Python numpy.little_endian() Examples
The following are 10
code examples of numpy.little_endian().
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Example #1
| Source File: netcdf.py From me-ica with GNU Lesser General Public License v2.1 | 5 votes |
|
def _write_var_data(self, name):
var = self.variables[name]
# Set begin in file header.
the_beguine = self.fp.tell()
self.fp.seek(var._begin)
self._pack_begin(the_beguine)
self.fp.seek(the_beguine)
# Write data.
if not var.isrec:
self.fp.write(var.data.tostring())
count = var.data.size * var.data.itemsize
self.fp.write(asbytes('0') * (var._vsize - count))
else: # record variable
# Handle rec vars with shape[0] < nrecs.
if self._recs > len(var.data):
shape = (self._recs,) + var.data.shape[1:]
var.data.resize(shape)
pos0 = pos = self.fp.tell()
for rec in var.data:
# Apparently scalars cannot be converted to big endian. If we
# try to convert a ``=i4`` scalar to, say, '>i4' the dtype
# will remain as ``=i4``.
if not rec.shape and (rec.dtype.byteorder == '<' or
(rec.dtype.byteorder == '=' and LITTLE_ENDIAN)):
rec = rec.byteswap()
self.fp.write(rec.tostring())
# Padding
count = rec.size * rec.itemsize
self.fp.write(asbytes('0') * (var._vsize - count))
pos += self._recsize
self.fp.seek(pos)
self.fp.seek(pos0 + var._vsize)
Example #2
| Source File: netcdf.py From me-ica with GNU Lesser General Public License v2.1 | 5 votes |
|
def _write_values(self, values):
if hasattr(values, 'dtype'):
nc_type = REVERSE[values.dtype.char, values.dtype.itemsize]
else:
types = [
(int, NC_INT),
(long, NC_INT),
(float, NC_FLOAT),
(basestring, NC_CHAR),
]
try:
sample = values[0]
except TypeError:
sample = values
for class_, nc_type in types:
if isinstance(sample, class_): break
typecode, size = TYPEMAP[nc_type]
dtype_ = '>%s' % typecode
values = asarray(values, dtype=dtype_)
self.fp.write(asbytes(nc_type))
if values.dtype.char == 'S':
nelems = values.itemsize
else:
nelems = values.size
self._pack_int(nelems)
if not values.shape and (values.dtype.byteorder == '<' or
(values.dtype.byteorder == '=' and LITTLE_ENDIAN)):
values = values.byteswap()
self.fp.write(values.tostring())
count = values.size * values.itemsize
self.fp.write(asbytes('0') * (-count % 4)) # pad
Example #3
| Source File: netcdf.py From lambda-packs with MIT License | 5 votes |
|
def _write_var_data(self, name):
var = self.variables[name]
# Set begin in file header.
the_beguine = self.fp.tell()
self.fp.seek(var._begin)
self._pack_begin(the_beguine)
self.fp.seek(the_beguine)
# Write data.
if not var.isrec:
self.fp.write(var.data.tostring())
count = var.data.size * var.data.itemsize
self.fp.write(b'0' * (var._vsize - count))
else: # record variable
# Handle rec vars with shape[0] < nrecs.
if self._recs > len(var.data):
shape = (self._recs,) + var.data.shape[1:]
# Resize in-place does not always work since
# the array might not be single-segment
try:
var.data.resize(shape)
except ValueError:
var.__dict__['data'] = np.resize(var.data, shape).astype(var.data.dtype)
pos0 = pos = self.fp.tell()
for rec in var.data:
# Apparently scalars cannot be converted to big endian. If we
# try to convert a ``=i4`` scalar to, say, '>i4' the dtype
# will remain as ``=i4``.
if not rec.shape and (rec.dtype.byteorder == '<' or
(rec.dtype.byteorder == '=' and LITTLE_ENDIAN)):
rec = rec.byteswap()
self.fp.write(rec.tostring())
# Padding
count = rec.size * rec.itemsize
self.fp.write(b'0' * (var._vsize - count))
pos += self._recsize
self.fp.seek(pos)
self.fp.seek(pos0 + var._vsize)
Example #4
| Source File: netcdf.py From Computable with MIT License | 5 votes |
|
def _write_var_data(self, name):
var = self.variables[name]
# Set begin in file header.
the_beguine = self.fp.tell()
self.fp.seek(var._begin)
self._pack_begin(the_beguine)
self.fp.seek(the_beguine)
# Write data.
if not var.isrec:
self.fp.write(var.data.tostring())
count = var.data.size * var.data.itemsize
self.fp.write(b'0' * (var._vsize - count))
else: # record variable
# Handle rec vars with shape[0] < nrecs.
if self._recs > len(var.data):
shape = (self._recs,) + var.data.shape[1:]
var.data.resize(shape)
pos0 = pos = self.fp.tell()
for rec in var.data:
# Apparently scalars cannot be converted to big endian. If we
# try to convert a ``=i4`` scalar to, say, '>i4' the dtype
# will remain as ``=i4``.
if not rec.shape and (rec.dtype.byteorder == '<' or
(rec.dtype.byteorder == '=' and LITTLE_ENDIAN)):
rec = rec.byteswap()
self.fp.write(rec.tostring())
# Padding
count = rec.size * rec.itemsize
self.fp.write(b'0' * (var._vsize - count))
pos += self._recsize
self.fp.seek(pos)
self.fp.seek(pos0 + var._vsize)
Example #5
| Source File: netcdf.py From Computable with MIT License | 5 votes |
|
def _write_values(self, values):
if hasattr(values, 'dtype'):
nc_type = REVERSE[values.dtype.char, values.dtype.itemsize]
else:
types = [(t, NC_INT) for t in integer_types]
types += [
(float, NC_FLOAT),
(str, NC_CHAR),
]
try:
sample = values[0]
except TypeError:
sample = values
for class_, nc_type in types:
if isinstance(sample, class_):
break
typecode, size = TYPEMAP[nc_type]
dtype_ = '>%s' % typecode
values = asarray(values, dtype=dtype_)
self.fp.write(asbytes(nc_type))
if values.dtype.char == 'S':
nelems = values.itemsize
else:
nelems = values.size
self._pack_int(nelems)
if not values.shape and (values.dtype.byteorder == '<' or
(values.dtype.byteorder == '=' and LITTLE_ENDIAN)):
values = values.byteswap()
self.fp.write(values.tostring())
count = values.size * values.itemsize
self.fp.write(b'0' * (-count % 4)) # pad
Example #6
| Source File: netcdf.py From GraphicDesignPatternByPython with MIT License | 5 votes |
|
def _write_var_data(self, name):
var = self.variables[name]
# Set begin in file header.
the_beguine = self.fp.tell()
self.fp.seek(var._begin)
self._pack_begin(the_beguine)
self.fp.seek(the_beguine)
# Write data.
if not var.isrec:
self.fp.write(var.data.tostring())
count = var.data.size * var.data.itemsize
self._write_var_padding(var, var._vsize - count)
else: # record variable
# Handle rec vars with shape[0] < nrecs.
if self._recs > len(var.data):
shape = (self._recs,) + var.data.shape[1:]
# Resize in-place does not always work since
# the array might not be single-segment
try:
var.data.resize(shape)
except ValueError:
var.__dict__['data'] = np.resize(var.data, shape).astype(var.data.dtype)
pos0 = pos = self.fp.tell()
for rec in var.data:
# Apparently scalars cannot be converted to big endian. If we
# try to convert a ``=i4`` scalar to, say, '>i4' the dtype
# will remain as ``=i4``.
if not rec.shape and (rec.dtype.byteorder == '<' or
(rec.dtype.byteorder == '=' and LITTLE_ENDIAN)):
rec = rec.byteswap()
self.fp.write(rec.tostring())
# Padding
count = rec.size * rec.itemsize
self._write_var_padding(var, var._vsize - count)
pos += self._recsize
self.fp.seek(pos)
self.fp.seek(pos0 + var._vsize)
Example #7
| Source File: netcdf.py From Splunking-Crime with GNU Affero General Public License v3.0 | 5 votes |
|
def _write_var_data(self, name):
var = self.variables[name]
# Set begin in file header.
the_beguine = self.fp.tell()
self.fp.seek(var._begin)
self._pack_begin(the_beguine)
self.fp.seek(the_beguine)
# Write data.
if not var.isrec:
self.fp.write(var.data.tostring())
count = var.data.size * var.data.itemsize
self.fp.write(b'0' * (var._vsize - count))
else: # record variable
# Handle rec vars with shape[0] < nrecs.
if self._recs > len(var.data):
shape = (self._recs,) + var.data.shape[1:]
# Resize in-place does not always work since
# the array might not be single-segment
try:
var.data.resize(shape)
except ValueError:
var.__dict__['data'] = np.resize(var.data, shape).astype(var.data.dtype)
pos0 = pos = self.fp.tell()
for rec in var.data:
# Apparently scalars cannot be converted to big endian. If we
# try to convert a ``=i4`` scalar to, say, '>i4' the dtype
# will remain as ``=i4``.
if not rec.shape and (rec.dtype.byteorder == '<' or
(rec.dtype.byteorder == '=' and LITTLE_ENDIAN)):
rec = rec.byteswap()
self.fp.write(rec.tostring())
# Padding
count = rec.size * rec.itemsize
self.fp.write(b'0' * (var._vsize - count))
pos += self._recsize
self.fp.seek(pos)
self.fp.seek(pos0 + var._vsize)
Example #8
| Source File: netcdf.py From lambda-packs with MIT License | 4 votes |
|
def _write_values(self, values):
if hasattr(values, 'dtype'):
nc_type = REVERSE[values.dtype.char, values.dtype.itemsize]
else:
types = [(t, NC_INT) for t in integer_types]
types += [
(float, NC_FLOAT),
(str, NC_CHAR)
]
# bytes index into scalars in py3k. Check for "string" types
if isinstance(values, text_type) or isinstance(values, binary_type):
sample = values
else:
try:
sample = values[0] # subscriptable?
except TypeError:
sample = values # scalar
for class_, nc_type in types:
if isinstance(sample, class_):
break
typecode, size = TYPEMAP[nc_type]
dtype_ = '>%s' % typecode
# asarray() dies with bytes and '>c' in py3k. Change to 'S'
dtype_ = 'S' if dtype_ == '>c' else dtype_
values = asarray(values, dtype=dtype_)
self.fp.write(asbytes(nc_type))
if values.dtype.char == 'S':
nelems = values.itemsize
else:
nelems = values.size
self._pack_int(nelems)
if not values.shape and (values.dtype.byteorder == '<' or
(values.dtype.byteorder == '=' and LITTLE_ENDIAN)):
values = values.byteswap()
self.fp.write(values.tostring())
count = values.size * values.itemsize
self.fp.write(b'0' * (-count % 4)) # pad
Example #9
| Source File: netcdf.py From GraphicDesignPatternByPython with MIT License | 4 votes |
|
def _write_att_values(self, values):
if hasattr(values, 'dtype'):
nc_type = REVERSE[values.dtype.char, values.dtype.itemsize]
else:
types = [(t, NC_INT) for t in integer_types]
types += [
(float, NC_FLOAT),
(str, NC_CHAR)
]
# bytes index into scalars in py3k. Check for "string" types
if isinstance(values, text_type) or isinstance(values, binary_type):
sample = values
else:
try:
sample = values[0] # subscriptable?
except TypeError:
sample = values # scalar
for class_, nc_type in types:
if isinstance(sample, class_):
break
typecode, size = TYPEMAP[nc_type]
dtype_ = '>%s' % typecode
# asarray() dies with bytes and '>c' in py3k. Change to 'S'
dtype_ = 'S' if dtype_ == '>c' else dtype_
values = asarray(values, dtype=dtype_)
self.fp.write(asbytes(nc_type))
if values.dtype.char == 'S':
nelems = values.itemsize
else:
nelems = values.size
self._pack_int(nelems)
if not values.shape and (values.dtype.byteorder == '<' or
(values.dtype.byteorder == '=' and LITTLE_ENDIAN)):
values = values.byteswap()
self.fp.write(values.tostring())
count = values.size * values.itemsize
self.fp.write(b'\x00' * (-count % 4)) # pad
Example #10
| Source File: netcdf.py From Splunking-Crime with GNU Affero General Public License v3.0 | 4 votes |
|
def _write_values(self, values):
if hasattr(values, 'dtype'):
nc_type = REVERSE[values.dtype.char, values.dtype.itemsize]
else:
types = [(t, NC_INT) for t in integer_types]
types += [
(float, NC_FLOAT),
(str, NC_CHAR)
]
# bytes index into scalars in py3k. Check for "string" types
if isinstance(values, text_type) or isinstance(values, binary_type):
sample = values
else:
try:
sample = values[0] # subscriptable?
except TypeError:
sample = values # scalar
for class_, nc_type in types:
if isinstance(sample, class_):
break
typecode, size = TYPEMAP[nc_type]
dtype_ = '>%s' % typecode
# asarray() dies with bytes and '>c' in py3k. Change to 'S'
dtype_ = 'S' if dtype_ == '>c' else dtype_
values = asarray(values, dtype=dtype_)
self.fp.write(asbytes(nc_type))
if values.dtype.char == 'S':
nelems = values.itemsize
else:
nelems = values.size
self._pack_int(nelems)
if not values.shape and (values.dtype.byteorder == '<' or
(values.dtype.byteorder == '=' and LITTLE_ENDIAN)):
values = values.byteswap()
self.fp.write(values.tostring())
count = values.size * values.itemsize
self.fp.write(b'0' * (-count % 4)) # pad
