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Lars Ruthotto committed
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*.pyc
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@@ -128,7 +128,7 @@ class BaseMesh(object):
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def nN():
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doc = "Total number of nodes"
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fget = lambda self: self.n + 1
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fget = lambda self: np.prod(self.n + 1)
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return locals()
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nN = property(**nN())
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@@ -23,7 +23,7 @@ class TensorMesh(BaseMesh, TensorView):
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def __init__(self, h, x0=None):
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super(TensorMesh, self).__init__(np.array([len(x) for x in h]), x0)
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assert len(h) == len(x0), "Dimension mismatch. x0 != len(h)"
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assert len(h) == len(self.x0), "Dimension mismatch. x0 != len(h)"
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for i, h_i in enumerate(h):
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assert type(h_i) == np.ndarray, ("h[%i] is not a numpy array." % i)
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@@ -0,0 +1,166 @@
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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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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):
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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 imageType in ["CC", "N"], "imageType must be 'CC' or 'N'"
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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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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_xticks(self.vectorNx)
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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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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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ax.set_xticks(self.vectorNx)
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ax.set_yticks(self.vectorNy)
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elif self.dim == 3:
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if direction == 'z':
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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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C = np.zeros((nX*self.nCx, nY*self.nCy))
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Ic = I[:].reshape(self.n, order='F')
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nCx = self.nCx
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nCy = self.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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ph = ax.pcolormesh(xx, yy, C.T)
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# Plot the lines
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gx = np.r_[0, np.cumsum(np.kron(np.ones((nX, 1)), np.sum(self.hy)).ravel())]
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gy = np.r_[0, np.cumsum(np.kron(np.ones((nY, 1)), np.sum(self.hx)).ravel())]
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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, 'w-', linewidth=2)
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ax.plot(gyX, gyY, 'w-', linewidth=2)
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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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ax.text((ix+1)*self.vectorNx[-1]-pad,(iy)*self.vectorNy[-1]+pad,
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'#%i'%iz,color='w',verticalalignment='bottom',horizontalalignment='right',size='x-large')
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fig.show()
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return ph
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def plotGrid(self):
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"""Plot the nodal, cell-centered and staggered grids for 1,2 and 3 dimensions."""
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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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fig.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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ax.plot(xn[:, 0], xn[:, 1], 'bs')
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ax.plot(xc[:, 0], xc[:, 1], 'ro')
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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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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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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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ax.plot(xn[:, 0], xn[:, 1], 'bs', zs=xn[:, 2])
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ax.plot(xc[:, 0], xc[:, 1], 'ro', zs=xc[:, 2])
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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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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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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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fig.show()
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from TensorMesh import TensorMesh
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@@ -1,96 +0,0 @@
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import numpy as np
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import matplotlib.pyplot as plt
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from mpl_toolkits.mplot3d import Axes3D
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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):
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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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if np.size(I) == self.n[0]:
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print 'cell-centered image'
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xx = self.gridCC
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ax.plot(xx[0], I, 'ro')
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elif np.size(I) == self.n[0]+1:
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print 'nodal image'
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xx = self.gridN
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ax.plot(xx[0], I, 'bs')
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fig.show()
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def plotGrid(self):
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"""Plot the nodal, cell-centered and staggered grids for 1,2 and 3 dimensions."""
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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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print xn
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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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fig.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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ax.plot(xn[:, 0], xn[:, 1], 'bs')
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ax.plot(xc[:, 0], xc[:, 1], 'ro')
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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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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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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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ax.plot(xn[:, 0], xn[:, 1], 'bs', zs=xn[:, 2])
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ax.plot(xc[:, 0], xc[:, 1], 'ro', zs=xc[:, 2])
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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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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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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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fig.show()
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@@ -0,0 +1,201 @@
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{
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"metadata": {
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"name": "exPlotImage2D"
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},
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"nbformat": 3,
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"nbformat_minor": 0,
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"worksheets": [
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{
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"cells": [
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"import sys\n",
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"sys.path.append('../')\n",
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"\n",
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"from SimPEG import TensorMesh"
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],
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 8
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Test 1D Plots\n",
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"\n",
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"For 1D nodal or cell-centered plots are supported.\n"
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"x0 = np.zeros(1)\n",
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"h = np.random.rand(51)\n",
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"mesh = TensorMesh([h],x0)"
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],
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 9
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"sin = lambda x: np.sin(x)\n",
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"xc = mesh.gridCC\n",
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"xn = mesh.gridN\n",
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"\n",
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"fig = plt.figure(1)\n",
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"fig.clf()\n",
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"ph1 = mesh.plotImage(sin(xc),ax=subplot(111))\n",
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"ph2 = mesh.plotImage(sin(xn),ax=subplot(111),imageType='N')\n"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"output_type": "display_data",
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||||
"png": 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truncated
|
||||
"text": [
|
||||
"<matplotlib.figure.Figure at 0x10b3f14d0>"
|
||||
]
|
||||
}
|
||||
],
|
||||
"prompt_number": 10
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Test 2D Plots\n",
|
||||
"\n",
|
||||
"Plot x and y coordinates of cell-centred points"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"collapsed": false,
|
||||
"input": [
|
||||
"x0 = np.zeros(2)\n",
|
||||
"h1 = np.linspace(.1,.5,3)\n",
|
||||
"h2 = np.linspace(.1,.5,5)\n",
|
||||
"mesh = TensorMesh([h1,h2],x0)"
|
||||
],
|
||||
"language": "python",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"prompt_number": 11
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"collapsed": false,
|
||||
"input": [
|
||||
"fig = plt.figure(1)\n",
|
||||
"fig.clf()\n",
|
||||
"ax1 = subplot(121)\n",
|
||||
"ax2 = subplot(122)\n",
|
||||
"mesh.plotImage(mesh.gridCC[:,0],ax = ax1)\n",
|
||||
"ax1.set_title('x coordinates') \n",
|
||||
"mesh.plotImage(mesh.gridCC[:,1],ax = ax2)\n",
|
||||
"ax2.set_title('y coordinates') "
|
||||
],
|
||||
"language": "python",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "pyout",
|
||||
"prompt_number": 12,
|
||||
"text": [
|
||||
"<matplotlib.text.Text at 0x10b3d0f90>"
|
||||
]
|
||||
},
|
||||
{
|
||||
"output_type": "display_data",
|
||||
"png": 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truncated
|
||||
"text": [
|
||||
"<matplotlib.figure.Figure at 0x10ac769d0>"
|
||||
]
|
||||
}
|
||||
],
|
||||
"prompt_number": 12
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Test 3D Plots\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"collapsed": false,
|
||||
"input": [
|
||||
"x0 = np.zeros(3)\n",
|
||||
"h1 = np.linspace(.1,.5,3)\n",
|
||||
"h1 = np.r_[1,2,1]\n",
|
||||
"h2 = np.r_[1,3]\n",
|
||||
"h3 = np.linspace(.1,.5,5)\n",
|
||||
"\n",
|
||||
"mesh = TensorMesh([h1,h2,h3],x0)"
|
||||
],
|
||||
"language": "python",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"prompt_number": 1
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"collapsed": false,
|
||||
"input": [
|
||||
"ax1 = ax=subplot(131)\n",
|
||||
"ax2 = ax=subplot(132)\n",
|
||||
"ax3 = ax=subplot(133)\n",
|
||||
"a1 = mesh.plotImage(mesh.gridCC[:,0],ax=ax1)\n",
|
||||
"a2 = mesh.plotImage(mesh.gridCC[:,1],ax=ax2)\n",
|
||||
"a3 = mesh.plotImage(mesh.gridCC[:,2],ax=ax3)\n",
|
||||
"\n",
|
||||
"ax1.set_title('x coordinate')\n",
|
||||
"ax2.set_title('y coordinate')\n",
|
||||
"ax3.set_title('z coordinate')\n"
|
||||
],
|
||||
"language": "python",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "stream",
|
||||
"stream": "stderr",
|
||||
"text": [
|
||||
"/Users/larsruthotto/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/matplotlib/figure.py:362: UserWarning: matplotlib is currently using a non-GUI backend, so cannot show the figure\n",
|
||||
" \"matplotlib is currently using a non-GUI backend, \"\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"output_type": "pyout",
|
||||
"prompt_number": 2,
|
||||
"text": [
|
||||
"<matplotlib.text.Text at 0x10cc8ab10>"
|
||||
]
|
||||
},
|
||||
{
|
||||
"output_type": "display_data",
|
||||
"png": 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truncated
|
||||
"text": [
|
||||
"<matplotlib.figure.Figure at 0x10c7671d0>"
|
||||
]
|
||||
}
|
||||
],
|
||||
"prompt_number": 2
|
||||
}
|
||||
],
|
||||
"metadata": {}
|
||||
}
|
||||
]
|
||||
}
|
||||
Reference in new issue
Block a user