From e16ec19e3a445c1156c990ed71628fb183332be9 Mon Sep 17 00:00:00 2001 From: jaseg Date: Mon, 12 Oct 2020 20:15:41 +0200 Subject: Initial commit --- tools/dsss_demod_test_waveform_gen.py | 86 +++++++++++++++++++++++++++++++++++ 1 file changed, 86 insertions(+) create mode 100644 tools/dsss_demod_test_waveform_gen.py (limited to 'tools/dsss_demod_test_waveform_gen.py') diff --git a/tools/dsss_demod_test_waveform_gen.py b/tools/dsss_demod_test_waveform_gen.py new file mode 100644 index 0000000..414c553 --- /dev/null +++ b/tools/dsss_demod_test_waveform_gen.py @@ -0,0 +1,86 @@ + +from os import path +import json +import functools + +import numpy as np +import numbers +import math +from scipy import signal as sig +import scipy.fftpack + +sampling_rate = 10 # sp/s + +# From https://github.com/mubeta06/python/blob/master/signal_processing/sp/gold.py +preferred_pairs = {5:[[2],[1,2,3]], 6:[[5],[1,4,5]], 7:[[4],[4,5,6]], + 8:[[1,2,3,6,7],[1,2,7]], 9:[[5],[3,5,6]], + 10:[[2,5,9],[3,4,6,8,9]], 11:[[9],[3,6,9]]} + +def gen_gold(seq1, seq2): + gold = [seq1, seq2] + for shift in range(len(seq1)): + gold.append(seq1 ^ np.roll(seq2, -shift)) + return gold + +def gold(n): + n = int(n) + if not n in preferred_pairs: + raise KeyError('preferred pairs for %s bits unknown' % str(n)) + t0, t1 = preferred_pairs[n] + (seq0, _st0), (seq1, _st1) = sig.max_len_seq(n, taps=t0), sig.max_len_seq(n, taps=t1) + return gen_gold(seq0, seq1) + +def modulate(data, nbits=5): + # 0, 1 -> -1, 1 + mask = np.array(gold(nbits))*2 - 1 + + sel = mask[data>>1] + data_lsb_centered = ((data&1)*2 - 1) + + signal = (np.multiply(sel, np.tile(data_lsb_centered, (2**nbits-1, 1)).T).flatten() + 1) // 2 + return np.hstack([ np.zeros(len(mask)), signal, np.zeros(len(mask)) ]) + +def load_noise_meas_params(capture_file): + with open(capture_file, 'rb') as f: + meas_data = np.copy(np.frombuffer(f.read(), dtype='float32')) + meas_data -= np.mean(meas_data) + return (meas_data,) + +def mains_noise_measured(seed, n, meas_data): + last_valid = len(meas_data) - n + st = np.random.RandomState(seed) + start = st.randint(last_valid) + return meas_data[start:start+n] + 50.00 + +def load_noise_synth_params(specfile): + with open(specfile) as f: + d = json.load(f) + return {'spl_x': np.linspace(*d['x_spec']), + 'spl_N': d['x_spec'][2], + 'psd_spl': (d['t'], d['c'], d['k']) } + +def mains_noise_synthetic(seed, n, psd_spl, spl_N, spl_x): + st = np.random.RandomState(seed) + noise = st.normal(size=spl_N) * 2 + spec = scipy.fftpack.fft(noise) **2 + + spec *= np.exp(scipy.interpolate.splev(spl_x, psd_spl)) + + spec **= 1/2 + + renoise = scipy.fftpack.ifft(spec) + return renoise[10000:][:n] + 50.00 + +@functools.lru_cache() +def load_noise_gen(url): + schema, refpath = url.split('://') + if not path.isabs(refpath): + refpath = path.abspath(path.join(path.dirname(__file__), refpath)) + + if schema == 'meas': + return mains_noise_measured, load_noise_meas_params(refpath) + elif schema == 'synth': + return mains_noise_synthetic, load_noise_synth_params(refpath) + else: + raise ValueError('Invalid schema', schema) + -- cgit