add changes from jupyter server
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856e5fbf7d
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010335a394
@ -238,7 +238,6 @@
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"scrolled": false,
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"slideshow": {
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"slide_type": "fragment"
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}
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@ -429,15 +428,26 @@
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"# reconstruct signal\n",
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"g = np.ones_like(t_) * a0\n",
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"for k, (ak, bk) in enumerate(zip(a, b)):\n",
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" g += ak * np.sin(bk*t_)\n",
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"\n",
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"# plotting\n",
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" g += ak * np.sin(bk*t_)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"slideshow": {
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"slide_type": "subslide"
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}
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},
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"outputs": [],
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"source": [
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"# Cell 7b: plotting\n",
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"plt.plot(t_, square, 'r', label='original signal') \n",
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"plt.plot(t_, g, 'g', label='Reihenentwicklung')\n",
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"plt.ticklabel_format(axis='y', style='sci', scilimits=(-1,1))\n",
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"plt.xlabel('time [sec]')\n",
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"plt.ylabel('amplitude')\n",
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"#plt.ylim(-1.1,1.1)\n",
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"#plt.ylim(0.9,1.1)\n",
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"plt.legend()\n",
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"plt.show()"
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]
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@ -494,14 +504,14 @@
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"scrolled": true,
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"scrolled": false,
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"slideshow": {
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"slide_type": "subslide"
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}
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},
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"outputs": [],
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"source": [
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"#plotting\n",
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"#Cell 8b: plotting\n",
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"plt.subplot(311)\n",
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"plt.title('Time Domain')\n",
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"plt.plot(t, square, linewidth=1)\n",
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@ -12,7 +12,7 @@
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" <div style=\"float: right ; margin: 50px ; padding: 20px ; background: rgba(255 , 255 , 255 , 0.7) ; width: 50% ; height: 150px\">\n",
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" <div style=\"position: relative ; top: 50% ; transform: translatey(-50%)\">\n",
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" <div style=\"font-size: xx-large ; font-weight: 900 ; color: rgba(0 , 0 , 0 , 0.8) ; line-height: 100%\">Signal Processing</div>\n",
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" <div style=\"font-size: large ; padding-top: 20px ; color: rgba(0 , 0 , 0 , 0.5)\">Filtering Basics</div>\n",
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" <div style=\"font-size: large ; padding-top: 20px ; color: rgba(0 , 0 , 0 , 0.5)\">Filtering Basics - Solution</div>\n",
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" </div>\n",
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" </div>\n",
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"</div>\n",
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@ -157,6 +157,7 @@
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},
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"outputs": [],
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"source": [
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"# Cell 1b: print stats\n",
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"print(st[0].stats)"
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]
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},
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@ -206,7 +207,7 @@
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},
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"outputs": [],
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"source": [
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"# filtered traces\n",
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"# Cell 2b: filtered traces\n",
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"stHP = st.copy()\n",
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"stHP.filter('highpass', freq=f0, corners=corners, zerophase=True)\n",
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"stLP = st.copy()\n",
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@ -229,13 +230,15 @@
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"execution_count": null,
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"metadata": {
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"slideshow": {
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"rise": {
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"scroll": true
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},
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"slide_type": "subslide"
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}
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},
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"outputs": [],
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"source": [
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"# ---------------------------------------------------------------\n",
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"# plot\n",
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"# Cell 2c - plot\n",
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"plt.rcParams['figure.figsize'] = 17, 17\n",
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"tx1 = 3000\n",
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"tx2 = 8000\n",
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@ -392,7 +395,7 @@
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},
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"outputs": [],
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"source": [
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"# plot - comment single lines to better see the remaining ones\n",
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"# Cell 3b: plot - comment single lines to better see the remaining ones\n",
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"plt.rcParams['figure.figsize'] = 15, 4\n",
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"plt.plot(t, tr.data, 'k', label='original', linewidth=1.)\n",
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"plt.plot(t, tr_filt.data, 'b', label='causal, n=2', linewidth=1.2)\n",
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@ -491,6 +494,7 @@
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},
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"outputs": [],
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"source": [
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"# Cell 5b: plot\n",
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"plt.rcParams['figure.figsize'] = 17, 21\n",
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"fig = plt.figure()\n",
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"ax1 = fig.add_subplot(7,1,1)\n",
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@ -574,6 +578,13 @@
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"\n",
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"6) There is no clear S-wave visible. Also in the horizontal components (channel 0 and 1) almost no S-wave energy is visible. This is a clear hint for an explosive type of event. Indeed, this is the recording of a nuclear test explosion. The recording with exactly these bandpass filters was used as cover figure for the book 'Quantitative Seismology' by Keiiti Aki and Paul G. Richards, 2nd edition."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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@ -594,6 +605,9 @@
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.6"
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},
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"rise": {
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"scroll": true
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}
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},
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"nbformat": 4,
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