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Copy pathm2cpp.py
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executable file
·104 lines (79 loc) · 4.12 KB
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#!/usr/bin/env python
# PYTHON_ARGCOMPLETE_OK
import argparse
from textwrap import dedent
from glob import glob
import matlab2cpp
hstring = "*** Matlab2cpp version " + str(matlab2cpp.__version__) + " ***\n\n" + """\
The toolbox frontend of the Matlab2cpp library. Use this to try to do automatic
and semi-automatic translation. The program will create files with the same
name as the input, but with various extra extensions. Scripts will receive the
extension `.cpp`, headers and modules `.hpp`. A file containing data type and
header information will be stored in a `.py` file. Any errors will be stored in
`.log`.
"""
parser = argparse.ArgumentParser(
formatter_class=argparse.RawDescriptionHelpFormatter,
description=dedent(hstring))
parser.add_argument("filename",
help="File containing valid Matlab code.").completer=\
lambda prefix, **kws: glob("*.m")
parser.add_argument("-o", '--original', action="store_true",
help="Include original Matlab code line as comment before the C++ translation of the code line")
parser.add_argument("-c", '--comments', action="store_true",
help="""\
Include Matlab comments in the generated C++ files.""")
parser.add_argument("-s", '--suggest', action="store_true",
help="""\
Automatically populate the `<filename>.py` file with datatype with suggestions
if possible.""")
parser.add_argument("-S", '--matlab-suggest', action="store_true",
help="""Creates a folder m2cpp_temp. In the folder the matlab file(s) to be translated are also put. \
These matlab file(s) are slightly modified so that they output data-type information of the variables \
to file(s). This output can then be used to set the datatypes for the translation.""")
parser.add_argument("-r", '--reset', action="store_true",
help="""\
Ignore the content of `<filename>.py` and make a fresh translation.""")
parser.add_argument("-t", '--tree', action="store_true",
help="""\
Print the underlying node tree. Each line in the output represents a node and
is formated as follows:
`<codeline> <position> <class> <backend> <datatype> <name> <translation>`
The indentation represents the tree structure.
""")
parser.add_argument("-T", "--tree-full", action="store_true",
help="""\
Same as -t, but the full node tree, but include meta-nodes.""")
parser.add_argument("-d", '--disp', action="store_true",
help="""\
Print out the progress of the translation process.""")
parser.add_argument("-p", "--paths_file", type=str, dest="paths_file",
help="""\
Flag and paths_file (-p path_to_pathsfile). m2cpp will look for matlab files in the location specified \
in the paths_file""")
parser.add_argument("-omp", '--enable-omp', action="store_true",
help="""\
OpenMP code is inserted for Parfor and loops marked with the pragma %%#PARFOR (in Matlab code) when this \
flag is set.""")
parser.add_argument("-tbb", '--enable-tbb', action="store_true",
help="""\
TBB code is inserted for Parfor and loops marked with the pragma %%#PARFOR (in Matlab code) when this flag is set.""")
parser.add_argument("-ref", '--reference', action="store_true",
help="""\
For the generated C++ code, function input parameters are "copied by value" as default. With this flag some \
input parameters in the generated code can be const references. There can be some performance advantage of using
const references instead of "copied by value". Note that Matlab "copies by value". \
The Matlab code you try to translate to C++ code could try read as well as write to this input variable. \
The code generator doesn't perform an analysis to detect this and then "copy by value" for this variable.""")
parser.add_argument("-l", '--line', type=int, dest="line",
help="Only display code related to code line number `<line>`.")
parser.add_argument("-n", '--nargin', action="store_true",
help="Don't remove if and switch branches which use nargin variable.")
try:
import argcomplete
argcomplete.autocomplete(parser)
except:
pass
if __name__ == "__main__":
args = parser.parse_args()
matlab2cpp.main(args)