Tickets/sitcom 2114 #31
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There was a problem hiding this comment. May I ask you to reformat this part of the code? Maybe add spaces between logical blocks of code. For example, instead of: lews_selected = [] hp_max_hist = np.array([]) hp_spread_max_hist = np.array([]) min_ele_range = -1 # minimum elevation change in slew, degrees min_azi_range = -1 # minimum azimuth change in slew, degrees hp_threshold = OPERATIONAL_LIMIT velocity_threshold = 0.5 # deg/s df_state = getEfdData( client, "lsst.sal.MTM1M3.logevent_detailedState", begin=Time(slews[0].begin, format="isot", scale="utc"), end=Time(slews[-1].end, format="isot", scale="utc"), ) Add a space to separate the variable definition from the query that is a multi-line code. Something like this: lews_selected = [] hp_max_hist = np.array([]) hp_spread_max_hist = np.array([]) min_ele_range = -1 # minimum elevation change in slew, degrees min_azi_range = -1 # minimum azimuth change in slew, degrees hp_threshold = OPERATIONAL_LIMIT velocity_threshold = 0.5 # deg/s df_state = getEfdData( client, "lsst.sal.MTM1M3.logevent_detailedState", begin=Time(slews[0].begin, format="isot", scale="utc"), end=Time(slews[-1].end, format="isot", scale="utc"), ) But apply this to the whole cell. Otherwise, it is hard to read. Reply via ReviewNB |
||
| "cells": [ | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "9627519e-ef49-41c5-9085-1a7373e7b3c0", | ||
| "metadata": { | ||
| "tags": [] | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "dayObs = 20250514 # format YYYYMMDD, e.g. \"20250514\"\n", | ||
| "bin_number = 100" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "7c235e45-d932-432a-b473-f72774f97a37", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "# SITCOM-2089 Evaluate M1M3 hard points individual forces (histogram)\n", | ||
| "\n", | ||
| "This notebook makes a histogram of maximum forces and spread of all slews passing certain conditions given a day_obs.\n", | ||
| "\n", | ||
| "### Prepare Notebook" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "c3d229f3-648a-4ee3-ac70-8e22bd90e53e", | ||
| "metadata": { | ||
| "tags": [] | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import pandas as pd\n", | ||
| "import matplotlib.pyplot as plt\n", | ||
| "import numpy as np\n", | ||
| "\n", | ||
| "from astropy.time import Time\n", | ||
| "import matplotlib.dates as mdates\n", | ||
| "\n", | ||
| "from lsst.summit.utils.tmaUtils import TMAEventMaker, TMAState\n", | ||
| "from lsst.summit.utils.efdUtils import getEfdData, makeEfdClient\n", | ||
| "from lsst_efd_client import EfdClient\n", | ||
| "\n", | ||
| "import warnings\n", | ||
| "warnings.filterwarnings(\"ignore\")\n", | ||
| "\n", | ||
| "from lsst.ts.xml.enums.MTM1M3 import DetailedStates" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "6fa49a3c-6c77-4d44-939f-b713b1e5ca76", | ||
| "metadata": { | ||
| "tags": [] | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "# create a client to retrieve datasets in the EFD database\n", | ||
| "client = EfdClient(\"usdf_efd\")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "fd6cf13c-81be-44a0-9177-6f0e1a5faed9", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "OPERATIONAL_LIMIT = 450 # newtons,TBC with Petr\n", | ||
| "SAFE_LIMIT = 900\n", | ||
| "BREAKAWAY_LIMIT = 3200" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "58085fea-42ff-43f0-89be-f3a2a1101b42", | ||
| "metadata": { | ||
| "tags": [] | ||
| }, | ||
| "source": [ | ||
| "### Define functions" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "c741d971-c0c5-48eb-b99d-553650ccc406", | ||
| "metadata": { | ||
| "tags": [] | ||
| }, | ||
| "source": [ | ||
| "#### get previous logged detailedState event from a given time stamp\n", | ||
| "\n", | ||
| "The status of M1M3 is not persistent in the EFD. In order to get at a given time what is the current status, use this function." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "f13c2bfb-3490-4685-a18b-39633d90ee2a", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "def get_previous_logged_detailedState(df_state, timestamp):\n", | ||
| " \"\"\"\n", | ||
| " Get logged detailedState from M1M3 immediately before arbitrary time\n", | ||
| " Args:\n", | ||
| " df_state (pandas dataframe): pandas dataframe obtained from time series of\n", | ||
| " \"lsst.sal.MTM1M3.logevent_detailedState\" covering a wide time frame which includes\n", | ||
| " the time stamp\n", | ||
| " timestamp (pandas timestamp): a timestamp where we want to probe the current status of M1M3\n", | ||
| " Returns:\n", | ||
| " prev_state: human readable status of current M1M3 status\n", | ||
| " \"\"\"\n", | ||
| " df_state_names = df_state[\"detailedState\"].map(lambda x: DetailedStates(x).name)\n", | ||
| " previous_index = df_state.index.asof(timestamp)\n", | ||
| " try:\n", | ||
| " prev = df_state.index.get_loc(previous_index)\n", | ||
| " except KeyError:\n", | ||
| " return \"KeyError\"\n", | ||
| " return df_state_names[prev]" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "72fdf187-0dbb-477c-a8dc-6749a9f8c9f8", | ||
| "metadata": { | ||
| "tags": [] | ||
| }, | ||
| "source": [ | ||
| "### Define relevant settings" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "5a56db2c-4172-46db-9155-3ff63fcbc5b9", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "#### Observation day" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "beda404b-dea9-49ba-9544-be6cbf635a63", | ||
| "metadata": { | ||
| "tags": [] | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "## Insert here the day_obs of interest\n", | ||
| "day_obs = dayObs" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "decee784-6779-4188-84d7-86727cb7cdb8", | ||
| "metadata": { | ||
| "tags": [] | ||
| }, | ||
| "source": [ | ||
| "### Load data" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "b66bab89-b2ef-42ae-a73e-ab34e72ea514", | ||
| "metadata": { | ||
| "tags": [] | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "# Select data from a given date\n", | ||
| "eventMaker = TMAEventMaker()\n", | ||
| "events = eventMaker.getEvents(day_obs)\n", | ||
| "\n", | ||
| "# Get lists of slew and track events\n", | ||
| "slews = [e for e in events if e.type == TMAState.SLEWING]\n", | ||
| "tracks = [e for e in events if e.type == TMAState.TRACKING]\n", | ||
| "print(f\"There are {len(events)} events\")\n", | ||
| "print(f\"Found {len(slews)} slews and {len(tracks)} tracks\")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "d3a7738e-6b42-4a06-8fc9-e8f5db9951c0", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "### Select slews passing certain criteria" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "05266ebb-b00b-44a5-a26f-d246ebc11843", | ||
| "metadata": { | ||
| "tags": [] | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "slews_selected = []\n", | ||
| "hp_max_hist = np.array([])\n", | ||
| "hp_spread_max_hist = np.array([])\n", | ||
| "min_ele_range = -1 # minimum elevation change in slew, degrees\n", | ||
| "min_azi_range = -1 # minimum azimuth change in slew, degrees\n", | ||
| "hp_threshold = OPERATIONAL_LIMIT\n", | ||
| "velocity_threshold = 0.5 # deg/s\n", | ||
| "\n", | ||
| "df_state = getEfdData(\n", | ||
| " client,\n", | ||
| " \"lsst.sal.MTM1M3.logevent_detailedState\",\n", | ||
| " begin=Time(slews[0].begin, format=\"isot\", scale=\"utc\"),\n", | ||
| " end=Time(slews[-1].end, format=\"isot\", scale=\"utc\"),\n", | ||
| ") # get an array for all state changes from first slew of day_obs to final one\n", | ||
| "\n", | ||
| "for i, slew in enumerate(slews):\n", | ||
| " if (\n", | ||
| " slew.seqNum == 0\n", | ||
| " ): # skip first one to avoid problems looking for a previous detailedState outside the df_state range\n", | ||
| " continue\n", | ||
| " \n", | ||
| " df_azi = getEfdData(client, \"lsst.sal.MTMount.azimuth\", event=slew)\n", | ||
| " df_ele = getEfdData(client, \"lsst.sal.MTMount.elevation\", event=slew)\n", | ||
| " df_hp = getEfdData(client, \"lsst.sal.MTM1M3.hardpointActuatorData\", event=slew)\n", | ||
| " timestamp = pd.Timestamp(\n", | ||
| " Time(slew.begin, format=\"iso\", scale=\"utc\").value, tz=\"utc\"\n", | ||
| " )\n", | ||
| " begin_state = get_previous_logged_detailedState(df_state, timestamp)\n", | ||
| " \n", | ||
| " if begin_state == \"KeyError\":\n", | ||
| " continue\n", | ||
| " \n", | ||
| " timestamp = pd.Timestamp(Time(slew.end, format=\"iso\", scale=\"utc\").value, tz=\"utc\")\n", | ||
| " end_state = get_previous_logged_detailedState(df_state, timestamp)\n", | ||
| " \n", | ||
| " if len(df_hp) > 0: \n", | ||
| " hp_max_individual = np.array(\n", | ||
| " [\n", | ||
| " np.max(abs(df_hp[\"measuredForce0\"].values)),\n", | ||
| " np.max(abs(df_hp[\"measuredForce1\"].values)),\n", | ||
| " np.max(abs(df_hp[\"measuredForce2\"].values)),\n", | ||
| " np.max(abs(df_hp[\"measuredForce3\"].values)),\n", | ||
| " np.max(abs(df_hp[\"measuredForce4\"].values)),\n", | ||
| " np.max(abs(df_hp[\"measuredForce5\"].values)),\n", | ||
| " ]\n", | ||
| " )\n", | ||
| " hp_max = np.max(hp_max_individual)\n", | ||
| " hp_spread_individual = np.array(\n", | ||
| " [\n", | ||
| " np.max(df_hp[\"measuredForce0\"].values)-np.min(df_hp[\"measuredForce0\"].values),\n", | ||
| " np.max(df_hp[\"measuredForce1\"].values)-np.min(df_hp[\"measuredForce1\"].values),\n", | ||
| " np.max(df_hp[\"measuredForce2\"].values)-np.min(df_hp[\"measuredForce2\"].values),\n", | ||
| " np.max(df_hp[\"measuredForce3\"].values)-np.min(df_hp[\"measuredForce3\"].values),\n", | ||
| " np.max(df_hp[\"measuredForce4\"].values)-np.min(df_hp[\"measuredForce4\"].values),\n", | ||
| " np.max(df_hp[\"measuredForce5\"].values)-np.min(df_hp[\"measuredForce5\"].values),\n", | ||
| " ]\n", | ||
| " )\n", | ||
| " hp_spread_max = np.max(hp_spread_individual)\n", | ||
| " \n", | ||
| " # introduce conditions to select specific slews\n", | ||
| "\n", | ||
| " # condition on minimum azimuth and minimum elevation\n", | ||
| " slew_delta_azi = df_azi[\"demandPosition\"].max() - df_azi[\"demandPosition\"].min()\n", | ||
| " slew_delta_ele = df_ele[\"demandPosition\"].max() - df_ele[\"demandPosition\"].min()\n", | ||
| " slew_ele_condition = slew_delta_ele > min_ele_range\n", | ||
| " slew_azi_condition = slew_delta_azi > min_azi_range\n", | ||
| "\n", | ||
| " # ensure that the HPs are active (mirror is 'raised')\n", | ||
| " state_condition = ( \n", | ||
| " (begin_state == \"ACTIVE\") or (begin_state == \"ACTIVEENGINEERING\")\n", | ||
| " ) and ((end_state == \"ACTIVE\") or (end_state == \"ACTIVEENGINEERING\"))\n", | ||
| "\n", | ||
| " # condition on maximum azimuth velocity\n", | ||
| " velocity_condition = (df_azi[\"actualVelocity\"] < velocity_threshold).all()\n", | ||
| "\n", | ||
| " # check all conditions to select slews and fill histogram\n", | ||
| " if (\n", | ||
| " slew_ele_condition\n", | ||
| " and slew_azi_condition\n", | ||
| " and state_condition\n", | ||
| " and velocity_condition\n", | ||
| " ):\n", | ||
| " hp_max_hist = np.append(hp_max_hist,hp_max) \n", | ||
| " hp_spread_max_hist = np.append(hp_spread_max_hist,hp_spread_max)\n" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "1fe2c77d-8883-4ee1-af48-f62b6b3a9f9d", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "### Plot histograms" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "194e2712-3e93-49c8-8f0f-136b4d4ff5ab", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "#### Plot distribution of maximum forces" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "53704b04-cd37-42eb-aa03-970f4e3510a5", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "# Plot a distribution of maximum forces\n", | ||
| "plt.ylabel(\"Number of slews\")\n", | ||
| "plt.xlabel(\"Maximum recorded force in any hardpoint per slew (N)\")\n", | ||
| "plt.title(f\"Maximum force on hardpoints for {day_obs}\")\n", | ||
| "plt.axvline(x=OPERATIONAL_LIMIT, color='orange', linestyle='--', linewidth=2, label='Operational limit')\n", | ||
| "plt.axvline(x=SAFE_LIMIT, color='red', linestyle='--', linewidth=2, label='Safe limit')\n", | ||
| "plt.axvline(x=BREAKAWAY_LIMIT, color='black', linestyle='--', linewidth=2, label='Breakaway limit')\n", | ||
| "plt.legend()\n", | ||
| "h = plt.hist(hp_max_hist, bins=bin_number)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "15170c22-f455-4873-a6f1-fdeaa06a37ab", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "#### Plot distribution of difference of maximum and minimum" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "80e39543-a4ba-436f-b638-68047fb62de0", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "plt.ylabel(\"Number of slews\")\n", | ||
| "plt.xlabel(\"Maximum spread of forces in any hardpoint per slew (N)\")\n", | ||
| "plt.title(f\"Maximum spread of forces on hardpoints for {day_obs}\")\n", | ||
| "plt.legend()\n", | ||
| "h = plt.hist(hp_spread_max_hist, bins=bin_number)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "a8db084a-b066-47c9-a834-097f8bd881b7", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "LSST", | ||
| "language": "python", | ||
| "name": "lsst" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.12.10" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 5 | ||
| } | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,18 @@ | ||
| title: MTM1M3 Max Forces Histogram | ||
| description: A notebook to make max forces histogram to check M1M3 status every morning | ||
| authors: | ||
| - name: HyeYun Park | ||
| slack: hyeyun | ||
| tags: | ||
| - mtm1m3 | ||
| - force actuators | ||
| - following error | ||
| parameters: | ||
| dayObs: | ||
| type: integer | ||
| description: Observation day in format YYYYMMDD | ||
| default: 20250514 | ||
| bin_number: | ||
| type: integer | ||
| description: Bin number for the histogram,, e.g. 100 | ||
| default: 100 |
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Can you remove this cell? It does not add anything to the execution.
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