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-rw-r--r--lab-windows/scratch.ipynb251
1 files changed, 249 insertions, 2 deletions
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",
@@ -18,7 +20,7 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
@@ -27,6 +29,251 @@
},
{
"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": [
+ "<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",
+ "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": [
+ "<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"
+ ]
+ },
+ {
+ "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": [
+ "<ipython-input-79-e66d1dcc2be5>: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,
"metadata": {},
"outputs": [
generated by cgit (git 2.34.1) at 2024-11-21 16:30:26 +0000