From e629575dc999c33ae620f5842ea7a03a3d1745b2 Mon Sep 17 00:00:00 2001 From: stedif <stefano.difrischia@inaf.it> Date: Wed, 1 Sep 2021 09:04:53 +0200 Subject: [PATCH] L2SS-235: add jupyter notebook for testing --- jupyter-notebooks/PCC_archive_attribute.ipynb | 283 ++++++++++++++++++ 1 file changed, 283 insertions(+) create mode 100644 jupyter-notebooks/PCC_archive_attribute.ipynb diff --git a/jupyter-notebooks/PCC_archive_attribute.ipynb b/jupyter-notebooks/PCC_archive_attribute.ipynb new file mode 100644 index 000000000..cd4197ee9 --- /dev/null +++ b/jupyter-notebooks/PCC_archive_attribute.ipynb @@ -0,0 +1,283 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "b2af67ec", + "metadata": {}, + "outputs": [], + "source": [ + "import sys, time\n", + "import numpy as np\n", + "sys.path.append('/hosthome/tango/devices')\n", + "from toolkit.archiver import Archiver,Retriever\n", + "from toolkit.archiver_base import *\n", + "from matplotlib import pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "c873d747", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "timeout 3000\n", + "new_timeout 10000\n", + "OFF\n" + ] + } + ], + "source": [ + "device_name = 'LTS/PCC/1'\n", + "attr_name = 'rcu_temperature_r'\n", + "attr_fq_name = str(device_name+'/'+attr_name).lower()\n", + "archiver = Archiver()\n", + "\n", + "d=DeviceProxy(device_name)\n", + "\n", + "# Need to increase the default timeout (3s) or device could raise error on initialising, \n", + "# when checking the list of archived attributes\n", + "print(\"timeout %s\" % str(d.get_timeout_millis()))\n", + "timeout = 10000\n", + "print(\"new_timeout %s\" % timeout)\n", + "d.set_timeout_millis(timeout)\n", + "\n", + "state = str(d.state())\n", + "print(state)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "684cf0a7", + "metadata": {}, + "outputs": [], + "source": [ + "# OPTIONAL\n", + "# Archiving starts at device initializations with polling-period = 1s, but period can be explicitly set\n", + "# Archiving strategies are ['ALWAYS','RUN','SHUTDOWN','SERVICE']\n", + "\n", + "archiver.remove_attribute_from_archiver(device_name,attr_name)\n", + "time.sleep(3)\n", + "archiver.add_attribute_to_archiver(attribute=attr_fq_name,polling_period=1000,event_period=10000,strategy='RUN')" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "249271c1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Device is now in ON state\n" + ] + } + ], + "source": [ + "if state == \"OFF\":\n", + " d.initialise()\n", + " time.sleep(1)\n", + "state = str(d.state())\n", + "if state == \"STANDBY\":\n", + " d.on()\n", + "state = str(d.state())\n", + "if state == \"ON\":\n", + " print(\"Device is now in ON state\")" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "81acaa95", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "35\n", + "1\n", + "('tango://databaseds:10000/lts/pcc/1/rcu_temperature_r',)\n" + ] + } + ], + "source": [ + "attr_list = d.get_attribute_list()\n", + "#for a in attr_list:\n", + " #print(a)\n", + "print(len(attr_list))\n", + "\n", + "#List of archived attributes - it should be 1 for now -\n", + "arch_attr_list = archiver.es.AttributeList\n", + "print(len(arch_attr_list))\n", + "print(arch_attr_list)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "9fd8415d", + "metadata": {}, + "outputs": [], + "source": [ + "# OPTIONAL: stop archiving switching off device or explicitly stopping\n", + "\n", + "d.off()\n", + "#archiver.stop_archiving_attribute(device_name,attr_name)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "88307600", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[<Attribute(fullname='tango://databaseds:10000/lts/pcc/1/rcu_temperature_r',data_type ='39',ttl='0',facility ='tango://databaseds:10000',domain ='lts',family ='pcc',member ='1',name ='rcu_temperature_r')>]" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "retriever = Retriever()\n", + "retriever.get_all_archived_attributes()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "c5a7e5e2", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "array_devdouble_ro\n" + ] + } + ], + "source": [ + "# Print database type of the attribute\n", + "print(retriever.get_attribute_datatype(attr_fq_name))" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "07fcc423", + "metadata": {}, + "outputs": [], + "source": [ + "# Retrieve records in the last n hours (works even with decimals)\n", + "records= retriever.get_attribute_value_by_hours(attr_fq_name,hours=0.1)\n", + "# Convert DB Array records into Python lists\n", + "data = build_array_from_record(records,records[0].dim_x_r)\n", + "# Extract only the value from the array \n", + "array_values = get_values_from_record(data)\n", + "\n", + "#records\n", + "#data\n", + "#array_values" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "3aad4160", + "metadata": {}, + "outputs": [], + "source": [ + "# Extract and process timestamps for plotting purposes\n", + "def get_timestamps(data,strformat):\n", + " timestamps = []\n", + " for i in range(len(data)):\n", + " timestamps.append(data[i][0].recv_time.strftime(strformat))\n", + " return timestamps\n", + "timestamps = get_timestamps(data,\"%Y-%m-%d %X\")" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "929132fd", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "<Figure size 4096x4096 with 2 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Plot of array values\n", + "\n", + "heatmap = np.array(array_values,dtype=np.float)\n", + "fig = plt.figure()\n", + "plt.rcParams['figure.figsize'] = [32, 32]\n", + "#plt.rcParams['figure.dpi'] = 128\n", + "ax = fig.add_subplot(111)\n", + "im = ax.imshow(heatmap, interpolation='nearest',cmap='coolwarm')\n", + "ax.set_xlabel('Array index')\n", + "ax.set_ylabel('Timestamp')\n", + "\n", + "ax.set_yticks(range(0,len(timestamps)))\n", + "ax.set_yticklabels(timestamps,fontsize=4)\n", + "\n", + "#ax.set_yticks(range(0,len(timestamps),10))\n", + "\n", + "ax.set_title('Archived data for '+ attr_fq_name)\n", + "cbar = fig.colorbar(ax=ax, mappable=im, orientation='horizontal')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8e0ef798", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "StationControl", + "language": "python", + "name": "stationcontrol" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} -- GitLab