Warning, /jana2/src/examples/InteractiveStreamingExample/jupyter/streamDet_Monitoring.ipynb is written in an unsupported language. File is not indexed.
0001 {
0002 "cells": [
0003 {
0004 "cell_type": "code",
0005 "execution_count": 5,
0006 "metadata": {},
0007 "outputs": [
0008 {
0009 "data": {
0010 "application/vnd.jupyter.widget-view+json": {
0011 "model_id": "ab29ad7c945b41c5bc0452800994d9b4",
0012 "version_major": 2,
0013 "version_minor": 0
0014 },
0015 "text/plain": [
0016 "Tab(children=(VBox(children=(BoundedIntText(value=5557, description='Port Number', max=6000, min=5000),)), VBo…"
0017 ]
0018 },
0019 "metadata": {},
0020 "output_type": "display_data"
0021 }
0022 ],
0023 "source": [
0024 "import ipywidgets as widgets\n",
0025 "from ipywidgets import VBox, HBox, FloatSlider\n",
0026 "from streamSubscriber import StreamSubscriber\n",
0027 "\n",
0028 "portTextBox = widgets.BoundedIntText(value = '5557', min = 5000, max = 6000, step = 1, description = 'Port Number', disabled = False)\n",
0029 "nrowsTextBox = widgets.BoundedIntText(value = '2', min = 1, max = 6, step = 1, description = 'Rows', disabled = False)\n",
0030 "ncolsTextBox = widgets.BoundedIntText(value = '2', min = 1, max = 6, step = 1, description = 'Columns', disabled = False)\n",
0031 "threshTextBox = widgets.BoundedIntText(value = '100', min = 0, max = 1024, step = 1, description = 'Hit Threshold', disabled = False)\n",
0032 "\n",
0033 "plotButton = widgets.RadioButtons(options = ['Occupancy', 'Waveform'], description = 'Plot Type', disabled = False)\n",
0034 "\n",
0035 "portTab = VBox(children = [portTextBox])\n",
0036 "threshTab = VBox(children = [threshTextBox])\n",
0037 "plotTab = VBox(children = [plotButton, nrowsTextBox, ncolsTextBox])\n",
0038 "\n",
0039 "tabs = widgets.Tab(children = [portTab, threshTab, plotTab])\n",
0040 "tabs.set_title(0, 'Port Selection')\n",
0041 "tabs.set_title(1, 'Threshold Selection')\n",
0042 "tabs.set_title(2, 'Plot Selection')\n",
0043 "\n",
0044 "tabs"
0045 ]
0046 },
0047 {
0048 "cell_type": "code",
0049 "execution_count": 6,
0050 "metadata": {
0051 "scrolled": false
0052 },
0053 "outputs": [
0054 {
0055 "data": {
0056 "image/png": "iVBORw0KGgoAAAANSUhEUgAAA1wAAAJ4CAYAAABxr+JQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAgAElEQVR4nOzde9htZV0v/O9PQEMFSVkpcXChUr3mAXVlmm5DzcLDhkrdYXnMYu+2FaaWhwy39lbbXWmZlZGYaOYhNCOig5qgvTvRBaKCh1dUFBBleQK0RNHf/mOOlc9+WutZc8G657OeyedzXfNaY9zjnmP8uF3XxC/3GPeo7g4AAAB73k3WuwAAAIBlJXABAAAMInABAAAMInABAAAMInABAAAMInABAAAMInABAAAMInABsEdU1dlV9cWqutmq9ldW1deq6prpc2FV/VZV3WpVv0Oq6tSqumLq9+Gqen5V3WIn17vZdJ5PVdW/VdVHq+qXq6pG/nMCwO4QuAC4wapqc5L/lKSTHLeDLv+ruw9IsinJk5LcJ8n/tz1MVdWtk/xLkv2T3Hfq+5AkByW5404u+5dJHpzkYUkOSPK4JCcm+f098g8FAHuAwAXAnvD4JO9K8sokT9hZp+7+ane/J7NQdpvMwleSPC3JNUke292XTH0v7e6Tuvv9q89TVQ9O8sNJHtndF3b3dd39riSPTfKUqrrT1O/WVfVnVfXpafbtzSvOcXxVXVBVV1fVx6rq2Kn9kqr6oRX9/kdV/fm0vbmquqpOnM55RVU9Y0Xfe1fVv1TVl6ZjL62qm6443lX136bZuC9V1R+unJGrqp+tqg9NM3wfrKp7TrN2b1z1z/+SqhIsATYAgQuAPeHxSV4zfX6kqm67VufuvibJWzKbFUuSH0rypu7+5pzXe0iSc7v70lXnPTfJZZnNfCXJq5PcPMn3JvmOJC9OZsEoyauS/HJms2gPSHLJnNdOkgcmOSqz0PfMFQHtG0l+KcnBSe471fHfV333EUm+L8ndkvyXJD8y1fToJP8js7E8MLNQ+vkkf57k2Ko6aOq3b5ITpvoB2MsJXADcIFV1/yS3T/KG7j4vyceS/OQcX/10kltP27dJcsVuXPbgNfpfkeTgqjokyUOT/Lfu/mJ3f727z5n6PDnJK7r7Ld39ze6+vLs/vBvXf353f6W7P5Dkz5I8Jkm6+7zuftc043ZJkj9J8oOrvvs/u/tL3f2pJG9PcvTU/jOZ3Xr5np65uLs/2d1XJHlHkkdP/Y5N8rlprAHYywlcANxQT0jyj939uWn/L7LGbYUrHJrkC9P255McshvX/Nwa/Q+Zjh+e5Avd/cUd9Dk8s2B4fa2cWftkku9Mkqr6rqo6s6o+U1VXJ/nNzMLhSp9Zsf2vSW45R02nZXa7ZKY/X30DagdggQQuAK63qto/s9vifnAKGZ/J7Ja6u1fV3df43i0zu43wnVPTW5P8WFXN+++ltyb5/qo6fNV5vz+z4PJPmYWiW2+/FW+VS7PzxTi+ktltiNvdbgd9Vl73iMxm65Lkj5N8OMlR3X1gkuckmXfVxLVqenOSu1XVXTK7JfE1c54TgHUmcAFwQ/xoZs8t3TmzW+OOTvL/ZBakHr+687SU+70yCxBfzOx2vCR5UWbPLZ1WVbef+h5aVS+qqrutPk93vzXJ25K8saq+t6r2qar7ZPa80x9390enW/H+LskfVdW3V9V+VfWA6RSnJnlSVT24qm4yXet7pmMXJDlh6r8lyaN28M/9a1V186r63swW/nj91H5AkquTfHk638/NNYozL0/yjKq6V83caftYdPdXk5ye2ezhu6fbEQHYAAQuAG6IJyT5s+7+VHd/ZvsnyUuT/NS0wEOS/EpVXZPZrYOvSnJekh/o7q8kSXd/IckPJPl6knOnvm9LclWSi3dy7Udm9gzU3yf5cmZh69Qkv7Ciz+Omc344yZVJnjpd792ZBaUXT9c4J7Pn0JLk1zKbafpikudnFnJWO2eq621Jfqe7/3Fqf0Zmz69dk+RP860gtkvd/ZdJfmO63jWZhdJbr+hyWpK7xu2EABtKdfd61wAAG8L0vrFPJNmvu69b8LWPyCw43q67r17ktQG4/sxwAcBebnq27WlJXidsAWws++66CwCwXqrqFkk+m9lqiMeuczkA7Ca3FAIAAAzilkIAAIBBBC4AAIBBNtwzXAcffHBv3rx5vcsAAABIkpx33nmf6+5NOzq24QLX5s2bs3Xr1vUuAwAAIElSVZ/c2TG3FAIAAAwicAEAAAwicAEAAAwicAEAAAwicAEAAAwicAEAAAwicAEAAAwicAEAAAwicAEAAAwicAEAAAwicAEAAAwicAEAAAwicAEAAAwicAEAAAwicAEAAAwicAEAAAwicAEAAAwicAEAAAwicAEAAAwicAEAAAwicAEAAAwyPHBV1T5V9d6qOnMHx25WVa+vqour6tyq2jy6HgAAgEVZxAzXSUk+tJNjT07yxe6+U5IXJ3nhAuoBAABYiKGBq6oOS/LwJC/fSZfjk5w2bZ+e5MFVVSNrAgAAWJTRM1y/l+RXknxzJ8cPTXJpknT3dUmuSnKbwTUBAAAsxL6jTlxVj0hyZXefV1XH3MBznZjkxCQ54ogj9kB1e9bmZ/3tTo9d8j8fvss+2/vN02dPXG9P9dneb2+qe2+s6cZQ995Yk7qXs6YbQ917Y03qXs6abgx17401qXvP/u+7EYyc4bpfkuOq6pIkr0vyoKr681V9Lk9yeJJU1b5JbpXk86tP1N2ndPeW7t6yadOmgSUDAADsOcMCV3c/u7sP6+7NSU5I8k/d/dhV3c5I8oRp+1FTnx5VEwAAwCINu6VwZ6rqBUm2dvcZSU5N8uqqujjJFzILZgAAAEthIYGru89Ocva0ffKK9q8mefQiagAAAFi0RbyHCwAA4EZJ4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhE4AIAABhkWOCqqm+rqndX1fuq6qKqev4O+jyxqrZV1QXT52dG1QMAALBo+w4897VJHtTdX66q/ZL8c1X9XXe/a1W/13f3zw+sAwAAYF0MC1zd3Um+PO3uN3161PUAAAD2NkOf4aqqfarqgiRXJnlLd5+7g26PrKr3V9XpVXX4yHoAAAAWaWjg6u5vdPfRSQ5Lcu+qusuqLn+TZHN33y3JW5KctqPzVNWJVbW1qrZu27ZtZMkAAAB7zEJWKezuLyV5e5JjV7V/vruvnXZfnuReO/n+Kd29pbu3bNq0aWyxAAAAe8jIVQo3VdVB0/b+SR6S5MOr+hyyYve4JB8aVQ8AAMCijVyl8JAkp1XVPpkFuzd095lV9YIkW7v7jCS/WFXHJbkuyReSPHFgPQAAAAs1cpXC9ye5xw7aT16x/ewkzx5VAwAAwHpayDNcAAAAN0YCFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCDDAldVfVtVvbuq3ldVF1XV83fQ52ZV9fqquriqzq2qzaPqAQAAWLSRM1zXJnlQd989ydFJjq2q+6zq8+QkX+zuOyV5cZIXDqwHAABgoYYFrp758rS73/TpVd2OT3LatH16kgdXVY2qCQAAYJGGPsNVVftU1QVJrkzylu4+d1WXQ5NcmiTdfV2Sq5LcZmRNAAAAizI0cHX3N7r76CSHJbl3Vd3l+pynqk6sqq1VtXXbtm17tkgAAIBBFrJKYXd/Kcnbkxy76tDlSQ5PkqraN8mtknx+B98/pbu3dPeWTZs2jS4XAABgjxi5SuGmqjpo2t4/yUOSfHhVtzOSPGHaflSSf+ru1c95AQAAbEj7Djz3IUlOq6p9Mgt2b+juM6vqBUm2dvcZSU5N8uqqujjJF5KcMLAeAACAhRoWuLr7/UnusYP2k1dsfzXJo0fVAAAAsJ4W8gwXAADAjZHABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMIjABQAAMMhuBa6quklVHTiqGAAAgGWyy8BVVX9RVQdW1S2SXJjkg1X1y+NLAwAA2NjmmeG6c3dfneRHk/xdkiOTPG5oVQAAAEtgnsC1X1Xtl1ngOqO7v56kx5YFAACw8c0TuP4kySVJbpHkHVV1+yRXjywKAABgGey7qw7d/ZIkL1nR9MmqeuC4kgAAAJbDTgNXVT1tF9990R6uBQAAYKmsNcN1wMKqAAAAWEI7DVzd/fxFFgIAALBs5nkP13dV1duq6sJp/25V9dzxpQEAAGxs86xS+KdJnp3k60nS3e9PcsLIogAAAJbBPIHr5t397lVt140oBgAAYJnME7g+V1V3zPSy46p6VJIrhlYFAACwBHb5Hq4kT0lySpLvqarLk3wiyWOHVgUAALAE5nnx8ceT/FBV3SLJTbr7mvFlAQAAbHy7DFxVdbMkj0yyOcm+VZUk6e4XDK0MAABgg5vnlsK/TnJVkvOSXDu2HAAAgOUxT+A6rLuPHV4JAADAkplnlcL/XVV3HV4JAADAkplnhuv+SZ5YVZ/I7JbCStLdfbehlQEAAGxw8wSuhw6vAgAAYAnNsyz8J6tqnyS3nac/AAAAM/MsC/8LSZ6X5LNJvjk1dxK3FAIAAKxhnhmrk5J8d3d/fnQxAAAAy2SeVQovzew9XAAAAOyGeWa4Pp7k7Kr626x48XF3v2hYVQAAAEtgnsD1qelz0+kDAADAHOZZpfD5iygEAABg2cyzSuGmJL+S5HuTfNv29u5+0MC6AAAANrx5Fs14TZIPJzkyyfOTXJLkPbv6UlUdXlVvr6oPVtVFVXXSDvocU1VXVdUF0+fk3awfAABgrzXPM1y36e5Tq+qk7j4nyTlVtcvAleS6JE/v7vOr6oAk51XVW7r7g6v6vbO7H7G7hQMAAOzt5glcX5/+vKKqHp7k00luvasvdfcVSa6Ytq+pqg8lOTTJ6sAFAACwlOYJXP9vVd0qydOT/EGSA5P80u5cpKo2J7lHknN3cPi+VfW+zILcM7r7ot05NwAAwN5qnlUKz5w2r0rywN29QFXdMskbkzy1u69edfj8JLfv7i9X1cOSvDnJUTs4x4lJTkySI444YndLAAAAWBfzrlL4s0k2r+zf3T89x3f3yyxsvaa737T6+MoA1t1nVdUfVdXB3f25Vf1OSXJKkmzZsqV3dV0AAIC9wTy3FP51kncmeWuSb8x74qqqJKcm+VB3v2gnfW6X5LPd3VV178xWTfz8vNcAAADYm80TuG7e3c+8Hue+X5LHJflAVV0wtT0nyRFJ0t0vS/KoJD9XVdcl+bckJ3S3GSwAAGApzBO4zqyqh3X3Wbtz4u7+5yS1iz4vTfLS3TkvAADARrHTwFVV1yTpzELTc6rq2syWiK8k3d0HLqZEAACAjWmngau7D1hkIQAAAMvmJjs7UFU/UlWP2kH7I6vqIWPLAgAA2Ph2GriSnJzknB20n5PkBWPKAQAAWB5rBa6bdfe21Y3TO7JuMa4kAACA5bBW4Dqwqv7DM17Ty4z3H1cSAADAclgrcL0pyZ9W1b/PZlXVLZO8bDoGAADAGtYKXM9N8tkkn6yq86rqvCSfSLJtOgYAAMAa1loW/rokz6qq5ye509R8cXf/20IqAwAA2OB2Gri2mwLWBxZQCwAAwFJZ65ZCAAAAbgCBCwAAYJA1bymsqlslOTbJoVPT5Un+obu/NLowAACAjW6nM1xV9fgk5yc5JsnNp88Dk5w3HQMAAGANa81w/WqSe62ezaqqb09ybpJXjSwMAABgo1vrGa5K0jto/+Z0DAAAgDWsNcP1G0nOr6p/THLp1HZEkock+fXRhQEAAGx0O53h6u7TkmxJck6Sa6fP2Um2dPcrF1EcAADARrbmKoXd/cUkr1tQLQAAAEvler2Hq6o+sKcLAQAAWDY7neGqqh/f2aEktxtTDgAAwPJY65bC1yd5TXa8UuG3jSkHAABgeawVuN6f5He6+8LVB6rqh8aVBAAAsBzWeobrqUmu3smxHxtQCwAAwFLZ6QxXd79zjWNbx5QDAACwPK7XKoUAAADsmsAFAAAwiMAFAAAwyNyBq6p+rKpuObIYAACAZTJX4KqqOyZ5Q5LHji0HAABgecw7w/WkJC9M8tMDawEAAFgquwxcVbVPkkdnFriuqqq7D68KAABgCcwzw/WwJO/q7muSvCLJk8eWBAAAsBzmCVxPTnLqtP1XSR5eVTcdVxIAAMByWDNwVdVBSQ7q7nckSXd/NcnpSR60gNoAAAA2tH3XOtjdX0pyzKq2Z44sCAAAYFl48TEAAMAgAhcAAMAgAhcAAMAg87yH645VdbNp+5iq+sVpMQ0AAADWMM8M1xuTfKOq7pTklCSHJ/mLoVUBAAAsgXkC1ze7+7okP5bkD7r7l5McMrYsAACAjW+ewPX1qnpMkickOXNq229cSQAAAMthnsD1pCT3TfIb3f2JqjoyyavHlgUAALDxrfni48lDuvsXt+9MoeurA2sCAABYCvPMcD1hB21P3MN1AAAALJ2dznBNz239ZJIjq+qMFYcOSPKF0YUBAABsdGvdUvi/k1yR5OAkv7ui/Zok7x9ZFAAAwDLYaeDq7k8m+WRmC2YAAACwm9a6pfCfu/v+VXVNkl55KEl394HDqwMAANjA1prhuv/05wGLKwcAAGB5rDXDdeu1vtjdFs4AAABYw1qLZpyX2a2EleSQJJ+etjO132FsaQAAABvbWrcUHrl9u6re2933WExJAAAAy2GeFx8n//eiGQAAAMxh3sAFAADAblpr0Yynrdj9jlX76e4XDasKAABgCay1aMbK5eD/dNU+AAAAu7DWohnPX2QhAAAAy2bYM1xVdXhVvb2qPlhVF1XVSTvoU1X1kqq6uKreX1X3HFUPAADAoq11S+ENdV2Sp3f3+VV1QJLzquot3f3BFX0emuSo6fP9Sf54+hMAAGDDGzbD1d1XdPf50/Y1ST6U5NBV3Y5P8qqeeVeSg6rqkFE1AQAALNJOA1dVPa2qnryD9idX1VN35yJVtTnJPZKcu+rQoUkuXbF/Wf5jKAMAANiQ1prh+qkkr9pB+6uT/PS8F6iqWyZ5Y5KndvfVu1fev5/jxKraWlVbt23bdn1OAQAAsHBrBa59u/vrqxu7+2tJap6TV9V+mYWt13T3m3bQ5fIkh6/YP2xqW33NU7p7S3dv2bRp0zyXBgAAWHdrBa6bVNVtVzfuqG1HqqqSnJrkQ2u8JPmMJI+fViu8T5KruvuKec4PAACwt1trlcLfTvK3VfX0JOdPbfea2n9njnPfL8njknygqi6Y2p6T5Igk6e6XJTkrycOSXJzkX5M8aXf/AQAAAPZWa734+FVVtS3JC5LcZWq+MMnJ3f13uzpxd/9zdnHrYXd3kqfMXy4AAMDGseZ7uKZgtctwBQAAwH+05nu4quqBVfXGqrpo+pxeVccsqDYAAIANba33cD08ySuSnJnkJzNbJv6sJK+oqoctpjwAAICNa61bCn85yY929/tWtF1QVVuT/EFm4QsAAICdWOuWwtutCltJku5+f5K5loYHAAC4MVsrcH3leh4DAAAga99SeMeqOmMH7ZXkDoPqAQAAWBprBa7j1zg2z4uPAQAAbtTWevHxOTtqr6rDk5yQZIfHAQAAmFnzPVzbVdWmqvrvVfXOJGfHohkAAAC7tNMZrqo6IMmPZ/YOru9K8qYkR3b3YQuqDQAAYENb6xmuK5O8O8lzk/xzd3dV/dhiygIAANj41rql8NlJbpbkj5I8u6ruuJiSAAAAlsNOA1d3/1533yffWq3wzUm+s6qeWVXftZDqAAAANrBdLprR3R/v7t/s7rsm2ZLkwCRnDa8MAABgg5trlcLtuvvC7v7V7r7TqIIAAACWxW4FLgAAAOYncAEAAAyy08BVVW+b/nzh4soBAABYHmu9h+uQqvqBJMdV1euS1MqD3X3+0MoAAAA2uLUC18lJfi3JYUletOpYJ3nQqKIAAACWwU4DV3efnuT0qvq17v71BdYEAACwFNaa4UqSdPevV9VxSR4wNZ3d3WeOLQsAAGDj2+UqhVX1W0lOSvLB6XNSVf3m6MIAAAA2ul3OcCV5eJKju/ubSVJVpyV5b5LnjCwMAABgo5v3PVwHrdi+1YhCAAAAls08M1y/leS9VfX2zJaGf0CSZw2tCgAAYAnMs2jGa6vq7CTfNzU9s7s/M7QqAACAJTDPDFe6+4okZwyuBQAAYKnM+wwXAAAAu0ngAgAAGGTNwFVV+1TVhxdVDAAAwDJZM3B19zeSfKSqjlhQPQAAAEtjnkUzvj3JRVX17iRf2d7Y3ccNqwoAAGAJzBO4fm14FQAAAEtonvdwnVNVt09yVHe/tapunmSf8aUBAABsbLtcpbCqfjbJ6Un+ZGo6NMmbRxYFAACwDOZZFv4pSe6X5Ook6e6PJvmOkUUBAAAsg3kC17Xd/bXtO1W1b5IeVxIAAMBymCdwnVNVz0myf1U9JMlfJvmbsWUBAABsfPMErmcl2ZbkA0n+a5Kzkjx3ZFEAAADLYJ5VCr9ZVaclOTezWwk/0t1uKQQAANiFXQauqnp4kpcl+ViSSnJkVf3X7v670cUBAABsZPO8+Ph3kzywuy9Okqq6Y5K/TSJwAQAArGGeZ7iu2R62Jh9Pcs2gegAAAJbGTme4qurHp82tVXVWkjdk9gzXo5O8ZwG1AQAAbGhr3VL4n1dsfzbJD07b25LsP6wiAACAJbHTwNXdT1pkIQAAAMtmnlUKj0zyC0k2r+zf3ceNKwsAAGDjm2eVwjcnOTXJ3yT55thyAAAAlsc8geur3f2S4ZUAAAAsmXkC1+9X1fOS/GOSa7c3dvf5w6oCAABYAvMErrsmeVySB+VbtxT2tA8AAMBOzBO4Hp3kDt39tdHFAAAALJObzNHnwiQHjS4EAABg2cwzw3VQkg9X1Xvyfz/DZVl4AACANcwTuJ43vAoAAIAltMvA1d3nLKIQAACAZbPLwFVV12S2KmGS3DTJfkm+0t0HjiwMAABgo9vlohndfUB3HzgFrP2TPDLJH+3qe1X1iqq6sqou3MnxY6rqqqq6YPqcvNvVAwAA7MXmWaXw3/XMm5P8yBzdX5nk2F30eWd3Hz19XrA7tQAAAOzt5rml8MdX7N4kyZYkX93V97r7HVW1+XpXBgAAsMHNs0rhf16xfV2SS5Icv4euf9+qel+STyd5RndftIfOCwAAsO7mWaXwSYOufX6S23f3l6vqYUnenOSoHXWsqhOTnJgkRxxxxKByAAAA9qydBq5dLGLR3f3rN+TC3X31iu2zquqPqurg7v7cDvqekuSUJNmyZUuvPg4AALA3WmvRjK/s4JMkT07yzBt64aq6XVXVtH3vqZbP39DzAgAA7C12OsPV3b+7fbuqDkhyUpInJXldkt/d2fdWfOe1SY5JcnBVXZbkeZm9wyvd/bIkj0ryc1V1XZJ/S3JCd5u9AgAAlsaaz3BV1a2TPC3JTyU5Lck9u/uL85y4ux+zi+MvTfLSOesEAADYcNZ6huu3k/x4Zs9O3bW7v7ywqgAAAJbAWs9wPT3JdyZ5bpJPV9XV0+eaqrp6je8BAACQtZ/hWiuMAQAAsAtCFQAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCACFwAAwCDDAldVvaKqrqyqC3dyvKrqJVV1cVW9v6ruOaoWAACA9TByhuuVSY5d4/hDkxw1fU5M8scDawEAAFi4YYGru9+R5AtrdJny5QcAAA8bSURBVDk+yat65l1JDqqqQ0bVAwAAsGjr+QzXoUkuXbF/2dQGAACwFDbEohlVdWJVba2qrdu2bVvvcgAAAOaynoHr8iSHr9g/bGr7D7r7lO7e0t1bNm3atJDiAAAAbqj1DFxnJHn8tFrhfZJc1d1XrGM9AAAAe9S+o05cVa9NckySg6vqsiTPS7JfknT3y5KcleRhSS5O8q9JnjSqFgAAgPUwLHB192N2cbyTPGXU9QEAANbbhlg0AwAAYCMSuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYRuAAAAAYZGriq6tiq+khVXVxVz9rB8SdW1baqumD6/MzIegAAABZp31Enrqp9kvxhkockuSzJe6rqjO7+4Kqur+/unx9VBwAAwHoZOcN17yQXd/fHu/trSV6X5PiB1wMAANirjAxchya5dMX+ZVPbao+sqvdX1elVdfjAegAAABZqvRfN+Jskm7v7bknekuS0HXWqqhOramtVbd22bdtCCwQAALi+Rgauy5OsnLE6bGr7d939+e6+dtp9eZJ77ehE3X1Kd2/p7i2bNm0aUiwAAMCeNjJwvSfJUVV1ZFXdNMkJSc5Y2aGqDlmxe1ySDw2sBwAAYKGGrVLY3ddV1c8n+Yck+yR5RXdfVFUvSLK1u89I8otVdVyS65J8IckTR9UDAACwaMMCV5J091lJzlrVdvKK7WcnefbIGgAAANbLei+aAQAAsLQELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEEELgAAgEGGBq6qOraqPlJVF1fVs3Zw/GZV9frp+LlVtXlkPQAAAIs0LHBV1T5J/jDJQ5PcOcljqurOq7o9OckXu/tOSV6c5IWj6gEAAFi0kTNc905ycXd/vLu/luR1SY5f1ef4JKdN26cneXBV1cCaAAAAFmZk4Do0yaUr9i+b2nbYp7uvS3JVktsMrAkAAGBhqrvHnLjqUUmO7e6fmfYfl+T7u/vnV/S5cOpz2bT/sanP51ad68QkJ067353kI0OK3rWDk3xul73Yk4z5YhnvxTLei2W8F8t4L5bxXjxjvlh7+3jfvrs37ejAvgMvenmSw1fsHza17ajPZVW1b5JbJfn86hN19ylJThlU59yqamt3b1nvOm5MjPliGe/FMt6LZbwXy3gvlvFePGO+WBt5vEfeUvieJEdV1ZFVddMkJyQ5Y1WfM5I8Ydp+VJJ/6lFTbgAAAAs2bIaru6+rqp9P8g9J9knyiu6+qKpekGRrd5+R5NQkr66qi5N8IbNQBgAAsBRG3lKY7j4ryVmr2k5esf3VJI8eWcMetu63Nd4IGfPFMt6LZbwXy3gvlvFeLOO9eMZ8sTbseA9bNAMAAODGbuQzXAAAADdqAtecqurYqvpIVV1cVc9a73qWTVW9oqqunF4VsL3t1lX1lqr66PTnt69njcukqg6vqrdX1Qer6qKqOmlqN+YDVNW3VdW7q+p903g/f2o/sqrOnX5XXj8tMMQeUlX7VNV7q+rMad94D1RVl1TVB6rqgqraOrX5TRmkqg6qqtOr6sNV9aGquq/xHqOqvnv6e739c3VVPdV4j1NVvzT9+/LCqnrt9O/RDfsbLnDNoar2SfKHSR6a5M5JHlNVd17fqpbOK5Mcu6rtWUne1t1HJXnbtM+ecV2Sp3f3nZPcJ8lTpr/TxnyMa5M8qLvvnuToJMdW1X2SvDDJi7v7Tkm+mOTJ61jjMjopyYdW7Bvv8R7Y3UevWLrZb8o4v5/k77v7e5LcPbO/68Z7gO7+yPT3+ugk90ryr0n+KsZ7iKo6NMkvJtnS3XfJbPG9E7KBf8MFrvncO8nF3f3x7v5aktclOX6da1oq3f2OzFaqXOn4JKdN26cl+dGFFrXEuvuK7j5/2r4ms39RHxpjPkTPfHna3W/6dJIHJTl9ajfee1BVHZbk4UlePu1XjPd68JsyQFXdKskDMlvtOd39te7+Uoz3Ijw4yce6+5Mx3iPtm2T/6T29N09yRTbwb7jANZ9Dk1y6Yv+yqY2xbtvdV0zbn0ly2/UsZllV1eYk90hyboz5MNPtbRckuTLJW5J8LMmXuvu6qYvflT3r95L8SpJvTvu3ifEerZP8Y1WdV1UnTm1+U8Y4Msm2JH823Tb78qq6RYz3IpyQ5LXTtvEeoLsvT/I7ST6VWdC6Ksl52cC/4QIXG8L0QmxLau5hVXXLJG9M8tTuvnrlMWO+Z3X3N6bbUQ7LbNb8e9a5pKVVVY9IcmV3n7fetdzI3L+775nZ7fdPqaoHrDzoN2WP2jfJPZP8cXffI8lXsup2NuO9503PDB2X5C9XHzPee870LNzxmf2Hhe9Mcov8x8dONhSBaz6XJzl8xf5hUxtjfbaqDkmS6c8r17mepVJV+2UWtl7T3W+amo35YNNtP29Pct8kB023SyR+V/ak+yU5rqouyewW8Adl9ryL8R5o+q/S6e4rM3u+5d7xmzLKZUku6+5zp/3TMwtgxnushyY5v7s/O+0b7zF+KMknuntbd389yZsy+13fsL/hAtd83pPkqGl1lJtmNp18xjrXdGNwRpInTNtPSPLX61jLUpmeZzk1yYe6+0UrDhnzAapqU1UdNG3vn+QhmT039/Ykj5q6Ge89pLuf3d2HdffmzH6v/6m7fyrGe5iqukVVHbB9O8kPJ7kwflOG6O7PJLm0qr57anpwkg/GeI/2mHzrdsLEeI/yqST3qaqbT/9/Zfvf7w37G+7Fx3Oqqodl9kzAPkle0d2/sc4lLZWqem2SY5IcnOSzSZ6X5M1J3pDkiCSfTPJfunv1whpcD1V1/yTvTPKBfOsZl+dk9hyXMd/DqupumT3gu09m/6HrDd39gqq6Q2YzMLdO8t4kj+3ua9ev0uVTVcckeUZ3P8J4jzON7V9Nu/sm+Yvu/o2quk38pgxRVUdntijMTZN8PMmTMv2+xHjvcdN/SPhUkjt091VTm7/fg0yvT/mJzFZVfm+Sn8nsma0N+RsucAEAAAzilkIAAIBBBC4AAIBBBC4AAIBBBC4AAIBBBC4AAIBBBC4Ahqiq21XV66rqY1V1XlWdVVXfVVXHVNWZ61jX2VW1ZSftW1fsb6mqs/fQNZ9YVS/dE+cCYGMRuADY46aXVf5VkrO7+47dfa8kz05y2/WtbJe+o6oeut5FrFZV+6x3DQBcPwIXACM8MMnXu/tl2xu6+33d/c5p95ZVdXpVfbiqXjMFtFTVyVX1nqq6sKpOWdF+dlW9sKreXVX/f1X9p6n9iVX1pqr6+6r6aFX9r+3Xq6ofrqp/qarzq+ovq+qWc9T920l+dXXj6hmqqjpzeqlyqurLVfXbVXVRVb21qu491fvxqjpuxWkOn9o/WlXPW3Gux07/XBdU1Z9sD1fTeX+3qt6X5L5z1A7AXkjgAmCEuyQ5b43j90jy1CR3TnKHJPeb2l/a3d/X3XdJsn+SR6z4zr7dfe/pe89b0X50kp9IctckP1FVh1fVwUmem/yf9u3eRaorDuP49xHxJTayRZokaBEEEVRMCIJpBO2VmELSWNnYSApFsBDZPyCVTSohYKVNQCTBrVx8TQgYDaSJooVoBEMadR1/FnOGzPqWmdWLA34/zdw5c865Tzc83HPZVlWbgCvAtyPkPg88TrJ1hLkDK4CZqloH/AtMA9uBncDRoXlfAF8B64Gv25HFtS37lqraCPSAb4b2vVhVG6rq3Bh5JEkTZPG7DiBJei9dqqrbAEl+A1YD54CtSQ4AHwBTwDXgx7bmVPv8pc0fOFtV/7S9rgOrgJX0y9xse0i2hH6ZGsU0/bJ2cMT5j4Ez7foq8Kiq5pJcfS7nz1V1v+U8BXwJPAE+Ay63nMuBu21+Dzg5YgZJ0oSycEmSunAN2PWa3x8NXfeAxUmWAceAz6vqVpIjwLKXrOkx///rhb2A0C84u8cNXlUzSaaBzUPDT5h/KmQ411xVVbt+OshTVU+TDOcs5quW83hVHXpJlIdV1Rs3vyRpsnikUJLUhRlgaZK9g4Ek6wfvXr3CoMT83d63el1h+z8XgC1JPm33XpFkzRjrp4EDQ99vABuTLEryCf3jgePanmQqyXJgBzALnAV2Jfmw5ZxKsmoBe0uSJpRPuCRJb11VVZKdwHdJDgIP6ZeW/cBHr1jzIMn3wO/AHeDyG9z/XpI9wIkkS9vwYeDPEdefTnJvaGgW+Au4DvwB/LqAWJfoHxH8GPihqq4AJDkM/JRkETAH7ANuLmB/SdIEyn+nICRJkiRJb5NHCiVJkiSpIxYuSZIkSeqIhUuSJEmSOmLhkiRJkqSOWLgkSZIkqSMWLkmSJEnqiIVLkiRJkjpi4ZIkSZKkjjwDuazLBJU0EhUAAAAASUVORK5CYII=\n",
0057 "text/plain": [
0058 "<Figure size 1044x756 with 1 Axes>"
0059 ]
0060 },
0061 "metadata": {
0062 "needs_background": "light"
0063 },
0064 "output_type": "display_data"
0065 },
0066 {
0067 "name": "stdout",
0068 "output_type": "stream",
0069 "text": [
0070 "INDRA Message received -> event = 55, size = 409656 bytes\n"
0071 ]
0072 },
0073 {
0074 "ename": "KeyboardInterrupt",
0075 "evalue": "",
0076 "output_type": "error",
0077 "traceback": [
0078 "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
0079 "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
0080 "\u001b[0;32m<ipython-input-6-e278b70eb590>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mplotButton\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalue\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'Occupancy'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mStreamSubscriber\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mplotButton\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mportTextBox\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mthreshTextBox\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 10\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mplotButton\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalue\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'Waveform'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mStreamSubscriber\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mplotButton\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mportTextBox\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mthreshTextBox\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnrowsTextBox\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mncolsTextBox\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
0081 "\u001b[0;32m~/daq/JANA2/src/plugins/streamDet/jupyter/streamSubscriber.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, plot_type, port, thresh, nrows, ncols)\u001b[0m\n\u001b[1;32m 35\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjana_msg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msubscriber\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrecv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 36\u001b[0m \u001b[0;31m# instantiate the indra message class\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 37\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjevent\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mIndraMessage\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjana_msg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 38\u001b[0m \u001b[0;31m# instantiate the monitoring plot classes\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 39\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot_type\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'Occupancy'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
0082 "\u001b[0;32m~/daq/JANA2/src/plugins/streamDet/jupyter/indraMessage.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, zmq_msg)\u001b[0m\n\u001b[1;32m 46\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msample\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndenumerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madc_smpls\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 47\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata_dict\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'adcSamplesChan_%s'\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m\u001b[0;31m \u001b[0m\u001b[0;31m\\\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 48\u001b[0;31m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata_dict\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'adcSamplesChan_%s'\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msample\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 49\u001b[0m \u001b[0;31m# serialize the data dictionary via pickle and publish it\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 50\u001b[0m \u001b[0;31m# self.event_data_dict = pickle.dumps(self.data_dict)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
0083 "\u001b[0;32m<__array_function__ internals>\u001b[0m in \u001b[0;36mappend\u001b[0;34m(*args, **kwargs)\u001b[0m\n",
0084 "\u001b[0;32m~/.local/lib/python3.6/site-packages/numpy/lib/function_base.py\u001b[0m in \u001b[0;36mappend\u001b[0;34m(arr, values, axis)\u001b[0m\n\u001b[1;32m 4696\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0marr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4697\u001b[0m \u001b[0marr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0marr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mravel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4698\u001b[0;31m \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mravel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4699\u001b[0m \u001b[0maxis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0marr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndim\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4700\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mconcatenate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalues\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
0085 "\u001b[0;32m<__array_function__ internals>\u001b[0m in \u001b[0;36mravel\u001b[0;34m(*args, **kwargs)\u001b[0m\n",
0086 "\u001b[0;32m~/.local/lib/python3.6/site-packages/numpy/core/fromnumeric.py\u001b[0m in \u001b[0;36mravel\u001b[0;34m(a, order)\u001b[0m\n\u001b[1;32m 1750\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0masarray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mravel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0morder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0morder\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1751\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1752\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0masanyarray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mravel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0morder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0morder\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1753\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1754\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
0087 "\u001b[0;32m~/.local/lib/python3.6/site-packages/numpy/core/_asarray.py\u001b[0m in \u001b[0;36masanyarray\u001b[0;34m(a, dtype, order)\u001b[0m\n\u001b[1;32m 136\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 137\u001b[0m \"\"\"\n\u001b[0;32m--> 138\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0morder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0morder\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msubok\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 139\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 140\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
0088 "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
0089 ]
0090 }
0091 ],
0092 "source": [
0093 "import matplotlib.pyplot as plt\n",
0094 "\n",
0095 "print ('Port = %d, ADC Threshold = %d, Plot Type = %s' % (portTextBox.value, threshTextBox.value, plotButton.value))\n",
0096 "\n",
0097 "%matplotlib inline\n",
0098 "plt.rcParams['figure.figsize'] = [14.5, 10.5]\n",
0099 "\n",
0100 "if plotButton.value == 'Occupancy':\n",
0101 " StreamSubscriber(plotButton.value, portTextBox.value, threshTextBox.value)\n",
0102 "if plotButton.value == 'Waveform':\n",
0103 " StreamSubscriber(plotButton.value, portTextBox.value, threshTextBox.value, nrowsTextBox.value, ncolsTextBox.value)"
0104 ]
0105 },
0106 {
0107 "cell_type": "code",
0108 "execution_count": null,
0109 "metadata": {},
0110 "outputs": [],
0111 "source": []
0112 }
0113 ],
0114 "metadata": {
0115 "kernelspec": {
0116 "display_name": "Python 3",
0117 "language": "python",
0118 "name": "python3"
0119 },
0120 "language_info": {
0121 "codemirror_mode": {
0122 "name": "ipython",
0123 "version": 3
0124 },
0125 "file_extension": ".py",
0126 "mimetype": "text/x-python",
0127 "name": "python",
0128 "nbconvert_exporter": "python",
0129 "pygments_lexer": "ipython3",
0130 "version": "3.6.8"
0131 }
0132 },
0133 "nbformat": 4,
0134 "nbformat_minor": 4
0135 }
