = plt.figure(1)
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fig.clf()
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ax = plt.subplot(111)
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xn = self.gridN
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xc = self.gridCC
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ax.hold(True)
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ax.plot(xn, np.ones(np.shape(xn)), 'bs')
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ax.plot(xc, np.ones(np.shape(xc)), 'ro')
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ax.plot(xn, np.ones(np.shape(xn)), 'k--')
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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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if showIt: plt.show()
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elif 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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xn = self.gridN
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xc = self.gridCC
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xs1 = self.gridFx
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xs2 = self.gridFy
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ax.hold(True)
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if nodes: ax.plot(xn[:, 0], xn[:, 1], 'bs')
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if centers: ax.plot(xc[:, 0], xc[:, 1], 'ro')
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if faces:
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ax.plot(xs1[:, 0], xs1[:, 1], 'g>')
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ax.plot(xs2[:, 0], xs2[:, 1], 'g^')
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# Plot the grid lines
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if lines:
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NN = self.r(self.gridN, 'N', 'N', 'M')
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X1 = np.c_[mkvc(NN[0][0, :]), mkvc(NN[0][self.nCx, :]), mkvc(NN[0][0, :])*np.nan].flatten()
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Y1 = np.c_[mkvc(NN[1][0, :]), mkvc(NN[1][self.nCx, :]), mkvc(NN[1][0, :])*np.nan].flatten()
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X2 = np.c_[mkvc(NN[0][:, 0]), mkvc(NN[0][:, self.nCy]), mkvc(NN[0][:, 0])*np.nan].flatten()
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Y2 = np.c_[mkvc(NN[1][:, 0]), mkvc(NN[1][:, self.nCy]), mkvc(NN[1][:, 0])*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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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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if showIt: plt.show()
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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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xn = self.gridN
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xc = self.gridCC
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xfs1 = self.gridFx
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xfs2 = self.gridFy
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xfs3 = self.gridFz
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xes1 = self.gridEx
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xes2 = self.gridEy
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xes3 = self.gridEz
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ax.hold(True)
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if nodes: ax.plot(xn[:, 0], xn[:, 1], 'bs', zs=xn[:, 2])
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if centers: ax.plot(xc[:, 0], xc[:, 1], 'ro', zs=xc[:, 2])
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if faces:
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ax.plot(xfs1[:, 0], xfs1[:, 1], 'g>', zs=xfs1[:, 2])
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ax.plot(xfs2[:, 0], xfs2[:, 1], 'g<', zs=xfs2[:, 2])
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ax.plot(xfs3[:, 0], xfs3[:, 1], 'g^', zs=xfs3[:, 2])
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if edges:
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ax.plot(xes1[:, 0], xes1[:, 1], 'k>', zs=xes1[:, 2])
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ax.plot(xes2[:, 0], xes2[:, 1], 'k<', zs=xes2[:, 2])
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ax.plot(xes3[:, 0], xes3[:, 1], 'k^', zs=xes3[:, 2])
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# Plot the grid lines
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if lines:
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NN = self.r(self.gridN, 'N', 'N', 'M')
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X1 = np.c_[mkvc(NN[0][0, :, :]), mkvc(NN[0][self.nCx, :, :]), mkvc(NN[0][0, :, :])*np.nan].flatten()
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Y1 = np.c_[mkvc(NN[1][0, :, :]), mkvc(NN[1][self.nCx, :, :]), mkvc(NN[1][0, :, :])*np.nan].flatten()
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Z1 = np.c_[mkvc(NN[2][0, :, :]), mkvc(NN[2][self.nCx, :, :]), mkvc(NN[2][0, :, :])*np.nan].flatten()
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X2 = np.c_[mkvc(NN[0][:, 0, :]), mkvc(NN[0][:, self.nCy, :]), mkvc(NN[0][:, 0, :])*np.nan].flatten()
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Y2 = np.c_[mkvc(NN[1][:, 0, :]), mkvc(NN[1][:, self.nCy, :]), mkvc(NN[1][:, 0, :])*np.nan].flatten()
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Z2 = np.c_[mkvc(NN[2][:, 0, :]), mkvc(NN[2][:, self.nCy, :]), mkvc(NN[2][:, 0, :])*np.nan].flatten()
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X3 = np.c_[mkvc(NN[0][:, :, 0]), mkvc(NN[0][:, :, self.nCz]), mkvc(NN[0][:, :, 0])*np.nan].flatten()
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Y3 = np.c_[mkvc(NN[1][:, :, 0]), mkvc(NN[1][:, :, self.nCz]), mkvc(NN[1][:, :, 0])*np.nan].flatten()
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Z3 = np.c_[mkvc(NN[2][:, :, 0]), mkvc(NN[2][:, :, self.nCz]), mkvc(NN[2][:, :, 0])*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.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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ax.set_zlabel('x3')
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if showIt: plt.show()
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