def setup_openpmd_meshes_group( self, dset ) :
"""
Set the attributes that are specific to the mesh path
Parameter
---------
dset : an h5py.Group object that contains all the mesh quantities
"""
# Field Solver
dset.attrs["fieldSolver"] = np.string_("PSATD")
# Field boundary
dset.attrs["fieldBoundary"] = np.array([
np.string_("reflecting"), np.string_("reflecting"),
np.string_("reflecting"), np.string_("reflecting") ])
# Particle boundary
dset.attrs["particleBoundary"] = np.array([
np.string_("absorbing"), np.string_("absorbing"),
np.string_("absorbing"), np.string_("absorbing") ])
# Current Smoothing
dset.attrs["currentSmoothing"] = np.string_("Binomial")
dset.attrs["currentSmoothingParameters"] = \
np.string_("period=1;numPasses=1;compensator=false")
# Charge correction
dset.attrs["chargeCorrection"] = np.string_("spectral")
dset.attrs["chargeCorrectionParameters"] = np.string_("period=1")
python类string_()的实例源码
def add(x1, x2):
"""
Return element-wise string concatenation for two arrays of str or unicode.
Arrays `x1` and `x2` must have the same shape.
Parameters
----------
x1 : array_like of str or unicode
Input array.
x2 : array_like of str or unicode
Input array.
Returns
-------
add : ndarray
Output array of `string_` or `unicode_`, depending on input types
of the same shape as `x1` and `x2`.
"""
arr1 = numpy.asarray(x1)
arr2 = numpy.asarray(x2)
out_size = _get_num_chars(arr1) + _get_num_chars(arr2)
dtype = _use_unicode(arr1, arr2)
return _vec_string(arr1, (dtype, out_size), '__add__', (arr2,))
def test_from_string_array(self):
A = np.array(asbytes_nested([['abc', 'foo'],
['long ', '0123456789']]))
assert_equal(A.dtype.type, np.string_)
B = np.char.array(A)
assert_array_equal(B, A)
assert_equal(B.dtype, A.dtype)
assert_equal(B.shape, A.shape)
B[0, 0] = 'changed'
assert_(B[0, 0] != A[0, 0])
C = np.char.asarray(A)
assert_array_equal(C, A)
assert_equal(C.dtype, A.dtype)
C[0, 0] = 'changed again'
assert_(C[0, 0] != B[0, 0])
assert_(C[0, 0] == A[0, 0])
def test_ljust(self):
assert_(issubclass(self.A.ljust(10).dtype.type, np.string_))
C = self.A.ljust([10, 20])
assert_array_equal(np.char.str_len(C), [[10, 20], [10, 20], [12, 20]])
C = self.A.ljust(20, asbytes('#'))
assert_array_equal(C.startswith(asbytes('#')), [
[False, True], [False, False], [False, False]])
assert_(np.all(C.endswith(asbytes('#'))))
C = np.char.ljust(asbytes('FOO'), [[10, 20], [15, 8]])
tgt = asbytes_nested([['FOO ', 'FOO '],
['FOO ', 'FOO ']])
assert_(issubclass(C.dtype.type, np.string_))
assert_array_equal(C, tgt)
def test_lstrip(self):
tgt = asbytes_nested([['abc ', ''],
['12345', 'MixedCase'],
['123 \t 345 \0 ', 'UPPER']])
assert_(issubclass(self.A.lstrip().dtype.type, np.string_))
assert_array_equal(self.A.lstrip(), tgt)
tgt = asbytes_nested([[' abc', ''],
['2345', 'ixedCase'],
['23 \t 345 \x00', 'UPPER']])
assert_array_equal(self.A.lstrip(asbytes_nested(['1', 'M'])), tgt)
tgt = [[sixu('\u03a3 '), ''],
['12345', 'MixedCase'],
['123 \t 345 \0 ', 'UPPER']]
assert_(issubclass(self.B.lstrip().dtype.type, np.unicode_))
assert_array_equal(self.B.lstrip(), tgt)
def test_rstrip(self):
assert_(issubclass(self.A.rstrip().dtype.type, np.string_))
tgt = asbytes_nested([[' abc', ''],
['12345', 'MixedCase'],
['123 \t 345', 'UPPER']])
assert_array_equal(self.A.rstrip(), tgt)
tgt = asbytes_nested([[' abc ', ''],
['1234', 'MixedCase'],
['123 \t 345 \x00', 'UPP']
])
assert_array_equal(self.A.rstrip(asbytes_nested(['5', 'ER'])), tgt)
tgt = [[sixu(' \u03a3'), ''],
['12345', 'MixedCase'],
['123 \t 345', 'UPPER']]
assert_(issubclass(self.B.rstrip().dtype.type, np.unicode_))
assert_array_equal(self.B.rstrip(), tgt)
def test_strip(self):
tgt = asbytes_nested([['abc', ''],
['12345', 'MixedCase'],
['123 \t 345', 'UPPER']])
assert_(issubclass(self.A.strip().dtype.type, np.string_))
assert_array_equal(self.A.strip(), tgt)
tgt = asbytes_nested([[' abc ', ''],
['234', 'ixedCas'],
['23 \t 345 \x00', 'UPP']])
assert_array_equal(self.A.strip(asbytes_nested(['15', 'EReM'])), tgt)
tgt = [[sixu('\u03a3'), ''],
['12345', 'MixedCase'],
['123 \t 345', 'UPPER']]
assert_(issubclass(self.B.strip().dtype.type, np.unicode_))
assert_array_equal(self.B.strip(), tgt)
def add(x1, x2):
"""
Return element-wise string concatenation for two arrays of str or unicode.
Arrays `x1` and `x2` must have the same shape.
Parameters
----------
x1 : array_like of str or unicode
Input array.
x2 : array_like of str or unicode
Input array.
Returns
-------
add : ndarray
Output array of `string_` or `unicode_`, depending on input types
of the same shape as `x1` and `x2`.
"""
arr1 = numpy.asarray(x1)
arr2 = numpy.asarray(x2)
out_size = _get_num_chars(arr1) + _get_num_chars(arr2)
dtype = _use_unicode(arr1, arr2)
return _vec_string(arr1, (dtype, out_size), '__add__', (arr2,))
def test_from_string_array(self):
A = np.array(asbytes_nested([['abc', 'foo'],
['long ', '0123456789']]))
assert_equal(A.dtype.type, np.string_)
B = np.char.array(A)
assert_array_equal(B, A)
assert_equal(B.dtype, A.dtype)
assert_equal(B.shape, A.shape)
B[0, 0] = 'changed'
assert_(B[0, 0] != A[0, 0])
C = np.char.asarray(A)
assert_array_equal(C, A)
assert_equal(C.dtype, A.dtype)
C[0, 0] = 'changed again'
assert_(C[0, 0] != B[0, 0])
assert_(C[0, 0] == A[0, 0])
def test_ljust(self):
assert_(issubclass(self.A.ljust(10).dtype.type, np.string_))
C = self.A.ljust([10, 20])
assert_array_equal(np.char.str_len(C), [[10, 20], [10, 20], [12, 20]])
C = self.A.ljust(20, asbytes('#'))
assert_array_equal(C.startswith(asbytes('#')), [
[False, True], [False, False], [False, False]])
assert_(np.all(C.endswith(asbytes('#'))))
C = np.char.ljust(asbytes('FOO'), [[10, 20], [15, 8]])
tgt = asbytes_nested([['FOO ', 'FOO '],
['FOO ', 'FOO ']])
assert_(issubclass(C.dtype.type, np.string_))
assert_array_equal(C, tgt)
def test_lstrip(self):
tgt = asbytes_nested([['abc ', ''],
['12345', 'MixedCase'],
['123 \t 345 \0 ', 'UPPER']])
assert_(issubclass(self.A.lstrip().dtype.type, np.string_))
assert_array_equal(self.A.lstrip(), tgt)
tgt = asbytes_nested([[' abc', ''],
['2345', 'ixedCase'],
['23 \t 345 \x00', 'UPPER']])
assert_array_equal(self.A.lstrip(asbytes_nested(['1', 'M'])), tgt)
tgt = [[sixu('\u03a3 '), ''],
['12345', 'MixedCase'],
['123 \t 345 \0 ', 'UPPER']]
assert_(issubclass(self.B.lstrip().dtype.type, np.unicode_))
assert_array_equal(self.B.lstrip(), tgt)
def test_rstrip(self):
assert_(issubclass(self.A.rstrip().dtype.type, np.string_))
tgt = asbytes_nested([[' abc', ''],
['12345', 'MixedCase'],
['123 \t 345', 'UPPER']])
assert_array_equal(self.A.rstrip(), tgt)
tgt = asbytes_nested([[' abc ', ''],
['1234', 'MixedCase'],
['123 \t 345 \x00', 'UPP']
])
assert_array_equal(self.A.rstrip(asbytes_nested(['5', 'ER'])), tgt)
tgt = [[sixu(' \u03a3'), ''],
['12345', 'MixedCase'],
['123 \t 345', 'UPPER']]
assert_(issubclass(self.B.rstrip().dtype.type, np.unicode_))
assert_array_equal(self.B.rstrip(), tgt)
def test_strip(self):
tgt = asbytes_nested([['abc', ''],
['12345', 'MixedCase'],
['123 \t 345', 'UPPER']])
assert_(issubclass(self.A.strip().dtype.type, np.string_))
assert_array_equal(self.A.strip(), tgt)
tgt = asbytes_nested([[' abc ', ''],
['234', 'ixedCas'],
['23 \t 345 \x00', 'UPP']])
assert_array_equal(self.A.strip(asbytes_nested(['15', 'EReM'])), tgt)
tgt = [[sixu('\u03a3'), ''],
['12345', 'MixedCase'],
['123 \t 345', 'UPPER']]
assert_(issubclass(self.B.strip().dtype.type, np.unicode_))
assert_array_equal(self.B.strip(), tgt)
def preprocess_writing(key, value):
if isinstance(value, dict):
# hack for storing dicts
value = np.array([str(value)])
else:
value = np.array(value)
if value.ndim == 0:
value = np.array([value])
# some output about the data to write
logg.m(key, type(value),
value.dtype, value.dtype.kind, value.shape,
v=6)
# make sure string format is chosen correctly
if value.dtype.kind == 'U':
value = value.astype(np.string_)
return key, value
