1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
|
import math, random
import spmatrix
import pysparse_version
def bytesToString(n):
if n < 1024:
return '%d Bytes' % n
n /= 1024.0
if n < 1024:
return '%.1f Kbytes' % n
n /= 1024.0
if n < 1024:
return '%.1f Mbytes' % n
n /= 1024.0
return '%.1f Gbytes' % n
def printInfo(mat, name):
if type(mat) == spmatrix.LLMatType:
if mat.issym:
typeName = 'LL symmetric'
else:
typeName = 'LL general'
storage = bytesToString(4*mat.shape[0] + 16*mat.nnz)
elif type(mat) == spmatrix.SSSMatType:
typeName = 'SSS'
storage = bytesToString(12*mat.shape[0] + 12*(mat.nnz - mat.shape[0]))
elif type(mat) == spmatrix.CSRMatType:
typeName = 'CSR'
storage = bytesToString(4*mat.shape[0] + 12*mat.nnz)
else:
typeName = 'Unknown'
storage = 'Unknown'
print 'Matrix statistics:'
print '%-20s: %s' % ('name', name)
print '%-20s: %s' % ('type', typeName)
print '%-20s: %dx%d' % ('dimensions', mat.shape[0], mat.shape[1])
print '%-20s: %d' % ('#non-zeros', mat.nnz)
print '%-20s: %s' % ('storage', storage)
print
def ll_mat_rand(n, m, density):
"""return a ll_mat object representing a general n-by-m sparse matrix filled with random non-zero values
The number of non-zero entries is less or equal than
n*m*density. The values of the non-zero entries are in the range
[0.0, 1.0)."""
nnz = int(density*n*m)
A = spmatrix.ll_mat(n, m, nnz)
for k in xrange(nnz):
i = random.randrange(n)
j = random.randrange(m)
A[i, j] = random.random()
return A
def exportVtk(mat, fileName):
"export matrix to a VTK data file"
print 'Write VTK file...'
# write VTK file
f = open(fileName, 'w')
f.write('# vtk DataFile Version 3.0\n')
comment = 'generated using pysparse-%s\n' % (pysparse_version.version, )
f.write(comment[:256])
f.write('ASCII\n\n')
f.write('DATASET STRUCTURED_POINTS\n')
f.write('DIMENSIONS %d %d 1\n' % (mat.shape[0], mat.shape[1]))
f.write('ORIGIN 1 1 1\n')
f.write('SPACING 1 1 1\n\n')
f.write('\nPOINT_DATA %d\n' % (mat.shape[0]*mat.shape[1]))
f.write('SCALARS entries float\n')
f.write('LOOKUP_TABLE default\n\n')
for i in xrange(mat.shape[0]):
for j in xrange(mat.shape[1]):
v = mat[i,j]
if v <> 0.0:
v = math.log(math.fabs(v))
f.write('%lf\n' % v)
f.close()
def viewVtk(mat):
import vtk
imageData = vtk.vtkImageData()
imageData.SetDimensions(mat.shape[0], mat.shape[1], 1)
imageData.SetScalarTypeToUnsignedShort()
imageData.SetNumberOfScalarComponents(1)
imageData.AllocateScalars()
viewer = vtk.vtkImageViewer()
viewer.SetInput(imageData)
viewer.SetZSlice(0)
iren = vtk.vtkRenderWindowInteractor()
iren.SetRenderWindow(viewer.GetRenderWindow())
iren.Initialize()
iren.Start()
imageData = vtk.vtkImageSinusoidSource()
imageData.SetWholeExtent(0, 300, 0, 300, 0, 10)
imageData.SetAmplitude(63)
imageData.SetDirection(1, 1, 0)
imageData.SetPeriod(25)
viewer = vtk.vtkImageViewer()
viewer.SetInput(imageData.GetOutput())
viewer.SetColorWindow(126)
viewer.SetColorLevel(0)
viewer.SetZSlice(0)
def hamschti(obj, event):
print 'Haam:'
print obj
print event
iren = vtk.vtkRenderWindowInteractor()
iren.SetRenderWindow(viewer.GetRenderWindow())
iren.Initialize()
interactor = vtk.vtkInteractorStyleImage()
##interactor.AddObserver('LeftButtonPressEvent', hamschti)
iren.SetInteractorStyle(interactor)
iren.Start()
|
