From 80de5c2e24056d38e49c4aeff4f84a299165d933 Mon Sep 17 00:00:00 2001 From: jaseg Date: Tue, 17 Mar 2020 17:20:43 +0100 Subject: Debugging signal capture subsystem --- lab-windows/scratch.ipynb | 251 +++++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 249 insertions(+), 2 deletions(-) (limited to 'lab-windows') diff --git a/lab-windows/scratch.ipynb b/lab-windows/scratch.ipynb index 93a11fe..da795fd 100644 --- a/lab-windows/scratch.ipynb +++ b/lab-windows/scratch.ipynb @@ -2,12 +2,14 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "import json\n", "import csv\n", + "import re\n", + "import math\n", "\n", "import numpy as np\n", "from matplotlib import pyplot as plt\n", @@ -18,13 +20,258 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "%matplotlib widget" ] }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [], + "source": [ + "def read_freq_log(fn):\n", + " with open(fn) as f:\n", + " def parse_freq(f):\n", + " try:\n", + " return float(f)\n", + " except:\n", + " return 0\n", + " freqs = np.trim_zeros(np.array([ parse_freq(line.split()[1]) for line in f.readlines() if re.match('\\d+: .*', line) ]))\n", + " return freqs[np.nonzero(freqs)]" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + ":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", + "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, freqs_clean_gnd = read_freq_log('/mnt/c/Users/jaseg/shared/dsss_test.log'), read_freq_log('/mnt/c/Users/jaseg/shared/dsss_test_50hz_clean.log'), read_freq_log('/mnt/c/Users/jaseg/shared/dsss_test_50hz_clean_gndtest.log')\n", + "\n", + "ax1.plot(freqs_mod)\n", + "ax1.grid()\n", + "\n", + "ax2.plot(freqs_clean)\n", + "ax2.grid()\n", + "\n", + "ax4.plot(freqs_clean_gnd)\n", + "ax4.grid()\n", + "\n", + "w = 512\n", + "\n", + "ax3.psd(freqs_mod[:80000], w, 100/128 * 10)\n", + "ax3.psd(freqs_clean[:80000], w, 100/128 * 10)\n", + "ax3.psd(freqs_clean_gnd[:80000], w, 100/128 * 10)\n", + "None" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "def read_raw_log(fn):\n", + " with open(fn) as f:\n", + " vals = np.array([ int(x, 16) for line in f for x in line.partition(':')[2].split() ])\n", + " return vals" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "f5f37f4970ae4d0fb5677c55045c6ebf", + "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", + "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", + "\n", + "ax1.plot(raw_50hz)\n", + "ax1.grid()\n", + "#for x in range(0, len(raw_50hz), 128):\n", + "# ax1.axvline(x, color='red', alpha=0.3)\n", + "\n", + "ax2.plot(raw_silence)\n", + "ax2.grid()\n", + "#for x in range(0, len(raw_silence), 128):\n", + "# ax2.axvline(x, color='red', alpha=0.3)\n", + "\n", + "w = 16384\n", + "\n", + "ax3.psd(raw_50hz, w, 1e3)\n", + "\n", + "ax4.psd(raw_silence, w, 1e3)\n", + "None" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "eba72dea09bc45ff9de68cb22b352fb3", + "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, 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", + "\n", + "raw_silence = raw_silence.reshape([-1, 128])\n", + "le_mean = raw_silence.mean(axis=0)\n", + "ax.plot(le_mean - np.mean(le_mean))\n", + "\n", + "raw_silence2 = raw_silence2.reshape([-1, 128])\n", + "le_mean2 = raw_silence2.mean(axis=0)\n", + "ax.plot(le_mean2 - np.mean(le_mean2))\n", + "ax.grid()" + ] + }, + { + "cell_type": "code", + "execution_count": 90, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + ":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": "d9143b226974466aaec05a70592ac69e", + "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", + "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", + "\n", + "ax1.plot(raw_d)\n", + "ax1.grid()\n", + "\n", + "ax2.plot(raw_e)\n", + "ax2.grid()\n", + "\n", + "w = 16384\n", + "\n", + "ax3.psd(raw_d, w, 1e3)\n", + "ax4.psd(raw_e, w, 1e3)\n", + "#ax3.psd(raw_silence, w, 1e3)\n", + "None" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + ":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, ax = plt.subplots(figsize=(9, 5))\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "48b1d8b994594af79c3dca2bf9a6fb41", + "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, ax = plt.subplots(figsize=(9, 5))\n", + "\n", + "raw_c = read_raw_log('/mnt/c/Users/jaseg/shared/rawlog_test_c.log')\n", + "\n", + "ax.plot(raw_c[1000:2000])\n", + "ax.grid()" + ] + }, { "cell_type": "code", "execution_count": 25, -- cgit