fw simulator: WIP

1 files changed, 184 insertions, 16 deletions

diff --git a/controller/fw/tools/dsss_demod_test_runner.py b/controller/fw/tools/dsss_demod_test_runner.py
index 4e93d7b..e31a686 100644
--- a/controller/fw/tools/dsss_demod_test_runner.py
+++ b/controller/fw/tools/dsss_demod_test_runner.py
@@ -4,36 +4,204 @@ import os
 from os import path
 import subprocess
 import json
+from collections import namedtuple, defaultdict
+from tqdm import tqdm
+import uuid
+import multiprocessing
+import sqlite3 
+import time
+from urllib.parse import urlparse
+import functools
+import tempfile
+import itertools
 
 import numpy as np
 np.set_printoptions(linewidth=240)
 
+from dsss_demod_test_waveform_gen import load_noise_meas_params, load_noise_synth_params,\
+        mains_noise_measured, mains_noise_synthetic, modulate as dsss_modulate
+
+
+def build_test_binary(nbits, thf, decimation, symbols, cachedir):
+    build_id = str(uuid.uuid4())
+    builddir = path.join(cachedir, build_id)
+    os.mkdir(builddir)
+
+    cwd = path.join(path.dirname(__file__), '..')
+
+    env = os.environ.copy()
+    env['BUILDDIR'] = path.abspath(builddir)
+    env['DSSS_GOLD_CODE_NBITS'] = str(nbits)
+    env['DSSS_DECIMATION'] = str(decimation)
+    env['DSSS_THRESHOLD_FACTOR'] = str(thf)
+    env['DSSS_WAVELET_WIDTH'] = str(0.73 * decimation)
+    env['DSSS_WAVELET_LUT_SIZE'] = str(10 * decimation)
+    env['TRANSMISSION_SYMBOLS'] = str(symbols)
+
+    with open(path.join(builddir, 'make_stdout.txt'), 'w') as stdout,\
+         open(path.join(builddir, 'make_stderr.txt'), 'w') as stderr:
+        subprocess.run(['make', 'clean', os.path.abspath(path.join(builddir, 'tools/dsss_demod_test'))],
+                env=env, cwd=cwd, check=True, stdout=stdout, stderr=stderr)
+
+    return build_id
+
+@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)
+
+def sequence_matcher(test_data, decoded, max_shift=3):
+    match_result = []
+    for shift in range(-max_shift, max_shift):
+        failures = -shift if shift < 0 else 0 # we're skipping the first $shift symbols
+        a = test_data if shift > 0 else test_data[-shift:]
+        b = decoded if shift < 0 else decoded[shift:]
+        for i, (ref, found) in enumerate(itertools.zip_longest(a, b)):
+            if ref is None: # end of signal
+                break
+            if ref != found:
+                failures += 1
+        match_result.append(failures)
+    failures = min(match_result)
+    return failures/len(test_data)
+
+ResultParams = namedtuple('ResultParams', ['nbits', 'thf', 'decimation', 'symbols', 'seed', 'amplitude', 'background'])
+
+def run_test(seed, amplitude_spec, background, nbits, decimation, symbols, thfs, lookup_binary, cachedir):
+    noise_gen, noise_params = load_noise_gen(background)
+
+    test_data = np.random.RandomState(seed=seed).randint(0, 2 * (2**nbits), symbols)
+    
+    signal = np.repeat(dsss_modulate(test_data, nbits) * 2.0 - 1, decimation)
+    # We're re-using the seed here. This is not a problem.
+    noise = noise_gen(seed, len(signal), *noise_params)
+
+    amplitudes = amplitude_spec[0] * 10 ** np.linspace(0, amplitude_spec[1], amplitude_spec[2])
+    output = []
+    for amp in amplitudes:
+        with tempfile.NamedTemporaryFile(dir=cachedir) as f:
+            waveform = signal*amp + noise
+            f.write(waveform.astype('float').tobytes())
+            f.flush()
+        
+            for thf in thfs:
+                cmdline = [lookup_binary(nbits, thf, decimation, symbols), f.name]
+                proc = subprocess.Popen(cmdline, stdout=subprocess.PIPE, text=True)
+                stdout, _stderr = proc.communicate()
+                if proc.returncode != 0:
+                    raise SystemError(f'Subprocess signalled error: {proc.returncode=}')
+
+                lines = stdout.splitlines()
+                matched = [ l.partition('[')[2].partition(']')[0]
+                        for l in lines if l.strip().startswith('data sequence received:') ]
+                matched = [ [ int(elem) for elem in l.split(',') ] for l in matched ]
+
+                ser = min(sequence_matcher(test_data, match) for match in matched) if matched else None
+                rpars = ResultParams(nbits, thf, decimation, symbols, seed, amp, background)
+                output.append((rpars, ser))
+                print(f'ran {rpars} {ser=} {" ".join(cmdline)}')
+    return output
+
+def parallel_generator(db, table, columns, builder, param_list, desc, context={}, params_mapper=lambda *args: args):
+    with multiprocessing.Pool(multiprocessing.cpu_count()) as pool:
+        with db as conn:
+            jobs = []
+            for params in param_list:
+                found_res = conn.execute(
+                            f'SELECT result FROM {table} WHERE ({",".join(columns)}) = ({",".join("?"*len(columns))})',
+                        params_mapper(*params)).fetchone()
+
+                if found_res:
+                    yield params, json.loads(*found_res)
+
+                else:
+                    jobs.append((params, pool.apply_async(builder, params, context)))
+
+        pool.close()
+        print('Using', len(param_list) - len(jobs), 'cached jobs', flush=True)
+        with tqdm(total=len(jobs), desc=desc) as tq:
+            for params, res in jobs:
+                tq.update(1)
+                result = res.get()
+                with db as conn:
+                    conn.execute(f'INSERT INTO {table} VALUES ({"?,"*len(params)}?,?)',
+                            (*params_mapper(*params), json.dumps(result), timestamp()))
+                yield params, result
+        pool.join()
 
 if __name__ == '__main__':
     import argparse
     parser = argparse.ArgumentParser()
-    parser.add_argument(metavar='test_data_directory', dest='dir', help='Directory with test data .bin files')
-    default_binary = path.abspath(path.join(path.dirname(__file__), '../build/tools/dsss_demod_test'))
-    parser.add_argument(metavar='test_binary', dest='binary', nargs='?', default=default_binary)
-    parser.add_argument('-d', '--dump', help='Write raw measurements to JSON file')
+    parser.add_argument('-d', '--dump', help='Write results to JSON file')
+    parser.add_argument('-c', '--cachedir', default='dsss_test_cache', help='Directory to store build output and data in')
     args = parser.parse_args()
 
-    bin_files = [ path.join(args.dir, d) for d in os.listdir(args.dir) if d.lower().endswith('.bin') ]
+    DecoderParams = namedtuple('DecoderParams', ['nbits', 'thf', 'decimation', 'symbols'])
+    dec_paramses = [ DecoderParams(nbits=nbits, thf=thf, decimation=decimation, symbols=20)
+            for nbits in [5, 6]
+            for thf in [4.5, 4.0, 5.0]
+            for decimation in [10, 5, 22] ]
+#    dec_paramses = [ DecoderParams(nbits=nbits, thf=thf, decimation=decimation, symbols=100)
+#            for nbits in [5, 6, 7, 8]
+#            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]
+#            for decimation in [1, 2, 3, 4, 5, 6, 9, 10, 11, 12, 16, 22, 30, 40, 50] ]
+
+    build_cache_dir = path.join(args.cachedir, 'builds')
+    data_cache_dir = path.join(args.cachedir, 'data')
+    os.makedirs(build_cache_dir, exist_ok=True)
+    os.makedirs(data_cache_dir, exist_ok=True)
+
+    build_db = sqlite3.connect(path.join(args.cachedir, 'build_db.sqlite3'))
+    build_db.execute('CREATE TABLE IF NOT EXISTS builds (nbits, thf, decimation, symbols, result, timestamp)')
+    timestamp = lambda: int(time.time()*1000)
+
+    builds = dict(parallel_generator(build_db, table='builds', columns=['nbits', 'thf', 'decimation', 'symbols'],
+            builder=build_test_binary, param_list=dec_paramses, desc='Building decoders',
+            context=dict(cachedir=build_cache_dir)))
+    print('Done building decoders.')
+
+    GeneratorParams = namedtuple('GeneratorParams', ['seed', 'amplitude_spec', 'background'])
+    gen_params = [ GeneratorParams(rep, (5e-3, 1, 5), background)
+            #GeneratorParams(rep, (0.05e-3, 3.5, 50), background)
+            for rep in range(30)
+            for background in ['meas://fmeas_export_ocxo_2day.bin', 'synth://grid_freq_psd_spl_108pt.json'] ]
+
+    data_db = sqlite3.connect(path.join(args.cachedir, 'data_db.sqlite3'))
+    data_db.execute('CREATE TABLE IF NOT EXISTS waveforms'
+                    '(seed, amplitude_spec, background, nbits, decimation, symbols, thresholds, result, timestamp)')
+
+    dec_param_groups = defaultdict(lambda: [])
+    for nbits, thf, decimation, symbols in dec_paramses:
+        dec_param_groups[(nbits, decimation, symbols)].append(thf)
+    waveform_params = [ (*gp, *dp, thfs) for gp in gen_params for dp, thfs in dec_param_groups.items() ]
+    print(f'Generated {len(waveform_params)} parameter sets')
 
-    savedata = {}
-    for p in bin_files:
-        output = subprocess.check_output([args.binary, p], stderr=subprocess.DEVNULL)
-        measurements = np.array([ float(value) for _offset, value in [ line.split() for line in output.splitlines() ] ])
-        savedata[p] = list(measurements)
+    def lookup_binary(*params):
+        return path.join(build_cache_dir, builds[tuple(params)], 'tools/dsss_demod_test')
 
-        # Cut off first and last sample for mean and RMS calculations as these show boundary effects.
-        measurements = measurements[1:-1]
-        mean = np.mean(measurements)
-        rms = np.sqrt(np.mean(np.square(measurements - mean)))
+    def params_mapper(seed, amplitude_spec, background, nbits, decimation, symbols, thresholds):
+        amplitude_spec = ','.join(str(x) for x in amplitude_spec)
+        thresholds = ','.join(str(x) for x in thresholds)
+        return seed, amplitude_spec, background, nbits, decimation, symbols, thresholds
 
-        print(f'{path.basename(p):<60}:    mean={mean:<8.4f}Hz rms={rms*1000:.3f}mHz')
+    results = []
+    for _params, chunk in parallel_generator(data_db, 'waveforms',
+            ['seed', 'amplitude_spec', 'background', 'nbits', 'decimation', 'symbols', 'thresholds'],
+            params_mapper=params_mapper,
+            builder=run_test,
+            param_list=waveform_params, desc='Generating waveforms',
+            context=dict(cachedir=data_cache_dir, lookup_binary=lookup_binary)):
+        results += chunk
 
     if args.dump:
         with open(args.dump, 'w') as f:
-            json.dump(savedata, f)
+            json.dump(results, f)