Loading python/lammps.py +48 −0 Original line number Diff line number Diff line Loading @@ -435,6 +435,54 @@ class lammps(object): return self.darray(raw_ptr, nelem, dim) def extract_compute(self, cid, style, datatype): value = self.lmp.extract_compute(cid, style, datatype) if style in (LMP_STYLE_GLOBAL, LMP_STYLE_LOCAL): if datatype == LMP_TYPE_VECTOR: nrows = self.lmp.extract_compute(cid, style, LMP_SIZE_VECTOR) print("NROWS", nrows) return self.darray(value, nrows) elif datatype == LMP_TYPE_ARRAY: nrows = self.lmp.extract_compute(cid, style, LMP_SIZE_ROWS) ncols = self.lmp.extract_compute(cid, style, LMP_SIZE_COLS) return self.darray(value, nrows, ncols) elif style == LMP_STYLE_ATOM: if datatype == LMP_TYPE_VECTOR: nlocal = self.lmp.extract_global("nlocal", LAMMPS_INT) return self.darray(value, nlocal) elif datatype == LMP_TYPE_ARRAY: nlocal = self.lmp.extract_global("nlocal", LAMMPS_INT) ncols = self.lmp.extract_compute(cid, style, LMP_SIZE_COLS) return self.darray(value, nlocal, ncols) return value def extract_fix(self, fid, style, datatype, nrow=0, ncol=0): value = self.lmp.extract_fix(fid, style, datatype, nrow, ncol) if style == LMP_STYLE_ATOM: if datatype == LMP_TYPE_VECTOR: nlocal = self.lmp.extract_global("nlocal", LAMMPS_INT) return self.darray(value, nlocal) elif datatype == LMP_TYPE_ARRAY: nlocal = self.lmp.extract_global("nlocal", LAMMPS_INT) ncols = self.lmp.extract_fix(fid, style, LMP_SIZE_COLS, 0, 0) return self.darray(value, nlocal, ncols) elif style == LMP_STYLE_LOCAL: if datatype == LMP_TYPE_VECTOR: nrows = self.lmp.extract_fix(fid, style, LMP_SIZE_ROWS, 0, 0) return self.darray(value, nrows) elif datatype == 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) return self.darray(value, nrows, ncols) return value def extract_variable(self, name, group=None, datatype=LMP_VAR_EQUAL): value = self.lmp.extract_variable(name, group, datatype) if datatype == LMP_VAR_ATOM: return np.ctypeslib.as_array(value) return value def iarray(self, c_int_type, raw_ptr, nelem, dim=1): np_int_type = self._ctype_to_numpy_int(c_int_type) Loading Loading
python/lammps.py +48 −0 Original line number Diff line number Diff line Loading @@ -435,6 +435,54 @@ class lammps(object): return self.darray(raw_ptr, nelem, dim) def extract_compute(self, cid, style, datatype): value = self.lmp.extract_compute(cid, style, datatype) if style in (LMP_STYLE_GLOBAL, LMP_STYLE_LOCAL): if datatype == LMP_TYPE_VECTOR: nrows = self.lmp.extract_compute(cid, style, LMP_SIZE_VECTOR) print("NROWS", nrows) return self.darray(value, nrows) elif datatype == LMP_TYPE_ARRAY: nrows = self.lmp.extract_compute(cid, style, LMP_SIZE_ROWS) ncols = self.lmp.extract_compute(cid, style, LMP_SIZE_COLS) return self.darray(value, nrows, ncols) elif style == LMP_STYLE_ATOM: if datatype == LMP_TYPE_VECTOR: nlocal = self.lmp.extract_global("nlocal", LAMMPS_INT) return self.darray(value, nlocal) elif datatype == LMP_TYPE_ARRAY: nlocal = self.lmp.extract_global("nlocal", LAMMPS_INT) ncols = self.lmp.extract_compute(cid, style, LMP_SIZE_COLS) return self.darray(value, nlocal, ncols) return value def extract_fix(self, fid, style, datatype, nrow=0, ncol=0): value = self.lmp.extract_fix(fid, style, datatype, nrow, ncol) if style == LMP_STYLE_ATOM: if datatype == LMP_TYPE_VECTOR: nlocal = self.lmp.extract_global("nlocal", LAMMPS_INT) return self.darray(value, nlocal) elif datatype == LMP_TYPE_ARRAY: nlocal = self.lmp.extract_global("nlocal", LAMMPS_INT) ncols = self.lmp.extract_fix(fid, style, LMP_SIZE_COLS, 0, 0) return self.darray(value, nlocal, ncols) elif style == LMP_STYLE_LOCAL: if datatype == LMP_TYPE_VECTOR: nrows = self.lmp.extract_fix(fid, style, LMP_SIZE_ROWS, 0, 0) return self.darray(value, nrows) elif datatype == 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) return self.darray(value, nrows, ncols) return value def extract_variable(self, name, group=None, datatype=LMP_VAR_EQUAL): value = self.lmp.extract_variable(name, group, datatype) if datatype == LMP_VAR_ATOM: return np.ctypeslib.as_array(value) return value def iarray(self, c_int_type, raw_ptr, nelem, dim=1): np_int_type = self._ctype_to_numpy_int(c_int_type) Loading
