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Merge branch 'startupScripts' of https://github.com/simpeg/simpeg into develop
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#!/usr/bin/python
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"""
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Input and output functions.
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"""
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import os as _os
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import errno as _errno
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import sys as _sys
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import numpy as _np
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from petsc4py import PETSc as _PETSc
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import fileinput as _fl
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def vecToArray(obj):
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""" Converts a PETSc vector to a numpy array, available on *all* MPI nodes.
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Args:
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obj (petsc4py.PETSc.Vec): input vector.
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Returns:
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numpy.array :
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"""
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# scatter vector 'obj' to all processes
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comm = obj.getComm()
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scatter, obj0 = _PETSc.Scatter.toAll(obj)
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scatter.scatter(obj, obj0, False, _PETSc.Scatter.Mode.FORWARD)
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return _np.asarray(obj0)
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# deallocate
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comm.barrier()
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scatter.destroy()
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obj0.destroy()
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def vecToArray0(obj):
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""" Converts a PETSc vector to a numpy array available on MPI node 0.
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Args:
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obj (petsc4py.PETSc.Vec): input vector.
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Returns:
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numpy.array :
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"""
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# scatter vector 'obj' to process 0
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comm = obj.getComm()
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rank = comm.getRank()
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scatter, obj0 = _PETSc.Scatter.toZero(obj)
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scatter.scatter(obj, obj0, False, _PETSc.Scatter.Mode.FORWARD)
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if rank == 0: return _np.asarray(obj0)
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# deallocate
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comm.barrier()
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scatter.destroy()
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obj0.destroy()
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def arrayToVec(vecArray):
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""" Converts a (global) array to a PETSc vector over :attr:`petsc4py.PETSc.COMM_WORLD`.
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Args:
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vecArray (array or numpy.array): input vector.
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Returns:
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petsc4py.PETSc.Vec() :
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"""
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vec = _PETSc.Vec().create(comm=_PETSc.COMM_WORLD)
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vec.setSizes(len(vecArray))
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vec.setUp()
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(Istart,Iend) = vec.getOwnershipRange()
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return vec.createWithArray(vecArray[Istart:Iend],
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comm=_PETSc.COMM_WORLD)
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vec.destroy()
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def arrayToMat(matArray):
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""" Converts a (global) 2D array to a PETSc matrix over :attr:`petsc4py.PETSc.COMM_WORLD`.
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Args:
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matArray (array or numpy.array): input square array.
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:rtype: petsc4py.PETSc.Mat()
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.. important::
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Requires `SciPy <http://www.scipy.org>`_.
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"""
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try:
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import scipy.sparse as sparse
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except:
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print '\nERROR: loading matrices from txt files requires Scipy!'
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return
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matSparse =matArray
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mat = _PETSc.Mat().createAIJ(size=matSparse.shape,comm=_PETSc.COMM_WORLD)
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(Istart,Iend) = mat.getOwnershipRange()
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ai = matSparse.indptr[Istart:Iend+1] - matSparse.indptr[Istart]
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aj = matSparse.indices[matSparse.indptr[Istart]:matSparse.indptr[Iend]]
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av = matSparse.data[matSparse.indptr[Istart]:matSparse.indptr[Iend]]
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mat.setValuesCSR(ai,aj,av)
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mat.assemble()
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return mat
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mat.destroy()
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def matToSparse(mat):
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""" Converts a PETSc matrix to a (global) sparse matrix.
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Args:
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mat (petsc4py.PETSc.Mat): input PETSc matrix.
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:rtype: scipy.sparse.csr_matrix
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.. important::
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Requires `SciPy <http://www.scipy.org>`_.
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"""
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import scipy.sparse as sparse
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data = mat.getValuesCSR()
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(Istart,Iend) = mat.getOwnershipRange()
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columns = mat.getSize()[0]
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sparseSubMat = sparse.csr_matrix(data[::-1],shape=(Iend-Istart,columns))
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comm = _PETSc.COMM_WORLD
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sparseSubMat = comm.tompi4py().allgather(sparseSubMat)
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return sparse.vstack(sparseSubMat)
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def adjToH(adj,d=[0],amp=[0.]):
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""" Creates a 1 particle PETSc-type Hamiltonian matrix from a PETSc adjacency matrix.
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Args:
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adj (petsc4py.PETSc.Mat): input PETSc-type adjacency matrix.
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d (array of ints): an array containing *integers* indicating the nodes
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where diagonal defects are to be placed (e.g. ``d=[0,1,4]``).
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amp (array of floats): an array containing *floats* indicating the diagonal defect
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amplitudes corresponding to each element in ``d`` (e.g. ``amp=[0.5,-1,4.2]``).
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Returns:
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: 1 particle Hamiltonian matrix
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:rtype: petsc4py.PETSc.Mat()
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Warning:
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* The size of ``a`` and ``d`` must be identical
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>>> amp = [0.5,-1.,4.2]
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>>> len(d) == len(amp)
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True
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* Elements of ``d`` can range from :math:`[0,N-1]` where the adjacency matrix is :math:`N\\times N`.
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"""
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(Istart,Iend) = adj.getOwnershipRange()
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diagSum = []
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for i in range(Istart,Iend):
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diagSum.append(_np.sum(adj.getRow(i)[-1]))
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for j,val in enumerate(d):
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if i==val: diagSum[i-Istart] += amp[j]
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mat = _PETSc.Mat().create(comm=_PETSc.COMM_WORLD)
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mat.setSizes(adj.getSize())
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mat.setUp()
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for i in range(Istart,Iend):
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mat.setValue(i,i,diagSum[i-Istart])
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mat.assemble()
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mat.axpy(-1,adj)
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return mat
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mat.destroy()
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#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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#---------------------- Vec I/O functions ---------------------------
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#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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def exportVec(vec,filename,filetype):
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""" Export a PETSc vector to a file.
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Args:
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vec (petsc4py.PETSc.Vec): input vector.
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filename (str): path to desired output file.
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filetype (str): the filetype of the exported vector.
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* ``'txt'`` - a column vector in text format.
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* ``'bin'`` - a PETSc binary vector.
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"""
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if _os.path.isabs(filename):
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outDir = _os.path.dirname(filename)
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else:
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outDir = './'+_os.path.dirname(filename)
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# create output directory if it doesn't exist
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try:
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_os.mkdir(outDir)
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except OSError as exception:
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if exception.errno != _errno.EEXIST:
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raise
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if filetype == 'txt':
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# scatter prob to process 0
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comm = vec.getComm()
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rank = comm.getRank()
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scatter, vec0 = _PETSc.Scatter.toZero(vec)
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scatter.scatter(vec, vec0, False, _PETSc.Scatter.Mode.FORWARD)
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# use process 0 to write to text file
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if rank == 0:
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array0 = _np.asarray(vec0)
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with open(filename,'w') as f:
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for i in range(len(array0)):
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f.write('{0: .12e}\n'.format(array0[i]))
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# deallocate
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comm.barrier()
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scatter.destroy()
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vec0.destroy()
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elif filetype == 'bin':
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binSave = _PETSc.Viewer().createBinary(filename, 'w')
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binSave(vec)
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binSave.destroy()
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vec.comm.barrier()
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def loadVec(filename,filetype):
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""" Import a PETSc vector from a file.
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Args:
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filename (str): path to input file.
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filetype (str): the filetype.
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* ``'txt'`` - a column vector in text format.
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* ``'bin'`` - a PETSc binary vector.
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"""
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if filetype == 'txt':
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try:
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vecArray = _np.loadtxt(filename,dtype=_PETSc.ScalarType)
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return arrayToVec(vecArray)
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except:
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print "\nERROR: input state space file " + filename\
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+ " does not exist or is in an incorrect format"
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_sys.exit()
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elif filetype == 'bin':
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binLoad = _PETSc.Viewer().createBinary(filename, 'r')
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try:
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return _PETSc.Vec().load(binLoad)
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except:
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print "\nERROR: input state space file " + filename\
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+ " does not exist or is in an incorrect format"
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_sys.exit()
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binLoad.destroy()
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#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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#---------------------- Mat I/O functions ---------------------------
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#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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def exportMat(mat,filename,filetype,mattype=None):
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""" Export a PETSc matrix to a file.
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Args:
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mat (petsc4py.PETSc.Mat): input matrix.
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filename (str): path to desired output file.
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filetype (str): the filetype of the exported vector.
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* ``'txt'`` - a 2D matrix array in text format.
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* ``'bin'`` - a PETSc binary matrix.
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mattype (str): (``None``,``'adj'``) - if set to ``adj``, only
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integers ``0`` and ``1`` are written. Note
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that this only applied in ``txt`` mode.
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"""
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rank = _PETSc.Comm.Get_rank(_PETSc.COMM_WORLD)
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if _os.path.isabs(filename):
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outDir = _os.path.dirname(filename)
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else:
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outDir = './'+_os.path.dirname(filename)
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# create output directory if it doesn't exist
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try:
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_os.mkdir(outDir)
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except OSError as exception:
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if exception.errno != _errno.EEXIST:
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raise
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if filetype == 'txt':
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txtSave = _PETSc.Viewer().createASCII(filename, 'w',
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format=_PETSc.Viewer.Format.ASCII_DENSE, comm=_PETSc.COMM_WORLD)
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txtSave(mat)
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txtSave.destroy()
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if rank == 0:
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for line in _fl.FileInput(filename,inplace=1):
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if line[2] != 't':
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if mattype == 'adj':
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line = line.replace(" i","j")
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line = line.replace(" -","-")
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line = line.replace("+-","-")
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line = line.replace("0000e+01+0.00000e+00j","")
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line = line.replace(".00000e+00+0.00000e+00j","")
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line = line.replace(".","")
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line = line.replace(" -","\t-")
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line = line.replace(" ","\t")
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line = line.replace(" ","")
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line = line.replace("\t"," ")
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print line,
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else:
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line = line.replace(" i","j")
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line = line.replace(" -","-")
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line = line.replace("+-","-")
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print line,
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elif filetype == 'bin':
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binSave = _PETSc.Viewer().createBinary(filename, 'w', comm=_PETSc.COMM_WORLD)
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binSave(mat)
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binSave.destroy()
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mat.comm.barrier()
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def loadMat(filename,filetype,delimiter=None):
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""" Import a PETSc matrix from a file.
|
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Args:
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filename (str): path to input file.
|
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filetype (str): the filetype.
|
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* ``'txt'`` - a 2D matrix array in text format.
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* ``'bin'`` - a PETSc matrix vector.
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delimiter (str): this is passed to `numpy.genfromtxt\
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<http://docs.scipy.org/doc/numpy/reference/generated/numpy.genfromtxt.html>`_
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in the case of strange delimiters in an imported ``txt`` file.
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"""
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if filetype == 'txt':
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try:
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try:
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if delimiter is None:
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matArray = _np.genfromtxt(filename,dtype=_PETSc.ScalarType)
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else:
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matArray = _np.genfromtxt(filename,dtype=_PETSc.ScalarType,delimiter=delimiter)
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except:
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filefix = []
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for line in _fl.FileInput(filename,inplace=0):
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if line[2] != 't':
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line = line.replace(" i","j")
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line = line.replace(" -","-")
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line = line.replace("+-","-")
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filefix.append(line)
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matArray = _np.genfromtxt(filefix,dtype=_PETSc.ScalarType)
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return arrayToMat(matArray)
|
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except:
|
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print "\nERROR: input state space file " + filename\
|
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+ " does not exist or is in an incorrect format"
|
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_sys.exit()
|
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|
||||
elif filetype == 'bin':
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binLoad = _PETSc.Viewer().createBinary(filename, 'r')
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try:
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return _PETSc.Mat().load(binLoad)
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||||
except:
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print "\nERROR: input state space file " + filename\
|
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+ " does not exist or is in an incorrect format"
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_sys.exit()
|
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binLoad.destroy()
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||||
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def exportVecToMat(vec,filename,filetype):
|
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""" Export a :math:`N^2` element PETSc vector as a :math:`N\\times N` matrix.
|
||||
|
||||
This is useful when wanting to view the full statespace of a 2 particle
|
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quantum walk.
|
||||
|
||||
Args:
|
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vec (petsc4py.PETSc.Vec): input :math:`N^2` element vector.
|
||||
filename (str): path to desired output file.
|
||||
filetype (str): the filetype of the exported vector.
|
||||
|
||||
* ``'txt'`` - an :math:`N\\times N` 2D matrix array in text format.
|
||||
* ``'bin'`` - an :math:`N\\times N` PETSc binary matrix.
|
||||
"""
|
||||
rank = _PETSc.Comm.Get_rank(_PETSc.COMM_WORLD)
|
||||
|
||||
if _os.path.isabs(filename):
|
||||
outDir = _os.path.dirname(filename)
|
||||
else:
|
||||
outDir = './'+_os.path.dirname(filename)
|
||||
|
||||
# create output directory if it doesn't exist
|
||||
try:
|
||||
_os.mkdir(outDir)
|
||||
except OSError as exception:
|
||||
if exception.errno != _errno.EEXIST:
|
||||
raise
|
||||
|
||||
vecArray = vecToArray(vec)
|
||||
matArray = vecArray.reshape([_np.sqrt(vecArray.size),_np.sqrt(vecArray.size)])
|
||||
|
||||
if filetype == 'txt':
|
||||
#if rank == 0: _np.savetxt(filename,matArray)
|
||||
txtSave = _PETSc.Viewer().createASCII(filename, 'w',
|
||||
format=_PETSc.Viewer.Format.ASCII_DENSE, comm=_PETSc.COMM_WORLD)
|
||||
txtSave(arrayToMat(matArray))
|
||||
txtSave.destroy()
|
||||
|
||||
if rank == 0:
|
||||
for line in _fl.FileInput(filename,inplace=1):
|
||||
if line[2] != 't':
|
||||
line = line.replace(" i","j")
|
||||
line = line.replace(" -","-")
|
||||
line = line.replace("+-","-")
|
||||
print line,
|
||||
|
||||
elif filetype == 'bin':
|
||||
binSave = _PETSc.Viewer().createBinary(filename, 'w', comm=_PETSc.COMM_WORLD)
|
||||
binSave(arrayToMat(matArray))
|
||||
binSave.destroy()
|
||||
vec.comm.barrier()
|
||||
|
||||
|
||||
def loadMatToVec(filename,filetype):
|
||||
""" Load a :math:`N\\times N` matrix as a :math:`N^2` element PETSc vector.
|
||||
|
||||
This is useful when wanting to import the full statespace of a 2 particle
|
||||
quantum walk to use for propagation.
|
||||
|
||||
Args:
|
||||
filename (str): path to the input file.
|
||||
filetype (str): the filetype
|
||||
|
||||
* ``'txt'`` - an :math:`N\\times N` 2D matrix array in text format.
|
||||
* ``'bin'`` - **Not yet implemented! Please use a txt \
|
||||
format for this type of import**.
|
||||
"""
|
||||
if filetype == 'txt':
|
||||
try:
|
||||
try:
|
||||
matArray = _np.loadtxt(filename,dtype=_PETSc.ScalarType)
|
||||
except:
|
||||
filefix = []
|
||||
for line in _fl.FileInput(filename,inplace=0):
|
||||
if line[2] != 't':
|
||||
line = line.replace(" i","j")
|
||||
line = line.replace(" -","-")
|
||||
line = line.replace("+-","-")
|
||||
filefix.append(line)
|
||||
|
||||
matArray = _np.loadtxt(filefix,dtype=_PETSc.ScalarType)
|
||||
|
||||
vecArray = matArray.reshape(matArray.shape[0]**2)
|
||||
return arrayToVec(vecArray)
|
||||
except:
|
||||
print "\nERROR: input state space file " + filename\
|
||||
+ " does not exist or is in an incorrect format"
|
||||
_sys.exit()
|
||||
|
||||
elif filetype == 'bin':
|
||||
print '\nERROR: only works for txt storage!'
|
||||
_sys.exit()
|
||||
@@ -0,0 +1,198 @@
|
||||
{
|
||||
"metadata": {
|
||||
"name": ""
|
||||
},
|
||||
"nbformat": 3,
|
||||
"nbformat_minor": 0,
|
||||
"worksheets": [
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"collapsed": false,
|
||||
"input": [
|
||||
"from SimPEG import *\n",
|
||||
"%pylab inline"
|
||||
],
|
||||
"language": "python",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "stream",
|
||||
"stream": "stdout",
|
||||
"text": [
|
||||
"Populating the interactive namespace from numpy and matplotlib\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"prompt_number": 4
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"collapsed": false,
|
||||
"input": [
|
||||
"M = mesh.TensorMesh([20,30]) \n",
|
||||
"A = M.faceDiv*M.faceDiv.T + sp.identity(M.nC)\n",
|
||||
"b = np.random.rand(M.nC)"
|
||||
],
|
||||
"language": "python",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"prompt_number": 35
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"collapsed": false,
|
||||
"input": [
|
||||
"phi = Solver(A).solve(b)\n",
|
||||
"colorbar(M.plotImage(phi))"
|
||||
],
|
||||
"language": "python",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"metadata": {},
|
||||
"output_type": "pyout",
|
||||
"prompt_number": 37,
|
||||
"text": [
|
||||
"<matplotlib.colorbar.Colorbar instance at 0x6c411b8>"
|
||||
]
|
||||
},
|
||||
{
|
||||
"metadata": {},
|
||||
"output_type": "display_data",
|
||||
"png": 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truncated
|
||||
"text": [
|
||||
"<matplotlib.figure.Figure at 0x67e6050>"
|
||||
]
|
||||
}
|
||||
],
|
||||
"prompt_number": 37
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"collapsed": false,
|
||||
"input": [
|
||||
"print np.linalg.norm(A*phi-b)"
|
||||
],
|
||||
"language": "python",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "stream",
|
||||
"stream": "stdout",
|
||||
"text": [
|
||||
"1.5220841846e-13\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"prompt_number": 38
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"collapsed": false,
|
||||
"input": [
|
||||
"import petsc4py\n",
|
||||
"import sys\n",
|
||||
"petsc4py.init(sys.argv)\n",
|
||||
"from petsc4py import PETSc"
|
||||
],
|
||||
"language": "python",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"prompt_number": 39
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"collapsed": false,
|
||||
"input": [
|
||||
"import PETScIO as IO\n",
|
||||
"Apetsc = PETSc.Mat().createAIJ(size=A.shape,csr=(A.indptr, A.indices, A.data))\n",
|
||||
"bpetsc = IO.arrayToVec(b)\n",
|
||||
"xpetsc = IO.arrayToVec(0*b)"
|
||||
],
|
||||
"language": "python",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"prompt_number": 40
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"collapsed": false,
|
||||
"input": [
|
||||
"ksp = PETSc.KSP().create()\n",
|
||||
"pc = PETSc.PC().create()\n",
|
||||
"\n",
|
||||
"ksp.setOperators(Apetsc)\n",
|
||||
"\n",
|
||||
"ksp.setType(ksp.Type.CG)\n",
|
||||
"pc = ksp.getPC()\n",
|
||||
"pc.setType(pc.Type.HYPRE)\n",
|
||||
"ksp.view()\n",
|
||||
"\n",
|
||||
"ksp.solve(bpetsc, xpetsc)\n",
|
||||
"print ksp.its"
|
||||
],
|
||||
"language": "python",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "stream",
|
||||
"stream": "stdout",
|
||||
"text": [
|
||||
"3\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"prompt_number": 76
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"collapsed": false,
|
||||
"input": [
|
||||
"X = IO.vecToArray(xpetsc)\n",
|
||||
"print np.linalg.norm(A*X-b)\n",
|
||||
"M.plotImage(X)"
|
||||
],
|
||||
"language": "python",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "stream",
|
||||
"stream": "stdout",
|
||||
"text": [
|
||||
"0.000199616893249\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"metadata": {},
|
||||
"output_type": "pyout",
|
||||
"prompt_number": 77,
|
||||
"text": [
|
||||
"<matplotlib.collections.QuadMesh at 0x792ae50>"
|
||||
]
|
||||
},
|
||||
{
|
||||
"metadata": {},
|
||||
"output_type": "display_data",
|
||||
"png": "iVBORw0KGgoAAAANSUhEUgAAAYQAAAESCAYAAAD9gqKNAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
|
||||
"text": [
|
||||
"<matplotlib.figure.Figure at 0x77479d0>"
|
||||
]
|
||||
}
|
||||
],
|
||||
"prompt_number": 77
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"collapsed": false,
|
||||
"input": [],
|
||||
"language": "python",
|
||||
"metadata": {},
|
||||
"outputs": []
|
||||
}
|
||||
],
|
||||
"metadata": {}
|
||||
}
|
||||
]
|
||||
}
|
||||
Executable
+145
@@ -0,0 +1,145 @@
|
||||
#! /bin/bash
|
||||
|
||||
locale-gen en_US en_US.UTF-8 hu_HU hu_HU.UTF-8 > output.t
|
||||
dpkg-reconfigure locales >> output.t
|
||||
|
||||
sudo apt-get update >> output.t
|
||||
echo " "
|
||||
echo " "
|
||||
echo " ============================================"
|
||||
echo " | Installing packages form package manager |"
|
||||
echo " ============================================"
|
||||
echo " "
|
||||
echo " "
|
||||
|
||||
sudo apt-get -y install aptitude >> output.t
|
||||
|
||||
packages=(gcc gfortran git libopenmpi-dev python-pip python-dev git flex bison cmake vim cython ipython python-scipy python-numpy python-nose python-pip python-matplotlib python-vtk python-h5py libmumps-ptscotch-4.10.0 libmumps-ptscotch-dev libblas-dev liblapack-dev )
|
||||
|
||||
|
||||
for item in ${packages[*]}
|
||||
do
|
||||
printf " %-30s\n" $item
|
||||
|
||||
done
|
||||
|
||||
for item in ${packages[*]}
|
||||
do
|
||||
tput cuu1
|
||||
done
|
||||
|
||||
for item in ${packages[*]}
|
||||
do
|
||||
sudo aptitude -y install $item >> output.t
|
||||
printf " %-30s %-4s\n" $item done
|
||||
done
|
||||
|
||||
|
||||
echo " "
|
||||
echo " "
|
||||
echo " ====================================="
|
||||
echo " | Installing extra Python libraries |"
|
||||
echo " ====================================="
|
||||
echo " "
|
||||
echo " "
|
||||
|
||||
|
||||
pipPackages=(mpi4py pymumps)
|
||||
|
||||
for item in ${pipPackages[*]}
|
||||
do
|
||||
printf " %-30s\n" $item
|
||||
done
|
||||
|
||||
for item in ${pipPackages[*]}
|
||||
do
|
||||
tput cuu1
|
||||
done
|
||||
|
||||
for item in ${pipPackages[*]}
|
||||
do
|
||||
sudo pip install $item >> output.t
|
||||
printf " %-30s %-4s\n" $item done
|
||||
done
|
||||
|
||||
Upgrade=(scipy numpy ipython)
|
||||
|
||||
for item in ${Upgrade[*]}
|
||||
do
|
||||
printf " %-8s%-7s\n" $item upgrade
|
||||
|
||||
done
|
||||
|
||||
for item in ${Upgrade[*]}
|
||||
do
|
||||
tput cuu1
|
||||
done
|
||||
|
||||
for item in ${Upgrade[*]}
|
||||
do
|
||||
sudo pip install $item --upgrade >> output.t
|
||||
printf " %-8s%-7s %-4s\n" $item upgrade done
|
||||
done
|
||||
|
||||
|
||||
|
||||
echo " "
|
||||
echo " "
|
||||
echo " ====================="
|
||||
echo " | Installing SimPEG |"
|
||||
echo " ====================="
|
||||
echo " "
|
||||
echo " "
|
||||
cd ~
|
||||
|
||||
|
||||
git clone https://github.com/simpeg/simpeg.git >> output.t
|
||||
cd simpeg/SimPEG/
|
||||
python setup.py >> output.t
|
||||
cd ~
|
||||
|
||||
mkdir petsc
|
||||
cd petsc
|
||||
|
||||
echo " "
|
||||
echo " "
|
||||
echo " ===================="
|
||||
echo " | Installing PETSc |"
|
||||
echo " ===================="
|
||||
echo " "
|
||||
echo " "
|
||||
wget http://ftp.mcs.anl.gov/pub/petsc/release-snapshots/petsc-3.4.3.tar.gz
|
||||
|
||||
tar -zxf petsc-3.4.3.tar.gz
|
||||
|
||||
cd petsc-3.4.3
|
||||
|
||||
./configure --with-debugging=no --dowload-mpich=yes --download-blacs=yes --download-f-blas-lapack=yes --download-scalapack=yes --download-mumps=yes --download-ml=yes --download-spooles=yes --download-hypre=yes --dowload-trilinos=yes --download-metis=yes --download-parmetis=yes --download-umfpack=yes --download-ptscotch=yes --download-superlu=yes --download-superlu_dist=yes --download-essl=yes --download-eucild=yes --download-spai=yes --download-mpi4py=yes --download-petsc4py=yes --download-scientificpython=yes
|
||||
|
||||
|
||||
echo "export PETSC_DIR=/home/${USER}/petsc/petsc-3.4.3" >> ~/.bashrc
|
||||
echo "export PETSC_ARCH=arch-linux2-c-opt" >> ~/.bashrc
|
||||
export PETSC_DIR=/home/${USER}/petsc/petsc-3.4.3
|
||||
export PETSC_ARCH=arch-linux2-c-opt
|
||||
. ~/.bashrc
|
||||
|
||||
make PETSC_DIR=/home/${USER}/petsc/petsc-3.4.3 PETSC_ARCH=arch-linux2-c-opt all
|
||||
make PETSC_DIR=/home/${USER}/petsc/petsc-3.4.3 PETSC_ARCH=arch-linux2-c-opt test
|
||||
|
||||
cd ~/petsc
|
||||
echo " "
|
||||
echo " "
|
||||
echo " ======================="
|
||||
echo " | Installing PETSc4PY |"
|
||||
echo " ======================="
|
||||
echo " "
|
||||
echo " "
|
||||
git clone https://bitbucket.org/petsc/petsc4py.git
|
||||
cd petsc4py/
|
||||
python setup.py build >> output.t
|
||||
python setup.py install --prefix=~/petsc >> output.t
|
||||
|
||||
echo "export PYTHONPATH=~/petsc/lib/python2.7/site-packages:/home/$USER/simpeg:${PYTHONPATH}" >> ~/.bashrc
|
||||
|
||||
cd ~
|
||||
source ~/.bashrc
|
||||
Reference in new issue
Block a user