fw simulator: WIP
This commit is contained in:
jaseg
parent
e505627ada
commit
87ae7dfcb3
24 changed files with 465 additions and 192 deletions
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@ -18,7 +18,7 @@ if __name__ == '__main__':
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print(f'const float {varname}[{args.n}] = {{')
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win = sig.ricker(args.n, args.w)
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par = ' '.join(f'{f:>015.8g}f,' for f in win)
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par = ' '.join(f'{f:>015.12e}f,' for f in win)
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print(textwrap.fill(par,
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initial_indent=' '*4, subsequent_indent=' '*4,
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width=120,
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@ -12,7 +12,7 @@
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#include "dsss_demod.h"
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void handle_dsss_received(uint8_t data[static TRANSMISSION_SYMBOLS]) {
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void handle_dsss_received(symbol_t data[static TRANSMISSION_SYMBOLS]) {
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printf("data sequence received: [ ");
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for (size_t i=0; i<TRANSMISSION_SYMBOLS; i++) {
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printf("%+3d", ((data[i]&1) ? 1 : -1) * (data[i]>>1));
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@ -4,36 +4,204 @@ import os
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from os import path
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import subprocess
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import json
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from collections import namedtuple, defaultdict
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from tqdm import tqdm
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import uuid
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import multiprocessing
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import sqlite3
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import time
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from urllib.parse import urlparse
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import functools
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import tempfile
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import itertools
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import numpy as np
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np.set_printoptions(linewidth=240)
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from dsss_demod_test_waveform_gen import load_noise_meas_params, load_noise_synth_params,\
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mains_noise_measured, mains_noise_synthetic, modulate as dsss_modulate
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def build_test_binary(nbits, thf, decimation, symbols, cachedir):
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build_id = str(uuid.uuid4())
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builddir = path.join(cachedir, build_id)
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os.mkdir(builddir)
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cwd = path.join(path.dirname(__file__), '..')
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env = os.environ.copy()
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env['BUILDDIR'] = path.abspath(builddir)
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env['DSSS_GOLD_CODE_NBITS'] = str(nbits)
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env['DSSS_DECIMATION'] = str(decimation)
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env['DSSS_THRESHOLD_FACTOR'] = str(thf)
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env['DSSS_WAVELET_WIDTH'] = str(0.73 * decimation)
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env['DSSS_WAVELET_LUT_SIZE'] = str(10 * decimation)
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env['TRANSMISSION_SYMBOLS'] = str(symbols)
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with open(path.join(builddir, 'make_stdout.txt'), 'w') as stdout,\
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open(path.join(builddir, 'make_stderr.txt'), 'w') as stderr:
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subprocess.run(['make', 'clean', os.path.abspath(path.join(builddir, 'tools/dsss_demod_test'))],
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env=env, cwd=cwd, check=True, stdout=stdout, stderr=stderr)
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return build_id
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@functools.lru_cache()
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def load_noise_gen(url):
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schema, refpath = url.split('://')
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if not path.isabs(refpath):
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refpath = path.abspath(path.join(path.dirname(__file__), refpath))
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if schema == 'meas':
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return mains_noise_measured, load_noise_meas_params(refpath)
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elif schema == 'synth':
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return mains_noise_synthetic, load_noise_synth_params(refpath)
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else:
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raise ValueError('Invalid schema', schema)
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def sequence_matcher(test_data, decoded, max_shift=3):
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match_result = []
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for shift in range(-max_shift, max_shift):
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failures = -shift if shift < 0 else 0 # we're skipping the first $shift symbols
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a = test_data if shift > 0 else test_data[-shift:]
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b = decoded if shift < 0 else decoded[shift:]
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for i, (ref, found) in enumerate(itertools.zip_longest(a, b)):
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if ref is None: # end of signal
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break
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if ref != found:
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failures += 1
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match_result.append(failures)
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failures = min(match_result)
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return failures/len(test_data)
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ResultParams = namedtuple('ResultParams', ['nbits', 'thf', 'decimation', 'symbols', 'seed', 'amplitude', 'background'])
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def run_test(seed, amplitude_spec, background, nbits, decimation, symbols, thfs, lookup_binary, cachedir):
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noise_gen, noise_params = load_noise_gen(background)
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test_data = np.random.RandomState(seed=seed).randint(0, 2 * (2**nbits), symbols)
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signal = np.repeat(dsss_modulate(test_data, nbits) * 2.0 - 1, decimation)
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# We're re-using the seed here. This is not a problem.
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noise = noise_gen(seed, len(signal), *noise_params)
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amplitudes = amplitude_spec[0] * 10 ** np.linspace(0, amplitude_spec[1], amplitude_spec[2])
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output = []
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for amp in amplitudes:
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with tempfile.NamedTemporaryFile(dir=cachedir) as f:
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waveform = signal*amp + noise
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f.write(waveform.astype('float').tobytes())
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f.flush()
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for thf in thfs:
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cmdline = [lookup_binary(nbits, thf, decimation, symbols), f.name]
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proc = subprocess.Popen(cmdline, stdout=subprocess.PIPE, text=True)
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stdout, _stderr = proc.communicate()
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if proc.returncode != 0:
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raise SystemError(f'Subprocess signalled error: {proc.returncode=}')
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lines = stdout.splitlines()
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matched = [ l.partition('[')[2].partition(']')[0]
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for l in lines if l.strip().startswith('data sequence received:') ]
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matched = [ [ int(elem) for elem in l.split(',') ] for l in matched ]
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ser = min(sequence_matcher(test_data, match) for match in matched) if matched else None
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rpars = ResultParams(nbits, thf, decimation, symbols, seed, amp, background)
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output.append((rpars, ser))
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print(f'ran {rpars} {ser=} {" ".join(cmdline)}')
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return output
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def parallel_generator(db, table, columns, builder, param_list, desc, context={}, params_mapper=lambda *args: args):
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with multiprocessing.Pool(multiprocessing.cpu_count()) as pool:
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with db as conn:
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jobs = []
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for params in param_list:
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found_res = conn.execute(
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f'SELECT result FROM {table} WHERE ({",".join(columns)}) = ({",".join("?"*len(columns))})',
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params_mapper(*params)).fetchone()
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if found_res:
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yield params, json.loads(*found_res)
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else:
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jobs.append((params, pool.apply_async(builder, params, context)))
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pool.close()
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print('Using', len(param_list) - len(jobs), 'cached jobs', flush=True)
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with tqdm(total=len(jobs), desc=desc) as tq:
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for params, res in jobs:
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tq.update(1)
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result = res.get()
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with db as conn:
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conn.execute(f'INSERT INTO {table} VALUES ({"?,"*len(params)}?,?)',
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(*params_mapper(*params), json.dumps(result), timestamp()))
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yield params, result
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pool.join()
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if __name__ == '__main__':
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import argparse
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parser = argparse.ArgumentParser()
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parser.add_argument(metavar='test_data_directory', dest='dir', help='Directory with test data .bin files')
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default_binary = path.abspath(path.join(path.dirname(__file__), '../build/tools/dsss_demod_test'))
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parser.add_argument(metavar='test_binary', dest='binary', nargs='?', default=default_binary)
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parser.add_argument('-d', '--dump', help='Write raw measurements to JSON file')
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parser.add_argument('-d', '--dump', help='Write results to JSON file')
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parser.add_argument('-c', '--cachedir', default='dsss_test_cache', help='Directory to store build output and data in')
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args = parser.parse_args()
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bin_files = [ path.join(args.dir, d) for d in os.listdir(args.dir) if d.lower().endswith('.bin') ]
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DecoderParams = namedtuple('DecoderParams', ['nbits', 'thf', 'decimation', 'symbols'])
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dec_paramses = [ DecoderParams(nbits=nbits, thf=thf, decimation=decimation, symbols=20)
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for nbits in [5, 6]
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for thf in [4.5, 4.0, 5.0]
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for decimation in [10, 5, 22] ]
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# dec_paramses = [ DecoderParams(nbits=nbits, thf=thf, decimation=decimation, symbols=100)
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# for nbits in [5, 6, 7, 8]
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# for thf in [1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 6.0, 6.5, 7.0, 7.5, 8.0, 8.5, 9.0, 9.5, 10.0]
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# for decimation in [1, 2, 3, 4, 5, 6, 9, 10, 11, 12, 16, 22, 30, 40, 50] ]
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savedata = {}
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for p in bin_files:
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output = subprocess.check_output([args.binary, p], stderr=subprocess.DEVNULL)
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measurements = np.array([ float(value) for _offset, value in [ line.split() for line in output.splitlines() ] ])
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savedata[p] = list(measurements)
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build_cache_dir = path.join(args.cachedir, 'builds')
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data_cache_dir = path.join(args.cachedir, 'data')
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os.makedirs(build_cache_dir, exist_ok=True)
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os.makedirs(data_cache_dir, exist_ok=True)
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# Cut off first and last sample for mean and RMS calculations as these show boundary effects.
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measurements = measurements[1:-1]
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mean = np.mean(measurements)
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rms = np.sqrt(np.mean(np.square(measurements - mean)))
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build_db = sqlite3.connect(path.join(args.cachedir, 'build_db.sqlite3'))
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build_db.execute('CREATE TABLE IF NOT EXISTS builds (nbits, thf, decimation, symbols, result, timestamp)')
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timestamp = lambda: int(time.time()*1000)
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print(f'{path.basename(p):<60}: mean={mean:<8.4f}Hz rms={rms*1000:.3f}mHz')
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builds = dict(parallel_generator(build_db, table='builds', columns=['nbits', 'thf', 'decimation', 'symbols'],
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builder=build_test_binary, param_list=dec_paramses, desc='Building decoders',
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context=dict(cachedir=build_cache_dir)))
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print('Done building decoders.')
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GeneratorParams = namedtuple('GeneratorParams', ['seed', 'amplitude_spec', 'background'])
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gen_params = [ GeneratorParams(rep, (5e-3, 1, 5), background)
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#GeneratorParams(rep, (0.05e-3, 3.5, 50), background)
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for rep in range(30)
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for background in ['meas://fmeas_export_ocxo_2day.bin', 'synth://grid_freq_psd_spl_108pt.json'] ]
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data_db = sqlite3.connect(path.join(args.cachedir, 'data_db.sqlite3'))
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data_db.execute('CREATE TABLE IF NOT EXISTS waveforms'
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'(seed, amplitude_spec, background, nbits, decimation, symbols, thresholds, result, timestamp)')
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dec_param_groups = defaultdict(lambda: [])
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for nbits, thf, decimation, symbols in dec_paramses:
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dec_param_groups[(nbits, decimation, symbols)].append(thf)
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waveform_params = [ (*gp, *dp, thfs) for gp in gen_params for dp, thfs in dec_param_groups.items() ]
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print(f'Generated {len(waveform_params)} parameter sets')
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def lookup_binary(*params):
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return path.join(build_cache_dir, builds[tuple(params)], 'tools/dsss_demod_test')
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def params_mapper(seed, amplitude_spec, background, nbits, decimation, symbols, thresholds):
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amplitude_spec = ','.join(str(x) for x in amplitude_spec)
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thresholds = ','.join(str(x) for x in thresholds)
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return seed, amplitude_spec, background, nbits, decimation, symbols, thresholds
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results = []
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for _params, chunk in parallel_generator(data_db, 'waveforms',
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['seed', 'amplitude_spec', 'background', 'nbits', 'decimation', 'symbols', 'thresholds'],
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params_mapper=params_mapper,
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builder=run_test,
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param_list=waveform_params, desc='Generating waveforms',
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context=dict(cachedir=data_cache_dir, lookup_binary=lookup_binary)):
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results += chunk
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if args.dump:
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with open(args.dump, 'w') as f:
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json.dump(savedata, f)
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json.dump(results, f)
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71
controller/fw/tools/dsss_demod_test_waveform_gen.py
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71
controller/fw/tools/dsss_demod_test_waveform_gen.py
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@ -0,0 +1,71 @@
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import functools
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import numpy as np
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import numbers
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import math
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from scipy import signal as sig
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import scipy.fftpack
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sampling_rate = 10 # sp/s
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# From https://github.com/mubeta06/python/blob/master/signal_processing/sp/gold.py
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preferred_pairs = {5:[[2],[1,2,3]], 6:[[5],[1,4,5]], 7:[[4],[4,5,6]],
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8:[[1,2,3,6,7],[1,2,7]], 9:[[5],[3,5,6]],
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10:[[2,5,9],[3,4,6,8,9]], 11:[[9],[3,6,9]]}
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def gen_gold(seq1, seq2):
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gold = [seq1, seq2]
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for shift in range(len(seq1)):
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gold.append(seq1 ^ np.roll(seq2, -shift))
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return gold
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def gold(n):
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n = int(n)
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if not n in preferred_pairs:
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raise KeyError('preferred pairs for %s bits unknown' % str(n))
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t0, t1 = preferred_pairs[n]
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(seq0, _st0), (seq1, _st1) = sig.max_len_seq(n, taps=t0), sig.max_len_seq(n, taps=t1)
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return gen_gold(seq0, seq1)
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def modulate(data, nbits=5):
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# 0, 1 -> -1, 1
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mask = np.array(gold(nbits))*2 - 1
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sel = mask[data>>1]
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data_lsb_centered = ((data&1)*2 - 1)
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signal = (np.multiply(sel, np.tile(data_lsb_centered, (2**nbits-1, 1)).T).flatten() + 1) // 2
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return np.hstack([ np.zeros(len(mask)), signal, np.zeros(len(mask)) ])
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def load_noise_meas_params(capture_file):
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with open(capture_file, 'rb') as f:
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meas_data = np.copy(np.frombuffer(f.read(), dtype='float32'))
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meas_data -= np.mean(meas_data)
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return (meas_data,)
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def mains_noise_measured(seed, n, meas_data):
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last_valid = len(meas_data) - n
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st = np.random.RandomState(seed)
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start = st.randint(last_valid)
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return meas_data[start:start+n]
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def load_noise_synth_params(specfile):
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with open(specfile) as f:
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d = json.load(f)
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return (np.linspace(*d['x_spec']), # spl_x
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d['x_spec'][2], # spl_N
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(d['t'], d['c'], d['k'])) # psd_spl
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def mains_noise_synthetic(seed, n, psd_spl, spl_N, spl_x):
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st = np.random.RandomState(seed)
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noise = st.normal(size=spl_N) * 2
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spec = scipy.fftpack.fft(noise) **2
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spec *= np.exp(scipy.interpolate.splev(spl_x, psd_spl))
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spec **= 1/2
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renoise = scipy.fftpack.ifft(spec)
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return renoise[10000:][:n]
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BIN
controller/fw/tools/fmeas_export_ocxo_2day.bin
Normal file
BIN
controller/fw/tools/fmeas_export_ocxo_2day.bin
Normal file
Binary file not shown.
1
controller/fw/tools/grid_freq_psd_spl_108pt.json
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1
controller/fw/tools/grid_freq_psd_spl_108pt.json
Normal file
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@ -0,0 +1 @@
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