From 99b9c0ecc13636553762ec4250adb6b6a50a097c Mon Sep 17 00:00:00 2001 From: jaseg Date: Thu, 20 Feb 2020 19:21:09 +0000 Subject: Prettify fft comparisons --- lab-windows/dsss_experiments-ber.ipynb | 109 ++++++++++++++++++++++-------- lab-windows/grid_frequency_spectra.ipynb | 24 +++++-- lab-windows/grid_scope.ipynb | 111 ++++++++++++++++++++++--------- 3 files changed, 180 insertions(+), 64 deletions(-) (limited to 'lab-windows') diff --git a/lab-windows/dsss_experiments-ber.ipynb b/lab-windows/dsss_experiments-ber.ipynb index d4a2992..91c1daf 100644 --- a/lab-windows/dsss_experiments-ber.ipynb +++ b/lab-windows/dsss_experiments-ber.ipynb @@ -104,7 +104,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 221, "metadata": {}, "outputs": [ { @@ -116,7 +116,7 @@ } ], "source": [ - "with open('/mnt/c/Users/jaseg/shared/raw_freq.bin', 'rb') as f:\n", + "with open('data/raw_freq.bin', 'rb') as f:\n", " mains_noise = np.copy(np.frombuffer(f.read(), dtype='float32'))\n", " print('mean:', np.mean(mains_noise), 'len:', len(mains_noise))\n", " mains_noise -= np.mean(mains_noise)" @@ -610,13 +610,21 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 220, "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=(12, 9))\n" + ] + }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "3bcd7f07ef26458da90f748fd74addfb", + "model_id": "f63ab2c387f948b29d992a3edd04f4fa", "version_major": 2, "version_minor": 0 }, @@ -630,10 +638,10 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 7, + "execution_count": 220, "metadata": {}, "output_type": "execute_result" } @@ -645,7 +653,7 @@ "# ser, std = np.mean(sers), np.std(sers)\n", "# results = { nbits: [ res.get() for res in series ] for nbits, series in results.items() }\n", "\n", - "with open(f'/mnt/c/Users/jaseg/shared/dsss_experiments_res-2020-02-19-19-30-05.json', 'r') as f:\n", + "with open(f'data/dsss_experiments_res-2020-02-19-19-30-05.json', 'r') as f:\n", " results = json.load(f)\n", "\n", "for nbits, series in results.items():\n", @@ -666,21 +674,21 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 218, "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", + ":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, cbar_ax), (intercept_ax, empty)) = plt.subplots(2, 2, figsize=(12, 9), gridspec_kw={'width_ratios': [1, 0.05]})\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c05f590a7c0040628c5c5d4032bb7c8e", + "model_id": "6651827b5eca4a0ba46effefd605f06c", "version_major": 2, "version_minor": 0 }, @@ -795,9 +803,9 @@ "\n", "results = []\n", "for fn in [\n", - " '/mnt/c/Users/jaseg/shared/dsss_experiments_res-2020-02-20-12-18-35.json',\n", - " '/mnt/c/Users/jaseg/shared/dsss_experiments_res-2020-02-20-12-26-07.json',\n", - " '/mnt/c/Users/jaseg/shared/dsss_experiments_res-2020-02-20-12-29-02.json'\n", + " 'data/dsss_experiments_res-2020-02-20-12-18-35.json',\n", + " 'data/dsss_experiments_res-2020-02-20-12-26-07.json',\n", + " 'data/dsss_experiments_res-2020-02-20-12-29-02.json'\n", "]:\n", " with open(fn, 'r') as f:\n", " results += json.load(f)\n", @@ -893,21 +901,21 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 268, "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, cbar_ax), (intercept_ax, empty)) = plt.subplots(2, 2, figsize=(12, 9), gridspec_kw={'width_ratios': [1, 0.05]})\n" + ":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, cbar_ax), (intercept_ax, empty)) = plt.subplots(2, 2, figsize=(12, 9), gridspec_kw={'width_ratios': [1, 0.05], 'hspace': 0.4})\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "fa93fb31355840148f941dab8b60f51c", + "model_id": "be4678ec02394b81b8aee83c759e1009", "version_major": 2, "version_minor": 0 }, @@ -922,21 +930,22 @@ "name": "stderr", "output_type": "stream", "text": [ - ":16: RuntimeWarning: divide by zero encountered in log10\n", + ":17: RuntimeWarning: divide by zero encountered in log10\n", " cm_func = lambda x: cmap(np.log10(x - min(decimations)) / (np.log10(max(decimations)) - np.log10(min(decimations))))\n" ] } ], "source": [ - "fig, ((ax, cbar_ax), (intercept_ax, empty)) = plt.subplots(2, 2, figsize=(12, 9), gridspec_kw={'width_ratios': [1, 0.05]})\n", + "fig, ((ax, cbar_ax), (intercept_ax, empty)) = plt.subplots(2, 2, figsize=(12, 9), gridspec_kw={'width_ratios': [1, 0.05], 'hspace': 0.4})\n", "empty.axis('off')\n", "#fig.tight_layout()\n", "\n", "results = []\n", + "\n", "for fn in [\n", - " '/mnt/c/Users/jaseg/shared/dsss_experiments_res-2020-02-20-14-10-13.json',\n", - " '/mnt/c/Users/jaseg/shared/dsss_experiments_res-2020-02-20-13-21-57.json',\n", - " '/mnt/c/Users/jaseg/shared/dsss_experiments_res-2020-02-20-13-23-47.json',\n", + " 'data/dsss_experiments_res-2020-02-20-14-10-13.json',\n", + " 'data/dsss_experiments_res-2020-02-20-13-21-57.json',\n", + " 'data/dsss_experiments_res-2020-02-20-13-23-47.json',\n", "]:\n", " with open(fn, 'r') as f:\n", " results += json.load(f)\n", @@ -953,16 +962,27 @@ " stds = np.array([ np.std(values) for values in data ])\n", " decimation_sers[decimation] = list(zip(amps, sers, stds))\n", " \n", + " amps = [ amp*1000 for amp in amps ]\n", " l, = ax.plot(amps, np.clip(sers, 0, 1), label=f'decimation={decimation}', color=cm_func(decimation))\n", " ax.fill_between(amps, np.clip(sers + stds, 0, 1), np.clip(sers - stds, 0, 1), facecolor=l.get_color(), alpha=0.2)\n", " ax.axhline(0.5, color='gray', ls=(0, (3, 4)), lw=0.8)\n", "ax.grid()\n", - "ax.set_xlabel('Amplitude in mHz')\n", + "ax.set_xlabel('Amplitude [mHz]')\n", "ax.set_ylabel('Symbol error rate')\n", "\n", "norm = matplotlib.colors.Normalize(vmin=np.log10(min(decimations)), vmax=np.log10(max(decimations)))\n", - "cb1 = matplotlib.colorbar.ColorbarBase(cbar_ax, cmap=cmap, norm=norm, orientation='vertical', label=\"Decimation\", ticks=[np.log10(d) for d in decimations])\n", - "cb1.ax.set_yticklabels([f'{d:.1f}' for d in decimations])\n", + "yticks = [np.log10(d) for d in decimations]\n", + "cb1 = matplotlib.colorbar.ColorbarBase(cbar_ax, cmap=cmap, norm=norm, orientation='vertical', ticks=yticks)\n", + "cb1t = cbar_ax.twinx()\n", + "cb1t.set_ylim(cbar_ax.get_ylim())\n", + "cb1t.set_yticks(yticks)\n", + "\n", + "cbar_ax.set_yticklabels([f'{d/sampling_rate:.1f}' for d in decimations])\n", + "cbar_ax.set_ylabel(\"chip duration [s]\", labelpad=-70)\n", + "\n", + "cb1t.set_yticklabels([f'{d/sampling_rate * 2**nbits:.1f}' for d in decimations])\n", + "cb1t.set_ylabel(\"symbol duration [s]\")\n", + "\n", "\n", "def plot_intercepts(ax, SER_TH = 0.5):\n", " intercepts = {}\n", @@ -988,8 +1008,10 @@ " std = data[:,1]\n", " \n", " ax.set_xlim([min(x), max(x)])\n", - " l = ax.plot(x, y, label='Amplitude at SER=0.5', color='orange')\n", - " ax.legend(loc=3)\n", + " y = [ v*1000 if v is not None else v for v in y ]\n", + " l = ax.plot(x, y, label='Amplitude at SER=0.5 [mHz]', color='orange')\n", + " #ax.legend(loc=3)\n", + " ax.set_ylabel('Amplitude at SER=0.5 [mHz]')\n", " ax.grid()\n", " \n", " x, y, std = zip(*[ (le_x, le_y, le_std) for le_x, le_y, le_std in zip(x, y, std) if le_y is not None ])\n", @@ -1002,12 +1024,43 @@ " ax.set_ylim([min(y)*0.9, max(y)*1.1])\n", " ax.set_xscale('log')\n", " ax.xaxis.set_major_formatter(matplotlib.ticker.FuncFormatter(lambda x, _: '{:g}'.format(x)))\n", - " ax.set_xticks([1, 2, 5, 10, 20, 50])\n", + " xticks = [1, 2, 5, 10, 20, 50]\n", + " ax.set_xticks(xticks)\n", + " ax.set_xticklabels([ f'{x/sampling_rate:.1f}' for x in xticks ])\n", " ax.set_xlim([1, 60])\n", + " ax.set_xlabel('chip duration [s]')\n", + " \n", + " axt = ax.twiny()\n", + " axt.set_xlim(ax.get_xlim())\n", + " axt.set_xscale('log')\n", + " axt.set_xticks(xticks)\n", + " axt.set_xticklabels([ f'{x/sampling_rate * 2**nbits:.1f}' for x in xticks ])\n", + " axt.set_xlabel('symbol duration [s]')\n", + " \n", " return l\n", "\n", "l1 = plot_intercepts(intercept_ax)\n" ] + }, + { + "cell_type": "code", + "execution_count": 227, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "41.6" + ] + }, + "execution_count": 227, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "13 * 2**5 / 10" + ] } ], "metadata": { diff --git a/lab-windows/grid_frequency_spectra.ipynb b/lab-windows/grid_frequency_spectra.ipynb index 3d375ef..7b187f5 100644 --- a/lab-windows/grid_frequency_spectra.ipynb +++ b/lab-windows/grid_frequency_spectra.ipynb @@ -141,13 +141,21 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 72, "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + ":20: 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()\n" + ] + }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "fd94bc97a276400db0539b703c4eeeac", + "model_id": "2991d932b113496a9135d569f9577abe", "version_major": 2, "version_minor": 0 }, @@ -161,10 +169,10 @@ { "data": { "text/plain": [ - "(1.6666666666666667e-05, 0.5)" + "(5e-07, 0.02)" ] }, - "execution_count": 23, + "execution_count": 72, "metadata": {}, "output_type": "execute_result" } @@ -194,8 +202,14 @@ "ax.xaxis.set_major_formatter(plt.FuncFormatter(lambda x, _pos: f'{1/x:.1f}'))\n", "ax.set_xlabel('T in s')\n", "ax.set_ylabel('Amplitude Δf')\n", + "\n", + "for i, t in enumerate([45, 60, 600, 1200, 1800, 3600]):\n", + " ax.axvline(1/t, color='red', alpha=0.5)\n", + " ax.annotate(f'{t} s', xy=(1/t, 3e-3), xytext=(-15, 0), xycoords='data', textcoords='offset pixels', rotation=90)\n", + "#ax.text(1/60, 10,'60 s', ha='left')\n", "ax.grid()\n", - "ax.set_xlim([1/60000, 0.5])" + "ax.set_xlim([1/60000, 0.5])\n", + "ax.set_ylim([5e-7, 2e-2])" ] }, { diff --git a/lab-windows/grid_scope.ipynb b/lab-windows/grid_scope.ipynb index 9f53906..6ce34fb 100644 --- a/lab-windows/grid_scope.ipynb +++ b/lab-windows/grid_scope.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 104, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -36,7 +36,7 @@ "metadata": {}, "outputs": [], "source": [ - "db = sqlite3.connect('/mnt/c/Users/jaseg/shared/waveform-raspi.sqlite3')" + "db = sqlite3.connect('data/waveform-raspi.sqlite3')" ] }, { @@ -100,7 +100,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f960454ab93244db97e039ae7ebd02ee", + "model_id": "55690b4f59d54454b83deb5200c05f09", "version_major": 2, "version_minor": 0 }, @@ -177,7 +177,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "264a9f8478e449289c1592c9595dc6cc", + "model_id": "cf5c2e35008740379508eaaedfcf3b31", "version_major": 2, "version_minor": 0 }, @@ -246,7 +246,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "7c2382eb8e124ef9b29546ecaed3e155", + "model_id": "efa9db02cdfc4f6c86d1eadd4769d097", "version_major": 2, "version_minor": 0 }, @@ -279,7 +279,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "d29e8ee5bf7f4e94a1749239aec24d6d", + "model_id": "e4122530c1444f75aca410ad51d4a733", "version_major": 2, "version_minor": 0 }, @@ -356,7 +356,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "47c40f28b5a34a94b4a631fd62107521", + "model_id": "a36a994f6f484a6cba81b6e680c9eee1", "version_major": 2, "version_minor": 0 }, @@ -412,7 +412,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "4a4cb62296df496bad37d93547d3c26a", + "model_id": "e4116959544f44f6a4b898419a5d51db", "version_major": 2, "version_minor": 0 }, @@ -490,7 +490,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -509,21 +509,13 @@ }, { "cell_type": "code", - "execution_count": 81, + "execution_count": 15, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - ":17: 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": "3809a1a83b5844e3906f1d74bcd15b5d", + "model_id": "09069e2c9cb740d5b58846371aeea0f2", "version_major": 2, "version_minor": 0 }, @@ -548,7 +540,7 @@ "5.0" ] }, - "execution_count": 81, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -585,21 +577,13 @@ }, { "cell_type": "code", - "execution_count": 156, + "execution_count": 16, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - ":20: 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()\n" - ] - }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "d137ae59ed7947ce8e3f7295e102f2f0", + "model_id": "b812e4b240a642398f09bb3cff8f5cee", "version_major": 2, "version_minor": 0 }, @@ -616,7 +600,7 @@ "(1.6666666666666667e-05, 0.5)" ] }, - "execution_count": 156, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -649,6 +633,71 @@ "ax.grid()\n", "ax.set_xlim([1/60000, 0.5])" ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "c835382368b6423ab5446835c5785afd", + "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": [ + "(5e-07, 0.02)" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Number of samplepoints\n", + "N = len(data)\n", + "# sample spacing\n", + "T = 1.0 / 10.0\n", + "x = np.linspace(0.0, N*T, N)\n", + "yf = scipy.fftpack.fft(data)\n", + "xf = np.linspace(0.0, 1.0/(2.0*T), N//2)\n", + "\n", + "yf = 2.0/N * np.abs(yf[:N//2])\n", + "\n", + "average_from = lambda val, start, average_width: np.hstack([val[:start], [ np.mean(val[i:i+average_width]) for i in range(start, len(val), average_width) ]])\n", + "\n", + "average_width = 6\n", + "average_start = 20\n", + "yf = average_from(yf, average_start, average_width)\n", + "xf = average_from(xf, average_start, average_width)\n", + "yf = average_from(yf, 70, 4)\n", + "xf = average_from(xf, 70, 4)\n", + "\n", + "fig, ax = plt.subplots()\n", + "ax.loglog(xf, yf)\n", + "ax.xaxis.set_major_formatter(plt.FuncFormatter(lambda x, _pos: f'{1/x:.1f}'))\n", + "ax.set_xlabel('T in s')\n", + "ax.set_ylabel('Amplitude Δf')\n", + "\n", + "for i, t in enumerate([45, 60, 600, 1200, 1800, 3600]):\n", + " ax.axvline(1/t, color='red', alpha=0.5)\n", + " ax.annotate(f'{t} s', xy=(1/t, 3e-5), xytext=(-15, 0), xycoords='data', textcoords='offset pixels', rotation=90)\n", + "#ax.text(1/60, 10,'60 s', ha='left')\n", + "ax.grid()\n", + "ax.set_xlim([1/60000, 0.5])\n", + "ax.set_ylim([5e-7, 2e-2])" + ] } ], "metadata": { -- cgit