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apply some codeql recommendations

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- remove unused imports
- avoid overlaps of variable names with keywords
- make some exception processing more explicit
This commit is contained in:
Axel Kohlmeyer
2021-05-09 19:52:31 -04:00
parent 6d9309b76d
commit 69a92a3e00
4 changed files with 94 additions and 97 deletions
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72
python/lammps/numpy_wrapper.py
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@ -142,7 +142,7 @@ class numpy_wrapper:
# -------------------------------------------------------------------------
def extract_compute(self, cid, style, type):
def extract_compute(self, cid, cstyle, ctype):
"""Retrieve data from a LAMMPS compute
This is a wrapper around the
@ -150,50 +150,50 @@ class numpy_wrapper:
It behaves the same as the original method, but returns NumPy arrays
instead of ``ctypes`` pointers.
:param id: compute ID
:type id: string
:param style: style of the data retrieve (global, atom, or local), see :ref:`py_style_constants`
:type style: int
:param type: type of the returned data (scalar, vector, or array), see :ref:`py_type_constants`
:type type: int
:param cid: compute ID
:type cid: string
:param cstyle: style of the data retrieve (global, atom, or local), see :ref:`py_style_constants`
:type cstyle: int
:param ctype: type of the returned data (scalar, vector, or array), see :ref:`py_type_constants`
:type ctype: int
:return: requested data either as float, as NumPy array with direct access to C data, or None
:rtype: float, numpy.array, or NoneType
"""
value = self.lmp.extract_compute(cid, style, type)
value = self.lmp.extract_compute(cid, cstyle, ctype)
if style in (LMP_STYLE_GLOBAL, LMP_STYLE_LOCAL):
if type == LMP_TYPE_VECTOR:
nrows = self.lmp.extract_compute(cid, style, LMP_SIZE_VECTOR)
if cstyle in (LMP_STYLE_GLOBAL, LMP_STYLE_LOCAL):
if ctype == LMP_TYPE_VECTOR:
nrows = self.lmp.extract_compute(cid, cstyle, LMP_SIZE_VECTOR)
return self.darray(value, nrows)
elif type == LMP_TYPE_ARRAY:
nrows = self.lmp.extract_compute(cid, style, LMP_SIZE_ROWS)
ncols = self.lmp.extract_compute(cid, style, LMP_SIZE_COLS)
elif ctype == LMP_TYPE_ARRAY:
nrows = self.lmp.extract_compute(cid, cstyle, LMP_SIZE_ROWS)
ncols = self.lmp.extract_compute(cid, cstyle, LMP_SIZE_COLS)
return self.darray(value, nrows, ncols)
elif style == LMP_STYLE_ATOM:
if type == LMP_TYPE_VECTOR:
elif cstyle == LMP_STYLE_ATOM:
if ctype == LMP_TYPE_VECTOR:
nlocal = self.lmp.extract_global("nlocal")
return self.darray(value, nlocal)
elif type == LMP_TYPE_ARRAY:
elif ctype == LMP_TYPE_ARRAY:
nlocal = self.lmp.extract_global("nlocal")
ncols = self.lmp.extract_compute(cid, style, LMP_SIZE_COLS)
ncols = self.lmp.extract_compute(cid, cstyle, LMP_SIZE_COLS)
return self.darray(value, nlocal, ncols)
return value
# -------------------------------------------------------------------------
def extract_fix(self, fid, style, type, nrow=0, ncol=0):
def extract_fix(self, fid, fstyle, ftype, nrow=0, ncol=0):
"""Retrieve data from a LAMMPS fix
This is a wrapper around the :py:meth:`lammps.extract_fix() <lammps.lammps.extract_fix()>` method.
It behaves the same as the original method, but returns NumPy arrays
instead of ``ctypes`` pointers.
:param id: fix ID
:type id: string
:param style: style of the data retrieve (global, atom, or local), see :ref:`py_style_constants`
:type style: int
:param type: type or size of the returned data (scalar, vector, or array), see :ref:`py_type_constants`
:type type: int
:param fid: fix ID
:type fid: string
:param fstyle: style of the data retrieve (global, atom, or local), see :ref:`py_style_constants`
:type fstyle: int
:param ftype: type or size of the returned data (scalar, vector, or array), see :ref:`py_type_constants`
:type ftype: int
:param nrow: index of global vector element or row index of global array element
:type nrow: int
:param ncol: column index of global array element
@ -202,22 +202,22 @@ class numpy_wrapper:
:rtype: integer or double value, pointer to 1d or 2d double array or None
"""
value = self.lmp.extract_fix(fid, style, type, nrow, ncol)
if style == LMP_STYLE_ATOM:
if type == LMP_TYPE_VECTOR:
value = self.lmp.extract_fix(fid, fstyle, ftype, nrow, ncol)
if fstyle == LMP_STYLE_ATOM:
if ftype == LMP_TYPE_VECTOR:
nlocal = self.lmp.extract_global("nlocal")
return self.darray(value, nlocal)
elif type == LMP_TYPE_ARRAY:
elif ftype == LMP_TYPE_ARRAY:
nlocal = self.lmp.extract_global("nlocal")
ncols = self.lmp.extract_fix(fid, style, LMP_SIZE_COLS, 0, 0)
ncols = self.lmp.extract_fix(fid, fstyle, LMP_SIZE_COLS, 0, 0)
return self.darray(value, nlocal, ncols)
elif style == LMP_STYLE_LOCAL:
if type == LMP_TYPE_VECTOR:
nrows = self.lmp.extract_fix(fid, style, LMP_SIZE_ROWS, 0, 0)
elif fstyle == LMP_STYLE_LOCAL:
if ftype == LMP_TYPE_VECTOR:
nrows = self.lmp.extract_fix(fid, fstyle, LMP_SIZE_ROWS, 0, 0)
return self.darray(value, nrows)
elif type == LMP_TYPE_ARRAY:
nrows = self.lmp.extract_fix(fid, style, LMP_SIZE_ROWS, 0, 0)
ncols = self.lmp.extract_fix(fid, style, LMP_SIZE_COLS, 0, 0)
elif ftype == LMP_TYPE_ARRAY:
nrows = self.lmp.extract_fix(fid, fstyle, LMP_SIZE_ROWS, 0, 0)
ncols = self.lmp.extract_fix(fid, fstyle, LMP_SIZE_COLS, 0, 0)
return self.darray(value, nrows, ncols)
return value