diff options
| -rw-r--r-- | controller/fw/Makefile | 2 | ||||
| -rw-r--r-- | controller/fw/src/dsss_demod.c | 49 | ||||
| -rw-r--r-- | controller/fw/src/main.c | 17 | ||||
| -rw-r--r-- | controller/fw/src/sr_global.h | 5 | ||||
| -rw-r--r-- | lab-windows/scratch.ipynb | 348 |
5 files changed, 351 insertions, 70 deletions
diff --git a/controller/fw/Makefile b/controller/fw/Makefile index 50d162d..0faea30 100644 --- a/controller/fw/Makefile +++ b/controller/fw/Makefile @@ -25,7 +25,7 @@ FMEAS_SAMPLING_RATE ?= $(shell echo $(FMEAS_ADC_SAMPLING_RATE) / \($(FMEAS_FFT_ DSSS_GOLD_CODE_NBITS ?= 5 DSSS_DECIMATION ?= 10 # TODO maybe auto adjust this based on detection rate? -DSSS_THESHOLD_FACTOR ?= 6.0f +DSSS_THESHOLD_FACTOR ?= 5.0f DSSS_WAVELET_WIDTH ?= 7.3 DSSS_WAVELET_LUT_SIZE ?= 69 DSSS_FILTER_FC ?= 3e-3 diff --git a/controller/fw/src/dsss_demod.c b/controller/fw/src/dsss_demod.c index 0758525..f9efda6 100644 --- a/controller/fw/src/dsss_demod.c +++ b/controller/fw/src/dsss_demod.c @@ -23,10 +23,8 @@ struct iir_biquad cwt_filter_bq[DSSS_FILTER_CLEN] = {DSSS_FILTER_COEFF}; void debug_print_vector(const char *name, size_t len, const float *data, size_t stride, bool index, bool debug); static float gold_correlate_step(const size_t ncode, const float a[DSSS_CORRELATION_LENGTH], size_t offx, bool debug); static float cwt_convolve_step(const float v[DSSS_WAVELET_LUT_SIZE], size_t offx); -#if 0 static float run_iir(const float x, const int order, const struct iir_biquad q[order], struct iir_biquad_state st[order]); static float run_biquad(float x, const struct iir_biquad *const q, struct iir_biquad_state *const restrict st); -#endif static void matcher_init(struct matcher_state states[static DSSS_MATCHER_CACHE_SIZE]); static void matcher_tick(struct matcher_state states[static DSSS_MATCHER_CACHE_SIZE], uint64_t ts, int peak_ch, float peak_ampl); @@ -41,7 +39,7 @@ void debug_print_vector(const char *name, size_t len, const float *data, size_t if (index) { DEBUG_PRINTN(" %16s [", ""); for (size_t i=0; i<len; i++) - DEBUG_PRINTN("%8zd ", i); + DEBUG_PRINTN("%8zu ", i); DEBUG_PRINTN("]\n"); } @@ -62,6 +60,8 @@ void dsss_demod_init(struct dsss_demod_state *st) { void dsss_demod_step(struct dsss_demod_state *st, float new_value, uint64_t ts) { //const float hole_patching_threshold = 0.01 * DSSS_CORRELATION_LENGTH; + bool log = false; + bool log_groups = true; st->signal[st->signal_wpos] = new_value; st->signal_wpos = (st->signal_wpos + 1) % ARRAY_LENGTH(st->signal); @@ -80,6 +80,7 @@ void dsss_demod_step(struct dsss_demod_state *st, float new_value, uint64_t ts) for (size_t i=0; i<DSSS_GOLD_CODE_COUNT; i++) avg += fabsf(cwt[i]); avg /= (float)DSSS_GOLD_CODE_COUNT; + if (log) DEBUG_PRINTN("%6zu: %f ", ts, avg); /* FIXME fix this filter */ //avg = run_iir(avg, ARRAY_LENGTH(cwt_filter_bq), cwt_filter_bq, st->cwt_filter.st); @@ -89,18 +90,21 @@ void dsss_demod_step(struct dsss_demod_state *st, float new_value, uint64_t ts) bool found = false; for (size_t i=0; i<DSSS_GOLD_CODE_COUNT; i++) { float val = cwt[i] / avg; + if (log) DEBUG_PRINTN("%f ", cwt[i]); + if (log) DEBUG_PRINTN("%f ", val); if (fabsf(val) > fabsf(max_val)) { max_val = val; max_ch = i; max_ts = ts; - - if (fabsf(val) > DSSS_THESHOLD_FACTOR) - found = true; } + + if (fabsf(val) > DSSS_THESHOLD_FACTOR) + found = true; } + if (log) DEBUG_PRINTN("%f %d ", max_val, found); + if (log) DEBUG_PRINTN("\n"); - /* FIXME: skipped sample handling here */ matcher_tick(st->matcher_cache, ts, max_ch, max_val); if (found) { @@ -116,6 +120,7 @@ void dsss_demod_step(struct dsss_demod_state *st, float new_value, uint64_t ts) /* We're between groups */ return; + if (log_groups) DEBUG_PRINTN("GROUP: %zu %d %f\n", st->group.max_ts, st->group.max_ch, st->group.max); /* A group ended. Process result. */ group_received(st); @@ -152,7 +157,9 @@ void matcher_tick(struct matcher_state states[static DSSS_MATCHER_CACHE_SIZE], u const float score_depreciation = 0.1f; /* 0.0 -> no depreciation, 1.0 -> complete disregard */ const int current_phase = ts % DSSS_CORRELATION_LENGTH; const int max_skips = TRANSMISSION_SYMBOLS/4*3; + bool debug = true; + bool header_printed = false; for (size_t i=0; i<DSSS_MATCHER_CACHE_SIZE; i++) { if (states[i].last_phase == -1) continue; /* Inactive entry */ @@ -161,6 +168,11 @@ void matcher_tick(struct matcher_state states[static DSSS_MATCHER_CACHE_SIZE], u /* Skip sampling */ float score = fabsf(peak_ampl) * (1.0f - skip_sampling_depreciation); if (score > states[i].candidate_score) { + if (debug && !header_printed) { + header_printed = true; + DEBUG_PRINTN("windows %zu\n", ts); + } + if (debug) DEBUG_PRINTN(" skip %d old=%f new=%f\n", i, states[i].candidate_score, score); /* We win, update candidate */ assert(i < DSSS_MATCHER_CACHE_SIZE); states[i].candidate_score = score; @@ -175,7 +187,15 @@ void matcher_tick(struct matcher_state states[static DSSS_MATCHER_CACHE_SIZE], u * process a group a couple ticks after its peak. We have to make sure the window is still open at this point. * This means we have to match against group_phase_tolerance should a little bit loosely. */ - if (abs(states[i].last_phase - current_phase) == group_phase_tolerance + DSSS_DECIMATION) { + int phase_delta = current_phase - states[i].last_phase; + if (phase_delta < 0) + phase_delta += DSSS_CORRELATION_LENGTH; + if (phase_delta == group_phase_tolerance + DSSS_DECIMATION) { + if (debug && !header_printed) { + header_printed = true; + DEBUG_PRINTN("windows %zu\n", ts); + } + if (debug) DEBUG_PRINTN(" %d ", i); /* Process window results */ assert(i < DSSS_MATCHER_CACHE_SIZE); assert(0 <= states[i].data_pos && states[i].data_pos < TRANSMISSION_SYMBOLS); @@ -183,17 +203,21 @@ void matcher_tick(struct matcher_state states[static DSSS_MATCHER_CACHE_SIZE], u states[i].data_pos = states[i].data_pos + 1; states[i].last_score = score_depreciation * states[i].last_score + (1.0f - score_depreciation) * states[i].candidate_score; + if (debug) DEBUG_PRINTN("commit pos=%d val=%d score=%f ", states[i].data_pos, states[i].candidate_data, states[i].last_score); states[i].candidate_score = 0.0f; states[i].last_skips += states[i].candidate_skips; if (states[i].last_skips > max_skips) { + if (debug) DEBUG_PRINTN("expire "); states[i].last_phase = -1; /* invalidate entry */ } else if (states[i].data_pos == TRANSMISSION_SYMBOLS) { + if (debug) DEBUG_PRINTN("match "); /* Frame received completely */ handle_dsss_received(states[i].data); states[i].last_phase = -1; /* invalidate entry */ } + if (debug) DEBUG_PRINTN("\n"); } } } @@ -211,6 +235,7 @@ static float score_group(const struct group *g, int phase_delta) { } void group_received(struct dsss_demod_state *st) { + bool debug = true; const int group_phase = st->group.max_ts % DSSS_CORRELATION_LENGTH; /* This is the score of a decoding starting at this group (with no context) */ float base_score = score_group(&st->group, 0); @@ -234,6 +259,7 @@ void group_received(struct dsss_demod_state *st) { float group_score = score_group(&st->group, phase_delta); if (st->matcher_cache[i].candidate_score < group_score) { assert(i < DSSS_MATCHER_CACHE_SIZE); + if (debug) DEBUG_PRINTN(" appending %zu %d score=%f pd=%d\n", i, decode_peak(st->group.max_ch, st->group.max), group_score, phase_delta); /* Append to entry */ st->matcher_cache[i].candidate_score = group_score; st->matcher_cache[i].candidate_phase = group_phase; @@ -243,7 +269,8 @@ void group_received(struct dsss_demod_state *st) { } /* Search for weakest entry */ - float score = st->matcher_cache[i].last_score; + /* TODO figure out this fitness function */ + float score = st->matcher_cache[i].last_score * (1.5f + 1.0f/st->matcher_cache[i].data_pos); if (score < min_score) { min_idx = i; min_score = score; @@ -252,6 +279,7 @@ void group_received(struct dsss_demod_state *st) { /* If we found empty entries, replace one by a new decoding starting at this group */ if (empty_idx >= 0) { + if (debug) DEBUG_PRINTN(" empty %zd %d\n", empty_idx, decode_peak(st->group.max_ch, st->group.max)); assert(0 <= empty_idx && empty_idx < DSSS_MATCHER_CACHE_SIZE); st->matcher_cache[empty_idx].last_phase = group_phase; st->matcher_cache[empty_idx].candidate_score = base_score; @@ -264,6 +292,7 @@ void group_received(struct dsss_demod_state *st) { /* If the weakest decoding in cache is weaker than a new decoding starting here, replace it */ } else if (min_score < base_score && min_idx >= 0) { + if (debug) DEBUG_PRINTN(" min %zd %d\n", min_idx, decode_peak(st->group.max_ch, st->group.max)); assert(0 <= min_idx && min_idx < DSSS_MATCHER_CACHE_SIZE); st->matcher_cache[min_idx].last_phase = group_phase; st->matcher_cache[min_idx].candidate_score = base_score; @@ -276,7 +305,6 @@ void group_received(struct dsss_demod_state *st) { } } -#if 0 float run_iir(const float x, const int order, const struct iir_biquad q[order], struct iir_biquad_state st[order]) { float intermediate = x; for (int i=0; i<(order+1)/2; i++) @@ -292,7 +320,6 @@ float run_biquad(float x, const struct iir_biquad *const q, struct iir_biquad_st st->reg[0] = intermediate; return out; } -#endif float cwt_convolve_step(const float v[DSSS_WAVELET_LUT_SIZE], size_t offx) { float sum = 0.0f; diff --git a/controller/fw/src/main.c b/controller/fw/src/main.c index 6589297..814c723 100644 --- a/controller/fw/src/main.c +++ b/controller/fw/src/main.c @@ -216,23 +216,14 @@ int main(void) con_printf("Booted.\r\n"); while (23) { if (adc_fft_buf_ready_idx != -1) { + for (int i=0; i<168*1000*2; i++) + asm volatile ("nop"); GPIOA->BSRR = 1<<11; - //adc_fft_buf_ready_idx = !adc_fft_buf_ready_idx; /* DEBUG */ - //DEBUG: - //memcpy(adc_fft_buf[!adc_fft_buf_ready_idx], adc_fft_buf[adc_fft_buf_ready_idx] + FMEAS_FFT_LEN/2, sizeof(adc_fft_buf[0][0]) * FMEAS_FFT_LEN/2); + memcpy(adc_fft_buf[!adc_fft_buf_ready_idx], adc_fft_buf[adc_fft_buf_ready_idx] + FMEAS_FFT_LEN/2, sizeof(adc_fft_buf[0][0]) * FMEAS_FFT_LEN/2); + GPIOA->BSRR = 1<<11<<16; for (int i=0; i<168*1000*2; i++) asm volatile ("nop"); - /* BEGIN DEBUG */ - con_printf_blocking("\r\n%06d: ", freq_sample_ts); - int old_idx = adc_fft_buf_ready_idx; - for (int i=0; i<FMEAS_FFT_LEN/2; i++) - con_printf_blocking("%03x ", adc_fft_buf[old_idx][FMEAS_FFT_LEN/2 + i]); - adc_fft_buf_ready_idx = -1; - freq_sample_ts++; /* TODO: also increase in case of freq measurement error? */ - GPIOA->BSRR = 1<<11<<16; - continue; - /* END DEBUG */ GPIOA->BSRR = 1<<11; float out; diff --git a/controller/fw/src/sr_global.h b/controller/fw/src/sr_global.h index 451cce0..97db4e4 100644 --- a/controller/fw/src/sr_global.h +++ b/controller/fw/src/sr_global.h @@ -2,9 +2,12 @@ #define __SR_GLOBAL_H__ #include <stdint.h> +#include <sys/types.h> + +#ifndef SIMULATION #include <stm32f407xx.h> #include <stm32f4_isr.h> -#include <sys/types.h> +#endif #define UNUSED(x) ((void) x) #define ARRAY_LENGTH(x) (sizeof(x) / sizeof(x[0])) diff --git a/lab-windows/scratch.ipynb b/lab-windows/scratch.ipynb index da795fd..d31ef92 100644 --- a/lab-windows/scratch.ipynb +++ b/lab-windows/scratch.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 3, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -10,6 +10,7 @@ "import csv\n", "import re\n", "import math\n", + "import struct\n", "\n", "import numpy as np\n", "from matplotlib import pyplot as plt\n", @@ -20,7 +21,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -29,7 +30,7 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -46,21 +47,13 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": 12, "metadata": {}, "outputs": [ { - "name": "stderr", - "output_type": "stream", - "text": [ - "<ipython-input-64-bdef8329a3e8>:1: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n", - " fig, axs = plt.subplots(2, 2, figsize=(15, 9))\n" - ] - }, - { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c040d7b8285a4444abc23ec0ef8c0d45", + "model_id": "57f40afcd2214d0392a5fc7577843454", "version_major": 2, "version_minor": 0 }, @@ -97,7 +90,146 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "8b2507e2a7a24129acddcdbb4356f8df", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axs = plt.subplots(2, 2, figsize=(15, 9))\n", + "ax1, ax2, ax3, ax4 = axs.flatten()\n", + "\n", + "freqs_mod, freqs_clean = read_freq_log('data/meas_sig_audio_test.log'), read_freq_log('/mnt/c/Users/jaseg/shared/dsss_test_50hz_clean_improved.log')\n", + "\n", + "ax1.plot(freqs_mod)\n", + "ax1.grid()\n", + "\n", + "ax2.plot(freqs_clean)\n", + "ax2.grid()\n", + "\n", + "w = 512\n", + "\n", + "ax3.psd(freqs_mod[:80000], w, 100/128 * 10)\n", + "ax4.psd(freqs_clean[:80000], w, 100/128 * 10)\n", + "None" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [], + "source": [ + "with open('data/dsss_test_demod_fixed_03.bin', 'wb') as f:\n", + " for freq in read_freq_log('data/dsss_test_demod_fixed_03.log'):\n", + " f.write(struct.pack('f', freq))" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "d3a944613a184c44be006ef957770e31", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "[<matplotlib.lines.Line2D at 0x7f49ad047130>]" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "ax.plot(read_freq_log('data/dsss_test_demod_fixed_03.log'))" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "5d366527c29840da9404ec7b1e1e0665", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(84250, 86000)" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "fig, axs = plt.subplots(2, 1, figsize=(15, 6))\n", + "ax1, ax2 = axs.flatten()\n", + "\n", + "freqs_mod = read_freq_log('data/meas_sig_audio_test.log')\n", + "\n", + "with open('data/meas_sig_audio_test.bin', 'wb') as f:\n", + " for freq in freqs_mod:\n", + " f.write(struct.pack('f', freq))\n", + " \n", + "with open('data/ref_sig_audio_test.bin', 'rb') as f:\n", + " freqs_ref = np.array(list(struct.iter_unpack('f', f.read())))\n", + "\n", + "ax1.plot(freqs_mod)\n", + "ax1.set_title('measured')\n", + "ax1.grid()\n", + "ax2.plot(freqs_ref)\n", + "ax2.set_title('reference')\n", + "ax2.grid()\n", + "\n", + "ax1.set_xlim([84250+47, 86000+47])\n", + "ax2.set_xlim([84250, 86000])" + ] + }, + { + "cell_type": "code", + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -109,13 +241,13 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f5f37f4970ae4d0fb5677c55045c6ebf", + "model_id": "bc4efa3809dd423482f1ef34974192c0", "version_major": 2, "version_minor": 0 }, @@ -125,41 +257,73 @@ }, "metadata": {}, "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "<ipython-input-19-55f36f700399>:6: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n", + " fig.tight_layout()\n" + ] } ], "source": [ - "fig, axs = plt.subplots(2, 2, figsize=(15, 9))\n", + "# We see artifacts of the 128sp processing window in the analog readings if we process a buffer immediately after capture. We can reduce these artifacts by deferring the sampling a few milliseconds into the capture period.\n", + "# The reason for this is presumably a suboptimal power layout on the cheap f407 devboard leading to CPU load changes dumping noise into our ADC supply.\n", + "# In time domain plots we can see frequent high spikes in ADC counts that would be in accordance with this conjecture.\n", + "\n", + "fig, axs = plt.subplots(2, 2, figsize=(15, 9), sharey='row', gridspec_kw={'hspace': 0.2, 'wspace': 0.05})\n", + "fig.tight_layout()\n", "ax1, ax2, ax3, ax4 = axs.flatten()\n", "\n", - "raw_50hz, raw_silence = read_raw_log('/mnt/c/Users/jaseg/shared/rawlog_50hz_clean.log'), read_raw_log('/mnt/c/Users/jaseg/shared/rawlog_silence_clean3.log')\n", + "raw_left, raw_right = read_raw_log('data/rawlog_silence_clean.log'), read_raw_log('data/rawlog_silence_clean3.log')\n", + "raw_left = raw_left[26000:-10000].astype(float)\n", "\n", - "ax1.plot(raw_50hz)\n", + "raw_right = raw_right[26000:]\n", + "raw_right = raw_right[:len(raw_left)].astype(float)\n", + "\n", + "raw_left -= np.mean(raw_left)\n", + "raw_right -= np.mean(raw_right)\n", + "\n", + "ax1.set_title('Immediate processing')\n", + "ax1.plot(raw_left)\n", "ax1.grid()\n", - "#for x in range(0, len(raw_50hz), 128):\n", - "# ax1.axvline(x, color='red', alpha=0.3)\n", + "for x in range(0, len(raw_left), 128):\n", + " ax1.axvline(x, color='red', alpha=0.3)\n", "\n", - "ax2.plot(raw_silence)\n", + "ax2.set_title('Deferred processing')\n", + "ax2.plot(raw_right)\n", "ax2.grid()\n", - "#for x in range(0, len(raw_silence), 128):\n", - "# ax2.axvline(x, color='red', alpha=0.3)\n", + "for x in range(0, len(raw_right), 128):\n", + " ax2.axvline(x, color='red', alpha=0.3)\n", "\n", - "w = 16384\n", + "ax1.set_xlim([0, 1000])\n", + "ax1.set_ylim([-200, 200])\n", + "ax2.set_xlim([0, 1000])\n", + "ax2.set_ylim([-200, 200])\n", + "ax1.set_xlabel('t [ms]')\n", + "ax2.set_xlabel('t [ms]')\n", + "ax1.set_ylabel('ADC reading [counts]')\n", "\n", - "ax3.psd(raw_50hz, w, 1e3)\n", + "w = 2048\n", "\n", - "ax4.psd(raw_silence, w, 1e3)\n", + "ax3.psd(raw_left, w, 1e3)\n", + "ax4.psd(raw_right, w, 1e3)\n", + "ax3.set_ylim([-10, 26])\n", + "ax4.set_ylim([-10, 26])\n", + "ax4.set_ylabel(None)\n", "None" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "eba72dea09bc45ff9de68cb22b352fb3", + "model_id": "291774359d674902aad182268ec9c469", "version_major": 2, "version_minor": 0 }, @@ -174,8 +338,8 @@ "source": [ "fig, ax = plt.subplots(figsize=(12, 6))\n", "\n", - "raw_silence = read_raw_log('/mnt/c/Users/jaseg/shared/rawlog_silence_clean.log')\n", - "raw_silence2 = read_raw_log('/mnt/c/Users/jaseg/shared/rawlog_silence_clean3.log')\n", + "raw_silence = read_raw_log('data/rawlog_silence_clean.log')\n", + "raw_silence2 = read_raw_log('data/rawlog_silence_clean3.log')\n", "\n", "raw_silence = raw_silence.reshape([-1, 128])\n", "le_mean = raw_silence.mean(axis=0)\n", @@ -189,21 +353,21 @@ }, { "cell_type": "code", - "execution_count": 90, + "execution_count": 40, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "<ipython-input-90-5a220009d359>:1: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n", - " fig, axs = plt.subplots(2, 2, figsize=(15, 9))\n" + "<ipython-input-40-132a47f1202f>:1: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n", + " fig, axs = plt.subplots(4, 1, figsize=(15, 9), sharex=True)\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "d9143b226974466aaec05a70592ac69e", + "model_id": "2740bc857e6c4296b9ca74ada34fbb1d", "version_major": 2, "version_minor": 0 }, @@ -216,23 +380,119 @@ } ], "source": [ - "fig, axs = plt.subplots(2, 2, figsize=(15, 9))\n", + "fig, axs = plt.subplots(4, 1, figsize=(15, 9), sharex=True)\n", "ax1, ax2, ax3, ax4 = axs.flatten()\n", "\n", - "raw_d, raw_e = read_raw_log('/mnt/c/Users/jaseg/shared/rawlog_test_d.log'), read_raw_log('/mnt/c/Users/jaseg/shared/rawlog_test_e.log')\n", + "#with open('data/meas_sig_audio_test_processed.log') as f:\n", + "with open('data/meas_sig_audio_test_fixed_03.log') as f:\n", + " lines = f.readlines()\n", + " data = np.array([ [float(x) for x in line.split(': ')[1].split()] for line in lines if not line.startswith('GROUP:') ])\n", + " groups = [ int(line.split(' ')[2]) for line in lines if line.startswith('GROUP:') ]\n", "\n", - "ax1.plot(raw_d)\n", + "ax1.plot(data[:,0])\n", "ax1.grid()\n", + "ax1.set_xlim([4000, 16000])\n", + "ax1.set_ylim([-0.02, 0.1])\n", "\n", - "ax2.plot(raw_e)\n", + "ax2.plot(data[:,1:-2:2])\n", "ax2.grid()\n", + "ax2.set_ylim([-0.6, 0.6])\n", "\n", - "w = 16384\n", + "ax3.plot(data[:,2:-2:2])\n", + "ax3.grid()\n", "\n", - "ax3.psd(raw_d, w, 1e3)\n", - "ax4.psd(raw_e, w, 1e3)\n", - "#ax3.psd(raw_silence, w, 1e3)\n", - "None" + "ax4.plot(data[:,-2:])\n", + "ax4.grid()\n", + "\n", + "for x in groups:\n", + " ax4.axvline(x, color='red', alpha=0.4)" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<matplotlib.lines.Line2D at 0x7f497186d6d0>" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ax4.axvline(12433)\n", + "ax4.axvline(12164)\n", + "ax4.axvline(12475)" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "cff56db4807048cda06ae8b15b0c6344", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axs = plt.subplots(4, 1, figsize=(15, 9), sharex=True)\n", + "ax1, ax2, ax3, ax4 = axs.flatten()\n", + "\n", + "with open('data/ref_sig_audio_test_processed.log') as f:\n", + " lines = f.readlines()\n", + " data = np.array([ [float(x) for x in line.split(': ')[1].split()] for line in lines if not line.startswith('GROUP:') ])\n", + " groups = [ int(line.split(': ')[1]) for line in lines if line.startswith('GROUP:') ]\n", + "\n", + "ax1.plot(data[:,0])\n", + "ax1.grid()\n", + "ax1.set_xlim([82000, 95000])\n", + "ax1.set_ylim([-0.02, 0.1])\n", + "\n", + "ax2.plot(data[:,1:-2:2])\n", + "ax2.grid()\n", + "ax2.set_ylim([-0.6, 0.6])\n", + "\n", + "ax3.plot(data[:,2:-2:2])\n", + "ax3.grid()\n", + "\n", + "ax4.plot(data[:,-2:])\n", + "ax4.grid()\n", + "\n", + "for x in groups:\n", + " ax4.axvline(x, color='red', alpha=0.4)" + ] + }, + { + "cell_type": "code", + "execution_count": 93, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[516, 518, 4402, 4404, 5537, 7238, 12585, 17497, 17724, 34074, 34076, 41628, 44677, 46287, 49371, 49837, 53877, 54554, 56666, 56949, 60923, 67313, 67744, 67746, 68392, 79601, 84707, 84709, 84711, 85017, 85019, 85021, 85327, 85329, 85637, 85947, 85949, 85951, 86257, 86259, 86261, 86567, 86569, 86571, 86877, 86879, 86881, 87187, 87189, 87191, 87498, 87500, 87807, 87809, 87811, 88117, 88119, 88121, 88427, 88429, 88431, 88488, 88737, 88739, 88741, 89047, 89049, 89051, 89357, 89359, 89361, 89668, 89670, 89730, 89978, 89980, 90287, 90289, 90291, 90598, 90600, 90602, 90907, 90909, 90911, 91217, 91219, 91221, 91527, 91529, 91531, 91837, 91839, 91841, 92148, 92150, 92458, 92460, 92768, 92770, 93078, 93080, 93388, 93390, 93392, 93698, 93700, 93702, 94008, 94010, 94318, 94320]\n" + ] + } + ], + "source": [ + "print(groups)" ] }, { |