def mplfigure(name, kwargs=...):
'''Matplotlib figure context, convenience function.
Returns a :class:`matplotlib.figure.Figure` object suitable for
`object-oriented plotting`_. Upon exit the result is written to the currently
active logger.
.. _`object-oriented plotting`: https://matplotlib.org/gallery/api/agg_oo_sgskip.html
.. requires:: matplotlib
Args
----
name : :class:`str`
The filename of the resulting figure.
**kwargs :
Keyword arguments are passed on unchanged to the constructor of the
:class:`matplotlib.figure.Figure` object.
'''
import matplotlib.figure, matplotlib.backends.backend_agg
fig = matplotlib.figure.Figure(**kwargs)
with log.userfile(name, 'wb') as f:
yield fig
if f:
matplotlib.backends.backend_agg.FigureCanvas(
fig) # sets reference via fig.set_canvas
try:
fig.savefig(f, format=os.path.splitext(name)[1][1:])
finally:
fig.set_canvas(None) # break circular reference
def generate(self):
treelog.user('my message')
with treelog.infofile('test.dat', 'w') as f:
f.write('test1')
with treelog.context('my context'):
with treelog.iter.plain('iter', 'abc') as items:
for c in items:
treelog.info(c)
with treelog.context('empty'):
pass
treelog.error('multiple..\n ..lines')
with treelog.userfile('test.dat', 'wb') as f:
treelog.info('generating')
f.write(b'test2')
self.generate_test()
with treelog.context('context step={}', 0) as format:
treelog.info('foo')
format(1)
treelog.info('bar')
with treelog.errorfile('same.dat', 'wb') as f:
f.write(b'test3')
with treelog.debugfile('dbg.dat', 'wb') as f:
f.write(b'test4')
treelog.debug('dbg')
treelog.warning('warn')
def mplfigure(*args, **kwargs):
'''Matplotlib figure context, convenience function.
Returns a :class:`matplotlib.figure.Figure` object suitable for
`object-oriented plotting`_. Upon exit the result is written to the currently
active logger.
.. _`object-oriented plotting`: https://matplotlib.org/gallery/api/agg_oo_sgskip.html
.. requires:: matplotlib
Args
----
name : :class:`str`
The filename of the resulting figure.
**kwargs :
Keyword arguments are passed on unchanged to the constructor of the
:class:`matplotlib.figure.Figure` object.
'''
import matplotlib.figure, matplotlib.backends.backend_agg
name, = args
fig = matplotlib.figure.Figure(**kwargs)
with log.userfile(name, 'wb') as f:
yield fig
if f:
matplotlib.backends.backend_agg.FigureCanvas(fig) # sets reference via fig.set_canvas
try:
fig.savefig(f, format=os.path.splitext(name)[1][1:])
finally:
fig.set_canvas(None) # break circular reference
def vtk(name, cells, points, kwargs=...):
'''Export data to a VTK file.
This method provides a simple interface to the `VTK file format`_ with a
number of important restrictions:
* Simplex-only. This makes it possible to define the mesh by a combination
of vertex coordinates and a connectivity table.
* Legacy mode. The newer XML based format is more complex and does not
provide benefits within the constraints set by this method.
* Binary mode. This allows for direct output of binary data, which aids
speed, accuracy and file size.
Beyond the mandatory file name, connectivity table, and vertex coordinates,
any additional data sets can be provided as keyword arguments, where the keys
are the names by which the arrays are stored. The data can be either vertex
or point data, with the distinction made based on the length of the array.
.. _`VTK file format`: https://www.vtk.org/VTK/img/file-formats.pdf
Args
----
name : :class:`str`
Destination file name (without vtk extension).
tri : :class:`int` array
Triangulation.
x : :class:`float` array
Vertex coordinates.
**kwargs :
Cell and/or point data
'''
vtkcelltype = {
3: numpy.array(5, dtype='>u4'), # VTK_TRIANGLE
4: numpy.array(10, dtype='>u4')
} # VTK_TETRA
vtkndim = {
1: 'SCALARS {} {} 1\nLOOKUP_TABLE default\n',
2: 'VECTORS {} {}\n',
3: 'TENSORS {} {}\n'
}
vtkdtype = {
numpy.dtype('>i1'): 'char',
numpy.dtype('>u1'): 'unsigned_char',
numpy.dtype('>i2'): 'short',
numpy.dtype('>u2'): 'unsigned_short',
numpy.dtype('>i4'): 'int',
numpy.dtype('>u4'): 'unsigned_int',
numpy.dtype('>f4'): 'float',
numpy.dtype('>f8'): 'double'
}
def vtkarray(
a): # convert to big endian data and zero-pad all axes to length 3
a = numpy.asarray(a)
if any(n > 3 for n in a.shape[1:]):
raise Exception('invalid shape: {}'.format(a.shape))
e = numpy.zeros([len(a)] + [3] * (a.ndim - 1),
dtype='>{0.kind}{0.itemsize}'.format(a.dtype))
if e.dtype not in vtkdtype:
raise Exception('invalid data type: {}'.format(a.dtype))
e[tuple(map(slice, a.shape))] = a
return e
assert cells.ndim == points.ndim == 2
npoints, ndims = points.shape
ncells, nverts = cells.shape
if nverts not in vtkcelltype:
raise Exception('invalid point dimension: {}'.format(ndims))
points = vtkarray(points)
gathered = util.gather((len(array), (name, vtkarray(array)))
for name, array in kwargs.items())
for n, items in gathered:
if n != npoints and n != ncells:
raise Exception(
'data length matches neither points nor cells: {}'.format(
', '.join(dname for dname, array in items)))
t_cells = numpy.empty((ncells, nverts + 1), dtype='>u4')
t_cells[:, 0] = nverts
t_cells[:, 1:] = cells
name_vtk = name + '.vtk'
with log.userfile(name_vtk, 'wb') as vtk:
vtk.write(
b'# vtk DataFile Version 3.0\nvtk output\nBINARY\nDATASET UNSTRUCTURED_GRID\n'
)
vtk.write('POINTS {} {}\n'.format(
npoints, vtkdtype[points.dtype]).encode('ascii'))
points.tofile(vtk)
vtk.write('CELLS {} {}\n'.format(ncells, t_cells.size).encode('ascii'))
t_cells.tofile(vtk)
vtk.write('CELL_TYPES {}\n'.format(ncells).encode('ascii'))
vtkcelltype[nverts].repeat(ncells).tofile(vtk)
for n, items in gathered:
vtk.write('{}_DATA {}\n'.format(
'POINT' if n == npoints else 'CELL', n).encode('ascii'))
for dname, array in items:
vtk.write(vtkndim[array.ndim].format(
dname, vtkdtype[array.dtype]).encode('ascii'))
array.tofile(vtk)
return iter(title, builtins.range(*args))
def enumerate(title, iterable):
warnings.deprecation('log.enumerate is deprecated; use log.iter.percentage instead')
return iter(title, builtins.enumerate(iterable), length=_len(iterable))
def zip(title, *iterables):
warnings.deprecation('log.zip is deprecated; use log.iter.percentage instead')
return iter(title, builtins.zip(*iterables), length=min(map(_len, iterables)))
def count(title, start=0, step=1):
warnings.deprecation('log.count is deprecated; use log.iter.percentage instead')
return iter(title, itertools.count(start, step))
if distutils.version.StrictVersion(treelog.version) >= distutils.version.StrictVersion('1.0b5'):
from treelog import debug, info, user, warning, error, debugfile, infofile, userfile, warningfile, errorfile, context
else:
debug = lambda *args, **kwargs: treelog.debug(*args, **kwargs)
info = lambda *args, **kwargs: treelog.info(*args, **kwargs)
user = lambda *args, **kwargs: treelog.user(*args, **kwargs)
warning = lambda *args, **kwargs: treelog.warning(*args, **kwargs)
error = lambda *args, **kwargs: treelog.error(*args, **kwargs)
debugfile = lambda *args, **kwargs: treelog.debugfile(*args, **kwargs)
infofile = lambda *args, **kwargs: treelog.infofile(*args, **kwargs)
userfile = lambda *args, **kwargs: treelog.userfile(*args, **kwargs)
warningfile = lambda *args, **kwargs: treelog.warningfile(*args, **kwargs)
errorfile = lambda *args, **kwargs: treelog.errorfile(*args, **kwargs)
context = lambda *args, **kwargs: treelog.context(title, *initargs, **initkwargs)
# vim:sw=2:sts=2:et
def vtk(*args, **kwargs):
'''Export data to a VTK file.
This method provides a simple interface to the `VTK file format`_ with a
number of important restrictions:
* Simplex-only. This makes it possible to define the mesh by a combination
of vertex coordinates and a connectivity table.
* Legacy mode. The newer XML based format is more complex and does not
provide benefits within the constraints set by this method.
* Binary mode. This allows for direct output of binary data, which aids
speed, accuracy and file size.
Beyond the mandatory file name, connectivity table, and vertex coordinates,
any additional data sets can be provided as keyword arguments, where the keys
are the names by which the arrays are stored. The data can be either vertex
or point data, with the distinction made based on the length of the array.
.. _`VTK file format`: https://www.vtk.org/VTK/img/file-formats.pdf
Args
----
name : :class:`str`
Destination file name (without vtk extension).
tri : :class:`int` array
Triangulation.
x : :class:`float` array
Vertex coordinates.
**kwargs :
Cell and/or point data
'''
vtkcelltype = {
3: numpy.array( 5, dtype='>u4'), # VTK_TRIANGLE
4: numpy.array(10, dtype='>u4')} # VTK_TETRA
vtkndim = {
1: 'SCALARS {} {} 1\nLOOKUP_TABLE default\n',
2: 'VECTORS {} {}\n',
3: 'TENSORS {} {}\n'}
vtkdtype = {
numpy.dtype('>i1'): 'char', numpy.dtype('>u1'): 'unsigned_char',
numpy.dtype('>i2'): 'short', numpy.dtype('>u2'): 'unsigned_short',
numpy.dtype('>i4'): 'int', numpy.dtype('>u4'): 'unsigned_int',
numpy.dtype('>f4'): 'float', numpy.dtype('>f8'): 'double'}
def vtkarray(a): # convert to big endian data and zero-pad all axes to length 3
a = numpy.asarray(a)
if any(n > 3 for n in a.shape[1:]):
raise Exception('invalid shape: {}'.format(a.shape))
e = numpy.zeros([len(a)] + [3] * (a.ndim-1), dtype='>{0.kind}{0.itemsize}'.format(a.dtype))
if e.dtype not in vtkdtype:
raise Exception('invalid data type: {}'.format(a.dtype))
e[tuple(map(slice, a.shape))] = a
return e
name, cells, points = args
assert cells.ndim == points.ndim == 2
npoints, ndims = points.shape
ncells, nverts = cells.shape
if nverts not in vtkcelltype:
raise Exception('invalid point dimension: {}'.format(ndims))
points = vtkarray(points)
gathered = util.gather((len(array), (name, vtkarray(array))) for name, array in kwargs.items())
for n, items in gathered:
if n != npoints and n != ncells:
raise Exception('data length matches neither points nor cells: {}'.format(', '.join(dname for dname, array in items)))
t_cells = numpy.empty((ncells, nverts+1), dtype='>u4')
t_cells[:,0] = nverts
t_cells[:,1:] = cells
name_vtk = name + '.vtk'
with log.userfile(name_vtk, 'wb') as vtk:
vtk.write(b'# vtk DataFile Version 3.0\nvtk output\nBINARY\nDATASET UNSTRUCTURED_GRID\n')
vtk.write('POINTS {} {}\n'.format(npoints, vtkdtype[points.dtype]).encode('ascii'))
points.tofile(vtk)
vtk.write('CELLS {} {}\n'.format(ncells, t_cells.size).encode('ascii'))
t_cells.tofile(vtk)
vtk.write('CELL_TYPES {}\n'.format(ncells).encode('ascii'))
vtkcelltype[nverts].repeat(ncells).tofile(vtk)
for n, items in gathered:
vtk.write('{}_DATA {}\n'.format('POINT' if n == npoints else 'CELL', n).encode('ascii'))
for dname, array in items:
vtk.write(vtkndim[array.ndim].format(dname, vtkdtype[array.dtype]).encode('ascii'))
array.tofile(vtk)