{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "meaning-piano",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "# Temporal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "unusual-garbage",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-15T05:11:33.452638Z",
     "iopub.status.busy": "2022-09-15T05:11:33.452376Z",
     "iopub.status.idle": "2022-09-15T05:11:34.763232Z",
     "shell.execute_reply": "2022-09-15T05:11:34.762626Z"
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "ExecuteTime": {
     "end_time": "2023-05-10T23:25:34.814906483Z",
     "start_time": "2023-05-10T23:25:34.389514725Z"
    }
   },
   "outputs": [],
   "source": [
    "import starepandas\n",
    "import pystare\n",
    "import pandas\n",
    "import astropy.time\n",
    "import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "eleven-colon",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-15T05:11:34.766060Z",
     "iopub.status.busy": "2022-09-15T05:11:34.765794Z",
     "iopub.status.idle": "2022-09-15T05:11:34.780649Z",
     "shell.execute_reply": "2022-09-15T05:11:34.780129Z"
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "                dates\n0 2021-09-03 00:00:00\n1 2021-07-17 11:16:00",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>dates</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2021-09-03 00:00:00</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2021-07-17 11:16:00</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dates = ['2021-09-03', '2021-07-17 11:16']\n",
    "dates = pandas.to_datetime(dates, format='ISO8601')\n",
    "df = starepandas.STAREDataFrame({'dates': dates})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "separated-setting",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-15T05:11:34.783289Z",
     "iopub.status.busy": "2022-09-15T05:11:34.783049Z",
     "iopub.status.idle": "2022-09-15T05:11:34.786641Z",
     "shell.execute_reply": "2022-09-15T05:11:34.786016Z"
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "ExecuteTime": {
     "end_time": "2023-05-10T23:33:31.268876405Z",
     "start_time": "2023-05-10T23:33:30.864255485Z"
    }
   },
   "outputs": [],
   "source": [
    "series = df['dates']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "light-placement",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-15T05:11:34.788773Z",
     "iopub.status.busy": "2022-09-15T05:11:34.788512Z",
     "iopub.status.idle": "2022-09-15T05:11:34.793567Z",
     "shell.execute_reply": "2022-09-15T05:11:34.792950Z"
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "ExecuteTime": {
     "end_time": "2023-05-10T23:33:32.349696111Z",
     "start_time": "2023-05-10T23:33:32.046601552Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "array([2459460., 2459413.])"
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "times = astropy.time.Time(series, \n",
    "                          scale='utc', \n",
    "                          format='datetime64')\n",
    "times.jd1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "secure-newfoundland",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-15T05:11:34.795724Z",
     "iopub.status.busy": "2022-09-15T05:11:34.795422Z",
     "iopub.status.idle": "2022-09-15T05:11:34.799115Z",
     "shell.execute_reply": "2022-09-15T05:11:34.798666Z"
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "ExecuteTime": {
     "end_time": "2023-05-10T23:33:35.325728073Z",
     "start_time": "2023-05-10T23:33:34.331244243Z"
    }
   },
   "outputs": [],
   "source": [
    "tivs = starepandas.tivs_from_timeseries(df['dates'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "talented-container",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-15T05:11:34.801396Z",
     "iopub.status.busy": "2022-09-15T05:11:34.801184Z",
     "iopub.status.idle": "2022-09-15T05:11:34.803557Z",
     "shell.execute_reply": "2022-09-15T05:11:34.803156Z"
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "ExecuteTime": {
     "end_time": "2023-05-10T23:33:37.656814090Z",
     "start_time": "2023-05-10T23:33:37.435874192Z"
    }
   },
   "outputs": [],
   "source": [
    "# Pystare"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "dental-belly",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-15T05:11:34.805379Z",
     "iopub.status.busy": "2022-09-15T05:11:34.805191Z",
     "iopub.status.idle": "2022-09-15T05:11:34.809922Z",
     "shell.execute_reply": "2022-09-15T05:11:34.809501Z"
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "ExecuteTime": {
     "end_time": "2023-05-10T23:33:38.318607613Z",
     "start_time": "2023-05-10T23:33:38.161735880Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "array([2276059438861267137, 2275939265676325057])"
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "times = ['2021-09-03', '2021-07-17 11:16']\n",
    "times = astropy.time.Time(series, scale='utc', format='datetime64')\n",
    "tivs = pystare.from_julian_date(times.jd1, times.jd2, scale='utc', forward_res=48, reverse_res=48)\n",
    "tivs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "fixed-import",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-15T05:11:34.811931Z",
     "iopub.status.busy": "2022-09-15T05:11:34.811632Z",
     "iopub.status.idle": "2022-09-15T05:11:34.816935Z",
     "shell.execute_reply": "2022-09-15T05:11:34.816450Z"
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "ExecuteTime": {
     "end_time": "2023-05-10T23:33:40.213085970Z",
     "start_time": "2023-05-10T23:33:39.826670851Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "['2021-09-03T00:00:00', '2021-07-17T11:16:00']"
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mss = pystare.to_ms_since_epoch_utc(tivs)\n",
    "dts = [datetime.datetime.utcfromtimestamp(ms/1000) for ms in mss]\n",
    "[dt.isoformat() for dt in dts]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "disabled-theta",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-15T05:11:34.818899Z",
     "iopub.status.busy": "2022-09-15T05:11:34.818683Z",
     "iopub.status.idle": "2022-09-15T05:11:34.822820Z",
     "shell.execute_reply": "2022-09-15T05:11:34.822459Z"
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "ExecuteTime": {
     "end_time": "2023-05-10T23:33:42.140254214Z",
     "start_time": "2023-05-10T23:33:41.491963920Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "array([datetime.datetime(2021, 9, 3, 0, 0),\n       datetime.datetime(2021, 7, 17, 11, 16)], dtype=object)"
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jd = pystare.to_julian_date(tivs, scale='utc')\n",
    "times = astropy.time.Time(val=jd[0], val2=jd[1], format='jd')\n",
    "times.to_datetime()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "diagnostic-hazard",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}