{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "37e600ef",
   "metadata": {},
   "outputs": [],
   "source": [
    "from netCDF4 import Dataset\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.colors as mcolors\n",
    "import matplotlib.colors as Normalize\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.feature as cfeature\n",
    "from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter\n",
    "import matplotlib.ticker as mticker\n",
    "import matplotlib\n",
    "import xarray as xr\n",
    "import netCDF4\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import glob\n",
    "import dask\n",
    "import os\n",
    "from datetime import datetime\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f8464ead",
   "metadata": {},
   "outputs": [],
   "source": [
    "monlist = ['04'] # months in the simulation\n",
    "sim_list = ['current','future','future_urban']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1dd8c71a",
   "metadata": {},
   "outputs": [],
   "source": [
    "c_precip = xr.open_dataset(f'/pscratch/sd/d/dbrooks/acc2017_analysis/precip_data/current/hourly_precip_data_month{monlist[0]}.nc')\n",
    "f_precip = xr.open_dataset(f'/pscratch/sd/d/dbrooks/acc2017_analysis/precip_data/future/hourly_precip_data_month{monlist[0]}.nc')\n",
    "fu_precip = xr.open_dataset(f'/pscratch/sd/d/dbrooks/acc2017_analysis/precip_data/future_urban/hourly_precip_data_month{monlist[0]}.nc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "144b8a2e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<xarray.Dataset> Size: 4GB\n",
      "Dimensions:  (south_north: 1080, west_east: 1210, Time: 720)\n",
      "Coordinates:\n",
      "    XLAT     (south_north, west_east) float32 5MB ...\n",
      "    XLONG    (south_north, west_east) float32 5MB ...\n",
      "  * Time     (Time) datetime64[ns] 6kB 2017-04-01T01:00:00 ... 2017-04-30T23:...\n",
      "Dimensions without coordinates: south_north, west_east\n",
      "Data variables:\n",
      "    RAINNC   (south_north, west_east, Time) float32 4GB ...\n"
     ]
    }
   ],
   "source": [
    "print(c_precip)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "59dbc285",
   "metadata": {},
   "outputs": [],
   "source": [
    "select_time_window = False\n",
    "select_subregion = False\n",
    "\n",
    "if select_time_window == True:\n",
    "    #start_time = '2017-06-19T06:00:00'\n",
    "    end_time = '2017-06-19T06:00:00'\n",
    "    start_time = '2017-06-01T00:00:00'\n",
    "    #end_time = '2017-06-24T06:00:00'\n",
    "else:\n",
    "    start_time = 0\n",
    "    end_time = 0\n",
    "\n",
    "# Land mask\n",
    "land_mask = xr.open_dataset('/pscratch/sd/d/dbrooks/acc2017_analysis/masks/landmask.nc')\n",
    "\n",
    "if select_time_window == True:\n",
    "    def subset_time_window(ds, start_time, end_time):\n",
    "        \"\"\"\n",
    "        Subset the dataset based on a specified time window.\n",
    "\n",
    "        Parameters:\n",
    "        ds (xarray.Dataset): The dataset to subset.\n",
    "        start_time (str or datetime): The start time of the window (inclusive).\n",
    "        end_time (str or datetime): The end time of the window (inclusive).\n",
    "\n",
    "        Returns:\n",
    "        xarray.Dataset: The subset of the dataset within the specified time window.\n",
    "        \"\"\"\n",
    "        # Subset the dataset by time\n",
    "        subset_ds = ds.sel(Time=slice(start_time, end_time))\n",
    "        \n",
    "        return subset_ds\n",
    "\n",
    "    c_precip = subset_time_window(c_precip, start_time, end_time)\n",
    "    f_precip = subset_time_window(f_precip, start_time, end_time)\n",
    "    fu_precip = subset_time_window(fu_precip, start_time, end_time) \n",
    "\n",
    "# Select subregion if desired\n",
    "if select_subregion == True:\n",
    "    def select_region(bounding_box, ds):\n",
    "        min_lon,min_lat,max_lon,max_lat = bounding_box[0], bounding_box[1], bounding_box[2], bounding_box[3]\n",
    "\n",
    "        # Access the latitude and longitude arrays (XLAT, XLONG)\n",
    "        lats = ds['XLAT']\n",
    "        lons = ds['XLONG']\n",
    "\n",
    "        # Create a boolean mask for the region of interest\n",
    "        region_mask = (lats >= min_lat) & (lats <= max_lat) & (lons >= min_lon) & (lons <= max_lon)\n",
    "\n",
    "        # Subset the data using the bounding box\n",
    "        ds = ds.where(region_mask, drop=True)\n",
    "\n",
    "        return ds\n",
    "    \n",
    "    bbox = [-97,26,-84,38]\n",
    "    \n",
    "    c_precip = select_region(bbox, c_precip)\n",
    "    f_precip = select_region(bbox, f_precip)\n",
    "    fu_precip = select_region(bbox, fu_precip) \n",
    "\n",
    "    land_mask = select_region(bbox, land_mask)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "1911e4b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib.ticker import FuncFormatter\n",
    "from joblib import Parallel, delayed\n",
    "from tqdm import tqdm\n",
    "\n",
    "# Define precipitation intensity bins and labels\n",
    "PRECIP_BINS = [(0.25, 2.5), (2.5, 10), (10, 50), (50, np.inf)]\n",
    "BIN_LABELS = ['0.25-2.5', '2.5-10', '10-50', '≥50']\n",
    "\n",
    "# Functions to calculate relative changes\n",
    "def calculate_relative_change(future, current):\n",
    "    return ((future / current) - 1) * 100\n",
    "\n",
    "def calculate_relative_change_urbanization(future, current, future_urban):\n",
    "    return ((future_urban - future) / future) * 100\n",
    "\n",
    "\n",
    "def calculate_frequency_per_bin(precip_data, bins):\n",
    "    bin_frequencies = []\n",
    "    for lower, upper in bins:\n",
    "        bin_mask = (precip_data >= lower) & (precip_data < upper)\n",
    "        bin_frequency = bin_mask.sum().item()\n",
    "        bin_frequencies.append(bin_frequency)\n",
    "    return bin_frequencies\n",
    "\n",
    "\n",
    "def calculate_percentage_per_bin(precip_data, bins):\n",
    "    if isinstance(precip_data, np.ndarray):\n",
    "        total_occurrences = len(precip_data)\n",
    "    else:\n",
    "        total_occurrences = precip_data.count().item()\n",
    "\n",
    "    bin_percentages = []\n",
    "    for lower, upper in bins:\n",
    "        bin_mask = (precip_data >= lower) & (precip_data < upper)\n",
    "        bin_frequency = bin_mask.sum().item()\n",
    "        bin_percentage = (bin_frequency / total_occurrences) * 100\n",
    "        bin_percentages.append(bin_percentage)\n",
    "\n",
    "    return bin_percentages\n",
    "\n",
    "\n",
    "def _to_scalar(value):\n",
    "    if hasattr(value, \"compute\"):\n",
    "        value = value.compute()\n",
    "    if hasattr(value, \"item\"):\n",
    "        return value.item()\n",
    "    return float(value)\n",
    "\n",
    "\n",
    "def compute_bin_counts_from_dataarray(precip_da, bins):\n",
    "    \"\"\"Compute bin counts without materializing the full field in memory.\"\"\"\n",
    "    total_valid = int(_to_scalar(precip_da.count()))\n",
    "    counts = []\n",
    "\n",
    "    for lower, upper in bins:\n",
    "        mask = (precip_da >= lower) & (precip_da < upper)\n",
    "        counts.append(int(_to_scalar(mask.sum())))\n",
    "\n",
    "    return np.array(counts, dtype=np.int64), total_valid\n",
    "\n",
    "\n",
    "def _multinomial_probs_with_residual(bin_counts, total_count):\n",
    "    \"\"\"Return probabilities for plotted bins plus one residual outside-bin category.\"\"\"\n",
    "    total_count = max(int(total_count), 1)\n",
    "    bin_counts = np.array(bin_counts, dtype=np.float64)\n",
    "    in_bin = float(np.sum(bin_counts))\n",
    "    residual = max(total_count - in_bin, 0.0)\n",
    "\n",
    "    probs = np.concatenate([bin_counts, np.array([residual])]) / total_count\n",
    "    probs = probs / probs.sum()\n",
    "    return probs\n",
    "\n",
    "\n",
    "def bootstrap_relative_change_from_counts(\n",
    "    current_counts,\n",
    "    future_counts,\n",
    "    future_urban_counts,\n",
    "    n_current,\n",
    "    n_future,\n",
    "    n_future_urban,\n",
    "    n_iterations=1000,\n",
    "    urban=False,\n",
    "    c_fu=False,\n",
    "    normalize=False,\n",
    "    bootstrap_sample_size=2000000,\n",
    "    random_seed=42,\n",
    "):\n",
    "    \"\"\"\n",
    "    Bootstrap relative changes using multinomial draws from bin counts.\n",
    "    Includes an implicit outside-bin category to preserve full-population proportions.\n",
    "    \"\"\"\n",
    "    rng = np.random.default_rng(random_seed)\n",
    "\n",
    "    p_cur = _multinomial_probs_with_residual(current_counts, n_current)\n",
    "    p_fut = _multinomial_probs_with_residual(future_counts, n_future)\n",
    "    p_fut_urb = _multinomial_probs_with_residual(future_urban_counts, n_future_urban)\n",
    "\n",
    "    n_cur_eff = min(int(n_current), int(bootstrap_sample_size))\n",
    "    n_fut_eff = min(int(n_future), int(bootstrap_sample_size))\n",
    "    n_fut_urb_eff = min(int(n_future_urban), int(bootstrap_sample_size))\n",
    "\n",
    "    # Draw K+1 categories (K plotted bins + residual), then keep only plotted bins.\n",
    "    cur_draws_full = rng.multinomial(n_cur_eff, p_cur, size=n_iterations).astype(np.float64)\n",
    "    fut_draws_full = rng.multinomial(n_fut_eff, p_fut, size=n_iterations).astype(np.float64)\n",
    "    fut_urb_draws_full = rng.multinomial(n_fut_urb_eff, p_fut_urb, size=n_iterations).astype(np.float64)\n",
    "\n",
    "    cur_draws = cur_draws_full[:, :-1]\n",
    "    fut_draws = fut_draws_full[:, :-1]\n",
    "    fut_urb_draws = fut_urb_draws_full[:, :-1]\n",
    "\n",
    "    if normalize:\n",
    "        cur_vals = (cur_draws / n_cur_eff) * 100.0\n",
    "        fut_vals = (fut_draws / n_fut_eff) * 100.0\n",
    "        fut_urb_vals = (fut_urb_draws / n_fut_urb_eff) * 100.0\n",
    "    else:\n",
    "        # Scale sampled counts back to full-dataset-equivalent counts.\n",
    "        cur_vals = cur_draws * (n_current / n_cur_eff)\n",
    "        fut_vals = fut_draws * (n_future / n_fut_eff)\n",
    "        fut_urb_vals = fut_urb_draws * (n_future_urban / n_fut_urb_eff)\n",
    "\n",
    "    with np.errstate(divide='ignore', invalid='ignore'):\n",
    "        if not urban:\n",
    "            if c_fu:\n",
    "                rel = ((fut_urb_vals / cur_vals) - 1) * 100\n",
    "                rel[cur_vals == 0] = np.nan\n",
    "            else:\n",
    "                rel = ((fut_vals / cur_vals) - 1) * 100\n",
    "                rel[cur_vals == 0] = np.nan\n",
    "        else:\n",
    "            rel = ((fut_urb_vals - fut_vals) / fut_vals) * 100\n",
    "            rel[fut_vals == 0] = np.nan\n",
    "\n",
    "    ci_lower = np.nanpercentile(rel, 2.5, axis=0)\n",
    "    ci_upper = np.nanpercentile(rel, 97.5, axis=0)\n",
    "\n",
    "    return ci_lower.tolist(), ci_upper.tolist(), np.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "606027bc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Land Only domain selected. Frequencies will be calculated only for land grid points.\n",
      "<xarray.DataArray 'LANDMASK' (south_north: 1080, west_east: 1210, Time: 719)> Size: 4GB\n",
      "array([[[nan, nan, nan, ..., nan, nan, nan],\n",
      "        [nan, nan, nan, ..., nan, nan, nan],\n",
      "        [nan, nan, nan, ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan, ..., nan, nan, nan],\n",
      "        [nan, nan, nan, ..., nan, nan, nan],\n",
      "        [nan, nan, nan, ..., nan, nan, nan]],\n",
      "\n",
      "       [[nan, nan, nan, ..., nan, nan, nan],\n",
      "        [nan, nan, nan, ..., nan, nan, nan],\n",
      "        [nan, nan, nan, ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan, ..., nan, nan, nan],\n",
      "        [nan, nan, nan, ..., nan, nan, nan],\n",
      "        [nan, nan, nan, ..., nan, nan, nan]],\n",
      "\n",
      "       [[nan, nan, nan, ..., nan, nan, nan],\n",
      "        [nan, nan, nan, ..., nan, nan, nan],\n",
      "        [nan, nan, nan, ..., nan, nan, nan],\n",
      "        ...,\n",
      "...\n",
      "        [nan, nan, nan, ..., nan, nan, nan],\n",
      "        [nan, nan, nan, ..., nan, nan, nan],\n",
      "        [nan, nan, nan, ..., nan, nan, nan]],\n",
      "\n",
      "       [[nan, nan, nan, ..., nan, nan, nan],\n",
      "        [nan, nan, nan, ..., nan, nan, nan],\n",
      "        [nan, nan, nan, ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan, ..., nan, nan, nan],\n",
      "        [nan, nan, nan, ..., nan, nan, nan],\n",
      "        [nan, nan, nan, ..., nan, nan, nan]],\n",
      "\n",
      "       [[nan, nan, nan, ..., nan, nan, nan],\n",
      "        [nan, nan, nan, ..., nan, nan, nan],\n",
      "        [nan, nan, nan, ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan, ..., nan, nan, nan],\n",
      "        [nan, nan, nan, ..., nan, nan, nan],\n",
      "        [nan, nan, nan, ..., nan, nan, nan]]],\n",
      "      shape=(1080, 1210, 719), dtype=float32)\n",
      "Coordinates:\n",
      "    XLONG    (south_north, west_east) float32 5MB -109.5 -109.5 ... -82.01\n",
      "    XLAT     (south_north, west_east) float32 5MB 26.33 26.33 ... 45.52 45.51\n",
      "  * Time     (Time) datetime64[ns] 6kB 2017-04-01T01:00:00 ... 2017-04-30T23:...\n",
      "    XTIME    float32 4B ...\n",
      "Dimensions without coordinates: south_north, west_east\n",
      "[37022346.  8691408.  1524311.    43562.]\n",
      "[37766163.  9759756.  1796427.    71239.]\n",
      "[37831320.  9701307.  1765276.    65970.]\n",
      "Dataset sizes - Current: 47,281,627, Future: 49,393,585, Future+Urban: 49,363,873\n",
      "\n",
      "Raw frequencies:\n",
      "  Current: [37022346.  8691408.  1524311.    43562.]\n",
      "  Future: [37766163.  9759756.  1796427.    71239.]\n",
      "  Future+Urban: [37831320.  9701307.  1765276.    65970.]\n",
      "\n",
      "Frequencies from streamed bin counts:\n",
      "  Current: [37022346  8691408  1524311    43562]\n",
      "  Future: [37766163  9759756  1796427    71239]\n",
      "  Future+Urban: [37831320  9701307  1765276    65970]\n",
      "\n",
      "Expected relative changes from streamed bin counts:\n",
      "  ACC: [ 2.00910283 12.29200148 17.8517376  63.53473211]\n",
      "  ACC+Urb: [ 2.18509654 11.61950975 15.80812577 51.43932785]\n",
      "  Urb: [ 0.17252746 -0.59887768 -1.73405321 -7.39622959]\n",
      "\n",
      "============================================================\n",
      "BOOTSTRAP MODE: Raw counts (scaled)\n",
      "============================================================\n",
      "\n",
      "Bootstrap Confidence Intervals (95%):\n",
      "  ACC:       Lower=[1.8670958229697505, 11.824464631446824, 16.50523963174856, 48.417458861013316], Upper=[2.119340440455065, 12.855168689555194, 19.58252021293511, 77.76010520187221]\n",
      "  ACC+Urb:   Lower=[2.0335431787183196, 10.96619789438356, 14.192325591370015, 39.71843970706143], Upper=[2.3468571314038433, 12.157048871720157, 17.634818870998366, 61.432182631242085]\n",
      "  Urban:     Lower=[0.06143778481671458, -1.137408097788091, -3.1340498857476407, -13.994936122877919], Upper=[0.31229723327955716, -0.16793992004576572, -0.29793507645522754, -1.439063330110419]\n",
      "ACC+Urb: [ 2.18509654 11.61950975 15.80812577 51.43932785]\n",
      "ACC: [ 2.00910283 12.29200148 17.8517376  63.53473211]\n",
      "Urb: [ 0.17252746 -0.59887768 -1.73405321 -7.39622959]\n",
      "\n",
      "============================================================\n",
      "VERIFICATION: Do raw values fall within confidence intervals?\n",
      "============================================================\n",
      "Bin 0.25-2.5:\n",
      "  Warming:       2.01% [1.87, 2.12] | in CI=True\n",
      "  Combined:      2.19% [2.03, 2.35] | in CI=True\n",
      "  Urbanization:  0.17% [0.06, 0.31] | in CI=True\n",
      "Bin 2.5-10:\n",
      "  Warming:       12.29% [11.82, 12.86] | in CI=True\n",
      "  Combined:      11.62% [10.97, 12.16] | in CI=True\n",
      "  Urbanization:  -0.60% [-1.14, -0.17] | in CI=True\n",
      "Bin 10-50:\n",
      "  Warming:       17.85% [16.51, 19.58] | in CI=True\n",
      "  Combined:      15.81% [14.19, 17.63] | in CI=True\n",
      "  Urbanization:  -1.73% [-3.13, -0.30] | in CI=True\n",
      "Bin ≥50:\n",
      "  Warming:       63.53% [48.42, 77.76] | in CI=True\n",
      "  Combined:      51.44% [39.72, 61.43] | in CI=True\n",
      "  Urbanization:  -7.40% [-13.99, -1.44] | in CI=True\n",
      "Land Only\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_precip_speed_frequency_bar(c_precip, f_precip, fu_precip, start_time=None, end_time=None, normalize=True, land_only=False, land_mask=land_mask):\n",
    "\n",
    "    # Step 1: Work with precipitation fields lazily (xarray/dask) to avoid large memory spikes.\n",
    "    c_precip = c_precip['RAINNC']\n",
    "    f_precip = f_precip['RAINNC']\n",
    "    fu_precip = fu_precip['RAINNC']\n",
    "\n",
    "    # Match old workflow: only keep precip values >= 0.25 mm/hr before frequency + bootstrap.\n",
    "    c_precip = c_precip.where(c_precip >= 0.25)\n",
    "    f_precip = f_precip.where(f_precip >= 0.25)\n",
    "    fu_precip = fu_precip.where(fu_precip >= 0.25)\n",
    "\n",
    "    if land_only == True:\n",
    "        # 1 for land, 0 for water\n",
    "        land_mask = land_mask['LANDMASK'] == 1\n",
    "\n",
    "        c_precip = xr.where(land_mask, c_precip, float(\"nan\"))\n",
    "        f_precip = xr.where(land_mask, f_precip, float(\"nan\"))\n",
    "        fu_precip = xr.where(land_mask, fu_precip, float(\"nan\"))\n",
    "\n",
    "        domain_type = 'Land Only'\n",
    "        print('Land Only domain selected. Frequencies will be calculated only for land grid points.')\n",
    "    else:\n",
    "        domain_type = 'Full Domain'\n",
    "\n",
    "    c_precip = c_precip.dropna(dim='Time', how='all')\n",
    "    f_precip = f_precip.dropna(dim='Time', how='all')\n",
    "    fu_precip = fu_precip.dropna(dim='Time', how='all')\n",
    "\n",
    "    print(c_precip)\n",
    "\n",
    "    # Step 2: Compute counts once (streamed), then derive either percentages or raw counts.\n",
    "    c_counts, c_total = compute_bin_counts_from_dataarray(c_precip, PRECIP_BINS)\n",
    "    f_counts, f_total = compute_bin_counts_from_dataarray(f_precip, PRECIP_BINS)\n",
    "    fu_counts, fu_total = compute_bin_counts_from_dataarray(fu_precip, PRECIP_BINS)\n",
    "\n",
    "    if normalize == True:\n",
    "        freq_current = (c_counts / c_total) * 100.0\n",
    "        freq_future = (f_counts / f_total) * 100.0\n",
    "        freq_future_urban = (fu_counts / fu_total) * 100.0\n",
    "    else:\n",
    "        freq_current = c_counts.astype(np.float64)\n",
    "        freq_future = f_counts.astype(np.float64)\n",
    "        freq_future_urban = fu_counts.astype(np.float64)\n",
    "\n",
    "    print(freq_current)\n",
    "    print(freq_future)\n",
    "    print(freq_future_urban)\n",
    "\n",
    "    # Step 3: Calculate relative change between simulations\n",
    "    relative_change_future = calculate_relative_change(np.array(freq_future), np.array(freq_current))\n",
    "    rel_change_c_vs_fu = calculate_relative_change(np.array(freq_future_urban), np.array(freq_current))\n",
    "    relative_change_urban = calculate_relative_change_urbanization(\n",
    "        np.array(freq_future), np.array(freq_current), np.array(freq_future_urban)\n",
    "    )\n",
    "\n",
    "    print(f\"Dataset sizes - Current: {c_total:,}, Future: {f_total:,}, Future+Urban: {fu_total:,}\")\n",
    "\n",
    "    # Print raw frequencies for debugging\n",
    "    print(f\"\\nRaw frequencies:\")\n",
    "    print(f\"  Current: {freq_current}\")\n",
    "    print(f\"  Future: {freq_future}\")\n",
    "    print(f\"  Future+Urban: {freq_future_urban}\")\n",
    "\n",
    "    test_cur_freq = np.array(c_counts)\n",
    "    test_fut_freq = np.array(f_counts)\n",
    "    test_fu_freq = np.array(fu_counts)\n",
    "\n",
    "    print(f\"\\nFrequencies from streamed bin counts:\")\n",
    "    print(f\"  Current: {test_cur_freq}\")\n",
    "    print(f\"  Future: {test_fut_freq}\")\n",
    "    print(f\"  Future+Urban: {test_fu_freq}\")\n",
    "\n",
    "    print(f\"\\nExpected relative changes from streamed bin counts:\")\n",
    "    print(f\"  ACC: {((test_fut_freq / test_cur_freq) - 1) * 100}\")\n",
    "    print(f\"  ACC+Urb: {((test_fu_freq / test_cur_freq) - 1) * 100}\")\n",
    "    print(f\"  Urb: {((test_fu_freq - test_fut_freq) / test_fut_freq) * 100}\")\n",
    "\n",
    "    print(f\"\\n{'='*60}\")\n",
    "    print(f\"BOOTSTRAP MODE: {'Normalized (percentages)' if normalize else 'Raw counts (scaled)'}\")\n",
    "    print(f\"{'='*60}\")\n",
    "\n",
    "    # Run bootstrapping from counts (memory-safe for large datasets).\n",
    "    # Match old bootstrap settings: 100 iterations + 1,000,000 max sample size.\n",
    "    acc_ci_lower, acc_ci_upper, acc_sig = bootstrap_relative_change_from_counts(\n",
    "        c_counts,\n",
    "        f_counts,\n",
    "        fu_counts,\n",
    "        c_total,\n",
    "        f_total,\n",
    "        fu_total,\n",
    "        n_iterations=100,\n",
    "        urban=False,\n",
    "        c_fu=False,\n",
    "        normalize=normalize,\n",
    "        bootstrap_sample_size=1000000,\n",
    "    )\n",
    "\n",
    "    accurb_ci_lower, accurb_ci_upper, accurb_urban_sig = bootstrap_relative_change_from_counts(\n",
    "        c_counts,\n",
    "        f_counts,\n",
    "        fu_counts,\n",
    "        c_total,\n",
    "        f_total,\n",
    "        fu_total,\n",
    "        n_iterations=100,\n",
    "        urban=False,\n",
    "        c_fu=True,\n",
    "        normalize=normalize,\n",
    "        bootstrap_sample_size=1000000,\n",
    "    )\n",
    "\n",
    "    urb_ci_lower, urb_ci_upper, urb_sig = bootstrap_relative_change_from_counts(\n",
    "        c_counts,\n",
    "        f_counts,\n",
    "        fu_counts,\n",
    "        c_total,\n",
    "        f_total,\n",
    "        fu_total,\n",
    "        n_iterations=100,\n",
    "        urban=True,\n",
    "        c_fu=False,\n",
    "        normalize=normalize,\n",
    "        bootstrap_sample_size=1000000,\n",
    "    )\n",
    "\n",
    "    print(f\"\\nBootstrap Confidence Intervals (95%):\")\n",
    "    print(f\"  ACC:       Lower={acc_ci_lower}, Upper={acc_ci_upper}\")\n",
    "    print(f\"  ACC+Urb:   Lower={accurb_ci_lower}, Upper={accurb_ci_upper}\")\n",
    "    print(f\"  Urban:     Lower={urb_ci_lower}, Upper={urb_ci_upper}\")\n",
    "\n",
    "    # Step 4: Plotting\n",
    "    fig, ax1 = plt.subplots(figsize=(5, 4))\n",
    "    ax2 = ax1.twinx()\n",
    "    ax2.grid(True, axis='y', alpha=0.5, zorder=0)\n",
    "\n",
    "    bar_width = 0.2\n",
    "    x = np.arange(len(PRECIP_BINS))\n",
    "\n",
    "    ax1.bar(x - bar_width, freq_current, width=bar_width, color='black', label='Current', zorder=2)\n",
    "    ax1.bar(x, freq_future, width=bar_width, color='#1E88E5', label='Warming', zorder=2)\n",
    "    ax1.bar(x + bar_width, freq_future_urban, width=bar_width, color='#D81B60', label='Warming+Urban', zorder=2)\n",
    "\n",
    "    if normalize == True:\n",
    "        ax1.set_xlabel('Precipitation rate (mm hr$^{-1}$)')\n",
    "        ax1.set_ylabel('Percentage of Total Occurrences (%)')\n",
    "        ax1.set_yscale('log')\n",
    "        ax1.set_xticks(x)\n",
    "        ax1.set_xticklabels(BIN_LABELS)\n",
    "        ax1.set_ylim(0, 300)\n",
    "    else:\n",
    "        ax1.set_xlabel('Precipitation rate (mm hr$^{-1}$)')\n",
    "        ax1.set_ylabel('Frequency (# of Occurrences)')\n",
    "        ax1.set_yscale('log')\n",
    "        ax1.set_xticks(x)\n",
    "        ax1.set_xticklabels(BIN_LABELS)\n",
    "        ax1.set_ylim(10, 10e9)\n",
    "\n",
    "    ax2.plot(x, rel_change_c_vs_fu, color=\"#FFB507\", marker='^', linestyle='-', label='Combined', linewidth=2)\n",
    "    ax2.plot(x, relative_change_future, color='black', marker='o', linestyle='--', label='Warming', linewidth=2)\n",
    "    ax2.plot(x, relative_change_urban, color='black', marker='s', linestyle=':', label='Urban', linewidth=2)\n",
    "    ax2.set_ylabel('Relative change (%)', color='black')\n",
    "\n",
    "    print('ACC+Urb:', rel_change_c_vs_fu)\n",
    "    print('ACC:', relative_change_future)\n",
    "    print('Urb:', relative_change_urban)\n",
    "\n",
    "    print(f\"\\n{'='*60}\")\n",
    "    print(\"VERIFICATION: Do raw values fall within confidence intervals?\")\n",
    "    print(f\"{'='*60}\")\n",
    "    for i, bin_label in enumerate(BIN_LABELS):\n",
    "        acc_in_ci = acc_ci_lower[i] <= relative_change_future[i] <= acc_ci_upper[i]\n",
    "        cfu_in_ci = accurb_ci_lower[i] <= rel_change_c_vs_fu[i] <= accurb_ci_upper[i]\n",
    "        urb_in_ci = urb_ci_lower[i] <= relative_change_urban[i] <= urb_ci_upper[i]\n",
    "\n",
    "        print(f\"Bin {bin_label}:\")\n",
    "        print(f\"  Warming:       {relative_change_future[i]:.2f}% [{acc_ci_lower[i]:.2f}, {acc_ci_upper[i]:.2f}] | in CI={acc_in_ci}\")\n",
    "        print(f\"  Combined:      {rel_change_c_vs_fu[i]:.2f}% [{accurb_ci_lower[i]:.2f}, {accurb_ci_upper[i]:.2f}] | in CI={cfu_in_ci}\")\n",
    "        print(f\"  Urbanization:  {relative_change_urban[i]:.2f}% [{urb_ci_lower[i]:.2f}, {urb_ci_upper[i]:.2f}] | in CI={urb_in_ci}\")\n",
    "\n",
    "    x = np.array(x)\n",
    "    acc_lower = np.array(acc_ci_lower)\n",
    "    acc_upper = np.array(acc_ci_upper)\n",
    "    urb_lower = np.array(urb_ci_lower)\n",
    "    urb_upper = np.array(urb_ci_upper)\n",
    "    accurb_lower = np.array(accurb_ci_lower)\n",
    "    accurb_upper = np.array(accurb_ci_upper)\n",
    "\n",
    "    ax2.fill_between(x, accurb_lower, accurb_upper, color=\"#FFB507\", alpha=0.3, zorder=1)\n",
    "    ax2.fill_between(x, acc_lower, acc_upper, color='blue', alpha=0.2, zorder=1)\n",
    "    ax2.fill_between(x, urb_lower, urb_upper, color='green', alpha=0.2, zorder=1)\n",
    "\n",
    "    all_values = np.concatenate([\n",
    "        rel_change_c_vs_fu,\n",
    "        relative_change_future,\n",
    "        relative_change_urban,\n",
    "        acc_lower,\n",
    "        acc_upper,\n",
    "        urb_lower,\n",
    "        urb_upper,\n",
    "        accurb_lower,\n",
    "        accurb_upper,\n",
    "    ])\n",
    "    all_values = all_values[~np.isnan(all_values)]\n",
    "\n",
    "    if len(all_values) > 0:\n",
    "        y_min = np.min(all_values)\n",
    "        y_max = np.max(all_values)\n",
    "        y_range = y_max - y_min\n",
    "        padding = max(y_range * 0.15, 5)\n",
    "        ax2.set_ylim(y_min - padding, y_max + padding)\n",
    "    else:\n",
    "        ax2.set_ylim(-20, 110)\n",
    "\n",
    "    if monlist[0] == '04':\n",
    "        month = 'April'\n",
    "    elif monlist[0] == '05':\n",
    "        month = 'May'\n",
    "    elif monlist[0] == '06':\n",
    "        month = 'June'\n",
    "\n",
    "    if select_time_window == True:\n",
    "        start_time = datetime.strptime(start_time, '%Y-%m-%dT%H:%M:%S')\n",
    "        end_time = datetime.strptime(end_time, '%Y-%m-%dT%H:%M:%S')\n",
    "        ax1.set_title(f'{start_time.strftime(\"%Y-%m-%d %Hz\")} to {end_time.strftime(\"%Y-%m-%d %Hz\")}', fontsize=12)\n",
    "    else:\n",
    "        ax1.set_title(f'{month} ({domain_type})', fontsize=12)\n",
    "\n",
    "    fig.tight_layout()\n",
    "    print(domain_type)\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "plot_precip_speed_frequency_bar(\n",
    "    c_precip,\n",
    "    f_precip,\n",
    "    fu_precip,\n",
    "    start_time=start_time,\n",
    "    end_time=end_time,\n",
    "    normalize=False,\n",
    "    land_only=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "c0623c88",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_max_precip_contours(ds1, ds2, ds3, threshold=50):\n",
    "    # Create the plot\n",
    "    fig, ax_precip = plt.subplots(\n",
    "        figsize=(7, 7),\n",
    "        subplot_kw={\"projection\": ccrs.PlateCarree()}\n",
    "    )\n",
    "\n",
    "    precip_current = ds1['RAINNC']\n",
    "    precip_future = ds2['RAINNC']\n",
    "    precip_future_urban = ds3['RAINNC']\n",
    "\n",
    "    max_precip_current = precip_current.max(dim='Time')\n",
    "    max_precip_future = precip_future.max(dim='Time')\n",
    "    max_precip_future_urban = precip_future_urban.max(dim='Time')\n",
    "\n",
    "    # Smooth if necessary\n",
    "    def downscale_field(da):\n",
    "        return da.coarsen(\n",
    "            south_north=4,\n",
    "            west_east=4,\n",
    "            boundary=\"trim\"\n",
    "        ).mean()\n",
    "\n",
    "    max_precip_current = downscale_field(max_precip_current)\n",
    "    max_precip_future = downscale_field(max_precip_future)\n",
    "    max_precip_future_urban = downscale_field(max_precip_future_urban)\n",
    "\n",
    "    lats = downscale_field(ds1['XLAT'])\n",
    "    lons = downscale_field(ds1['XLONG'])\n",
    "\n",
    "    # Ensure 2D coordinate fields for plotting (drop any Time dimension).\n",
    "    if 'Time' in lats.dims:\n",
    "        lats = lats.isel(Time=0)\n",
    "    if 'Time' in lons.dims:\n",
    "        lons = lons.isel(Time=0)\n",
    "\n",
    "    # Use numeric extent values (Cartopy expects plain floats).\n",
    "    lon_min = float(np.nanmin(lons.values))\n",
    "    lon_max = float(np.nanmax(lons.values))\n",
    "    lat_min = float(np.nanmin(lats.values))\n",
    "    lat_max = float(np.nanmax(lats.values))\n",
    "    ax_precip.set_extent([lon_min, lon_max, lat_min, lat_max], crs=ccrs.PlateCarree())\n",
    "\n",
    "    # Occurrence mask: where max precip during the period reaches/exceeds threshold\n",
    "    precip_threshold_current = (max_precip_current >= threshold)\n",
    "    precip_threshold_future = (max_precip_future >= threshold)\n",
    "    precip_threshold_future_urban = (max_precip_future_urban >= threshold)\n",
    "\n",
    "    ax_precip.contour(\n",
    "        lons, lats, precip_threshold_current, colors='black', linewidths=1.5,\n",
    "        transform=ccrs.PlateCarree(), zorder=2\n",
    "    )\n",
    "    ax_precip.contour(\n",
    "        lons, lats, precip_threshold_future, colors='#1E88E5', linewidths=1.5,\n",
    "        transform=ccrs.PlateCarree(), zorder=2\n",
    "    )\n",
    "    ax_precip.contour(\n",
    "        lons, lats, precip_threshold_future_urban, colors='#D81B60', linewidths=1.5,\n",
    "        transform=ccrs.PlateCarree(), zorder=2\n",
    "    )\n",
    "\n",
    "    # Build legend from explicit handles to avoid plotting dummy points on the map.\n",
    "    from matplotlib.lines import Line2D\n",
    "    legend_handles = [\n",
    "        Line2D([0], [0], color='black', lw=1.8, label='Current'),\n",
    "        Line2D([0], [0], color='#1E88E5', lw=1.8, label='Warming'),\n",
    "        Line2D([0], [0], color='#D81B60', lw=1.8, label='Warming+Urban'),\n",
    "    ]\n",
    "\n",
    "    # Add features and title\n",
    "    ax_precip.add_feature(cfeature.STATES, edgecolor=\"gray\", linewidths=0.65, alpha=0.7)\n",
    "    ax_precip.add_feature(cfeature.COASTLINE, edgecolor=\"gray\", linewidths=0.65, alpha=0.7)\n",
    "    gl = ax_precip.gridlines(\n",
    "        draw_labels=True, linewidth=0.6, color='gray', alpha=0.5,\n",
    "        linestyle='--', zorder=2\n",
    "    )\n",
    "    gl.top_labels = False\n",
    "    gl.right_labels = False\n",
    "    gl.left_labels = True\n",
    "    gl.bottom_labels = True\n",
    "\n",
    "    start_label = ds1.Time.min().dt.strftime(\"%m-%d %Hz\").values\n",
    "    end_label = ds1.Time.max().dt.strftime(\"%m-%d %Hz\").values\n",
    "\n",
    "    # Left-margin title styling to match the wind contour figure.\n",
    "    ax_precip.text(\n",
    "        0.0,\n",
    "        1.01,\n",
    "        f'Contours Where Max Precipitation Rate ≥{threshold} mm hr$^{{-1}}$\\n({start_label} to {end_label})',\n",
    "        transform=ax_precip.transAxes,\n",
    "        ha='left',\n",
    "        va='bottom',\n",
    "        fontsize=12,\n",
    "    )\n",
    "\n",
    "    ax_precip.legend(handles=legend_handles, loc='upper right')\n",
    "    fig.subplots_adjust(left=0.07, right=0.99, bottom=0.07, top=0.92)\n",
    "    plt.show()\n",
    "\n",
    "plot_max_precip_contours(ds1=c_precip, ds2=f_precip, ds3=fu_precip, threshold=75)"
   ]
  }
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