python to c++ transpiler
# Note: The last time I tested something was missing so I couldn't work
import pathlib
import transpyle
path = pathlib.Path('my_script.py')
code_reader = transpyle.CodeReader()
code = code_reader.read_file(path)
from_language = transpyle.Language.find('Python 3.6')
to_language = transpyle.Language.find('Fortran 95')
translator = transpyle.AutoTranslator(from_language, to_language)
fortran_code = translator.translate(code, path)
print(fortran_code)Python to C++ converter
import multiprocessing as mp
import multiprocessing.sharedctypes
import numpy as np
import scipy as sp
# Try to use the FFT implementation in PyFFTW if available, or fall back on
# numpy's.
try:
import pyfftw.interfaces.numpy_fft as npf
except ImportError:
from BoltzTraP2.misc import warning
warning("you can install pyfftw to get better FFT performance")
import numpy.fft as npf
from BoltzTraP2.units import * # import all functions from units
def fitde3D(data, equivalences):
"""Obtain the interpolation coefficients from DFT data.
Args:
data: DFTdata object containing all relevant input
equivalences: list of k-point equivalence classes in direct coordinates
Returns:
A set of interpolation coefficients as an array whose first dimension
runs over bands.
"""
kp = data.kpoints
ene = data.ebands
mommat = data.mommat
lattvec = data.get_lattvec()
tpii = 2j * np.pi
C1 = .75
C2 = .75
Rvec = np.array([equiv[0] for equiv in equivalences]) #assigning first element of equiv to the Rvec
Rvec = np.array([equiv[0] for equiv in equivalences])
nstar = np.array([len(equiv) for equiv in equivalences])
R = np.linalg.norm(Rvec @ lattvec.T, axis=1) #used to calculate vector norm
De = ene.T[:-1] - ene.T[-1]
if mommat is not None:
for i in range(3):
De = np.vstack((De, mommat[:, :, i])) #vstack
X2 = (R / R[1])**2
rhoi = 1. / ((1. - C1 * X2)**2 + C2 * X2**3)
rhoi[0] = 0.Copyright © 2021 Codeinu
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