llc4320 uplet high ke

uplet_high_ke.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# high ke values in llc uplet parcel simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR 1: PROJ: proj_create_from_database: Open of /home1/datahome/aponte/.miniconda3/envs/equinox/share/proj failed\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "from glob import glob\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import xarray as xr\n",
    "\n",
    "%matplotlib inline\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.feature as cfeature\n",
    "\n",
    "from xhistogram.xarray import histogram\n",
    "\n",
    "import mitequinox.utils as ut\n",
    "import mitequinox.plot as pl\n",
    "import mitequinox.parcels as pa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "        <table style=\"width: 100%; text-align: left;\">\n",
       "\n",
       "        <tr>\n",
       "        \n",
       "            <td style=\"text-align: left;\"><strong>Connection method:</strong> Cluster object</td>\n",
       "            <td style=\"text-align: left;\"><strong>Cluster type:</strong> dask_jobqueue.PBSCluster</td>\n",
       "        \n",
       "        </tr>\n",
       "\n",
       "        \n",
       "            <tr>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Dashboard: </strong> <a href=\"http://10.148.0.68:8787/status\" target=\"_blank\">http://10.148.0.68:8787/status</a>\n",
       "                </td>\n",
       "                <td style=\"text-align: left;\"></td>\n",
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       "        \n",
       "\n",
       "        \n",
       "            <details>\n",
       "            <summary style=\"margin-bottom: 20px;\"><h3 style=\"display: inline;\">Cluster Info</h3></summary>\n",
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       "    <div style=\"margin-left: 48px;\">\n",
       "        <h3 style=\"margin-bottom: 0px; margin-top: 0px;\">PBSCluster</h3>\n",
       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">d208e9e6</p>\n",
       "        <table style=\"width: 100%; text-align: left;\">\n",
       "            <tr>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Dashboard:</strong> <a href=\"http://10.148.0.68:8787/status\" target=\"_blank\">http://10.148.0.68:8787/status</a>\n",
       "                </td>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Workers:</strong> 0\n",
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       "                    <strong>Total threads:</strong> 0\n",
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       "                    <strong>Total memory:</strong> 0 B\n",
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       "\n",
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       "                        <strong>Comm:</strong> tcp://10.148.0.68:41250\n",
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       "                    </td>\n",
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       "                        <strong>Total threads:</strong> 0\n",
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       "                <tr>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Started:</strong> Just now\n",
       "                    </td>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Total memory:</strong> 0 B\n",
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       "        <summary style=\"margin-bottom: 20px;\">\n",
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       "<Client: 'tcp://10.148.0.68:41250' processes=0 threads=0, memory=0 B>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from dask.distributed import Client, LocalCluster\n",
    "if True:\n",
    "    from dask_jobqueue import PBSCluster\n",
    "    cluster = PBSCluster()\n",
    "    w = cluster.scale(jobs=4)\n",
    "else:\n",
    "    cluster = LocalCluster()\n",
    "client = Client(cluster)\n",
    "client"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "## load data\n",
    "\n",
    "Conventions for simulation names are for the example of the `global_dij8_up3_r1s111_15j` simulation:\n",
    "\n",
    "- `global`: simulation over the whole globe\n",
    "- `dij8`: one uplet every 8 model grid points (model grid size between 1 and 2km)\n",
    "- `up3`: 3 drifters per uplet\n",
    "- `r1s111`: all drifters are evenly distributed on a circle of radius 1/111 deg (approx. 1km)\n",
    "- `15j`: 15 day long simulation\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "root_dir = os.path.join(ut.work_data_dir,\"parcels\") \n",
    "\n",
    "# select a numerical simulation\n",
    "run_name = \"global_dij8_up3_r2s111_15j\"\n",
    "\n",
    "# and load\n",
    "ds_info, dirs = pa.load_logs(root_dir, run_name)\n",
    "_zarr = os.path.join(dirs[\"parquets\"], \"uplet.zarr\")\n",
    "ds_up = xr.open_zarr(_zarr).persist()\n",
    "\n",
    "ds_up[\"lon\"] = ds_up.lon%360\n",
    "ds_up[\"lon_init_uplet\"] = ds_up.lon_init_uplet%360\n",
    "ds_up = ds_up.assign_coords(timed=(ds_up.time-ds_up.time[0])/pd.Timedelta(\"1D\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### kinetic energy\n",
    "\n",
    "- Average kinetic energy in 1 deg by 1 deg bins and show the histogram as well as a map\n",
    "- Average kinetic energy in 1 deg by 1 deg bins at each time and show different snapshots of binned energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_up[\"u\"] = ds_up[\"x\"].differentiate(\"time\", datetime_unit=\"s\")\n",
    "ds_up[\"v\"] = ds_up[\"y\"].differentiate(\"time\", datetime_unit=\"s\")\n",
    "ds_up[\"ke\"] = ds_up.u**2 + ds_up.v**2\n",
    "\n",
    "# to filter out directly high values (3 m/s threshold)\n",
    "# 2 m/s threshold filters out values inside western boundary currents\n",
    "#ds_up = ds_up.where(np.sqrt(ds_up[\"ke\"].max(\"item\"))<3, drop=True).persist()\n",
    "\n",
    "ds_up = ds_up.persist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "maximum value of ke = 62.9 m^2/s^2\n"
     ]
    }
   ],
   "source": [
    "ke_max = ds_up[\"ke\"].max().compute()\n",
    "print(f\"maximum value of ke = {float(ke_max):.1f} m^2/s^2\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compute histogram of kinetic energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "ke_hist = histogram(ds_up[\"ke\"], bins=np.arange(0,70,.1)).compute()\n",
    "cdf = (ke_hist.cumsum()/ke_hist.sum()*100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home1/datahome/aponte/.miniconda3/envs/equinox/lib/python3.9/site-packages/xarray/core/computation.py:727: RuntimeWarning: divide by zero encountered in log10\n",
      "  result_data = func(*input_data)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2aab03f15fd0>]"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.log10(ke_hist).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "percentage of data points larger than 2 m/s = 99.8\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1,1)\n",
    "cdf.plot()\n",
    "ax.set_xlim(0,1)\n",
    "ax.grid()\n",
    "\n",
    "_perc = cdf.sel(ke_bin=2, method=\"nearest\")\n",
    "print(f\"percentage of data points larger than 2 m/s = {float(_perc):.1f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home1/datahome/aponte/.miniconda3/envs/equinox/lib/python3.9/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 17\n",
      "  result = blockwise(\n"
     ]
    }
   ],
   "source": [
    "ds_high = ds_up.where(ds_up[\"ke\"].max(\"item\")>9, drop=True).persist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of uplets concerned: 5918 out of 1976343 ( 0.29944194909486865 %)\n"
     ]
    }
   ],
   "source": [
    "print(f\"number of uplets concerned: {ds_high.uplet.size} out of {ds_up.uplet.size} ( {ds_high.uplet.size/ds_up.uplet.size*100} %)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x2aab12d41df0>"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "crs = ccrs.PlateCarree()\n",
    "ax = plt.axes(projection=crs)\n",
    "ax.coastlines()\n",
    "\n",
    "ds_high.plot.scatter(\"lon\", \"lat\", s=2, c=\"r\", marker=\"+\", ax=ax, transform=crs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Close cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "cluster.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "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": "3.9.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}