nbecker

#!/usr/bin/env python
# coding: utf-8

import os
os.environ["PATH"] += os.pathsep + '/usr/local/cuda-12.2/bin'
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' #supposed to suppress messages, but doesn't work
#import os
# use xla-lite (doesn't work for centroid for now)
#os.environ['TF_XLA_FLAGS']='--tf_xla_auto_jit=fusible'

nbecker

alias width = 960
alias height = 960
alias MAX_ITERS = 200

alias min_x = -2.0
alias max_x = 0.6
alias min_y = -1.5
alias max_y = 1.5

# Compute the number of steps to escape.

nbecker

#ifndef Complex_H
#define Complex_H

#include <complex>
typedef std::complex<double> Complex;
typedef std::complex<double> complex_t;
typedef std::complex<float> complex64_t;
typedef std::complex<long double> complex256_t;

// decomplexify ---------------------------------------------------------------

nbecker

import numpy as np

#pythran export getArrayFactor (complex[:], float[:], float[:], float[:,:], float[:,:], float)
#pythran export getArrayFactor (complex[:], float[:], float[:], float, float, float)
def getArrayFactor(W, px, py, theta, phi, L):
    theta = np.array (theta)
    phi = np.array (phi)
    N = px.shape[0]
    AF = np.zeros(theta.shape, dtype=complex)
    kx = np.sin(theta) * np.cos(phi) * 2.0 * np.pi / L

nbecker

import numpy as np

#pythran export getArrayFactor (complex[:], float[:], float[:], float[:,:], float[:,:], float)
def getArrayFactor(W, px, py, theta, phi, L):
    N = px.shape[0]
    AF = np.zeros(theta.shape, dtype=complex)
    kx = np.sin(theta) * np.cos(phi) * 2.0 * np.pi / L
    ky = np.sin(theta) * np.sin(phi) * 2.0 * np.pi / L
    for n in range(N):
        AF += W[n] * np.exp(-1j * (kx * px[n] + ky * py[n]))

nbecker

#!/usr/bin/env python
# coding: utf-8
import numpy as np
from sionna.utils import QAMSource
from sionna.signal import Upsampling, Downsampling, RootRaisedCosineFilter, empirical_psd, empirical_aclr
beta = 0.1
span_in_symbols = 32
samples_per_symbol = 2
rrcf = RootRaisedCosineFilter(span_in_symbols, samples_per_symbol, beta, normalize=False)
mf = RootRaisedCosineFilter(span_in_symbols, samples_per_symbol, beta, normalize=False)

nbecker

from transonic import boost
import numpy as np

@boost
class crl:
    k: float
    aT: float
    sum1: float
    sum2: float
    

nbecker

import numpy as np
from transonic import boost

A = "complex[:]"
S = "int[:]"

@boost(boundscheck=True)
def call1 (map: A, s: int):
    return map[s]

nbecker

import numpy as np

#pythran export orthogonal_mod (int[:], int)
#pythran export orthogonal_mod (int32[:], int)
def orthogonal_mod (x, nbits):
    out = np.zeros ((len(x), 1<<nbits), dtype=complex)
    for e in range (len (x)):
        out[e,x[e]] = 1
    return out

nbecker

                 from histogram2d_c.cc:6:
/home/nbecker/.local/include/xtensor/xtensor_config.hpp:87:43: error: 'XSIMD_DEFAULT_ALIGNMENT' was not declared in this scope; did you mean 'XTENSOR_DEFAULT_ALIGNMENT'?
   87 |         #define XTENSOR_DEFAULT_ALIGNMENT XSIMD_DEFAULT_ALIGNMENT
      |                                           ^~~~~~~~~~~~~~~~~~~~~~~
/home/nbecker/.local/include/xtensor/xtensor_config.hpp:87:43: note: in definition of macro 'XTENSOR_DEFAULT_ALIGNMENT'
   87 |         #define XTENSOR_DEFAULT_ALIGNMENT XSIMD_DEFAULT_ALIGNMENT
      |                                           ^~~~~~~~~~~~~~~~~~~~~~~
/home/nbecker/.local/include/xtensor/xstorage.hpp:1389:59: note: in expansion of macro 'XTENSOR_SELECT_ALIGN'
 1389 |     template <class T, std::size_t N, std::size_t Align = XTENSOR_SELECT_ALIGN(T)>
      |                                                           ^~~~~~~~~~~~~~~~~~~~