Add Ecuador region notebooks and config

regions/Ecuador/1.1. INAMHI-prepro.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 1.1. INAMHI Preprocessing\n",
+    "This notebook converts raw stake mass-balance files from the Ecuadorian INAMHI network into cleaned CSV tables."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from scripts.config_EC import *\n",
+    "from scripts.helpers import seed_all\n",
+    "seed_all(42)\n",
+    "# TODO: implement preprocessing for INAMHI glacier mass-balance data"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

regions/Ecuador/1.2. ERA5Land-prepro.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 1.2. ERA5-Land Preprocessing\n",
+    "Download and format ERA5-Land climate variables for Ecuador." 
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from scripts.config_EC import path_ERA5_raw\n",
+    "# TODO: add ERA5-Land download and processing steps for Ecuador"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

regions/Ecuador/3.2 Train-ML-model.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 3.2 Train ML Model\n",
+    "Assemble the Ecuador dataset, add features, and train an XGBoost model." 
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from scripts.config_EC import *\n",
+    "from scripts.xgb_helpers import process_or_load_data\n",
+    "# TODO: load INAMHI mass balance data and call process_or_load_data"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

regions/Ecuador/scripts/config_EC.py

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+# <------------------ INAMHI/Local Glacier Data: ------------------>
+# Point data
+path_PMB_INAMHI_raw = '../../../data/INAMHI/point/raw/'
+path_PMB_INAMHI_csv = '../../../data/INAMHI/point/csv/'
+
+# Glacier wide data
+path_SMB_INAMHI_raw = '../../../data/INAMHI/glacier-wide/raw/'
+path_SMB_INAMHI_csv = '../../../data/INAMHI/glacier-wide/csv/'
+
+# Gridded data for MBM to use for making predictions over whole grid
+path_glacier_grid = '../../../data/INAMHI/topo/gridded_topo_inputs/'  # DEMs & topo
+
+# Topo data
+path_DEM = '../../../data/INAMHI/topo/DEM/'  # DEMs
+path_pcsr = '../../../data/INAMHI/topo/pcsr/'  # Potential incoming clear sky solar radiation
+
+path_distributed_MB = '../../../data/INAMHI/distributed_MB_grids/'
+path_geodetic_MB = '../../../data/INAMHI/geodetic/'
+path_glacier_ids = '../../../data/INAMHI/EC_glacier_ids.csv'  # glacier ids for EC glaciers
+
+# <------------------ OTHER PATHS: ------------------>
+path_ERA5_raw = '../../../data/ERA5Land/raw/'  # ERA5-Land
+path_S2 = '../../../data/Sentinel/'  # Sentinel-2
+path_OGGM = '../../../data/OGGM/'
+path_glogem = '../../../data/GloGEM'  # glogem c_prec and t_off factors
+
+# <------------------ OTHER USEFUL FUNCTIONS & ATTRIBUTES: ------------------>
+vois_climate_long_name = {
+    't2m': 'Temperature',
+    'tp': 'Precipitation',
+    't2m_corr': 'Temperature corr.',
+    'tp_corr': 'Precipitation corr.',
+    'slhf': 'Surf. latent heat flux',
+    'sshf': 'Surf. sensible heat flux',
+    'ssrd': 'Surf. solar rad. down.',
+    'fal': 'Albedo',
+    'str': 'Surf. net thermal rad.',
+    'pcsr': 'Pot. in. clear sky solar rad.',
+    'u10': '10m E wind',
+    'v10': '10m N wind',
+}
+
+vois_units = {
+    't2m': 'C',
+    'tp': 'm w.e.',
+    't2m_corr': 'C',
+    'tp_corr': 'm w.e.',
+    'slhf': 'J m-2',
+    'sshf': 'J m-2',
+    'ssrd': 'J m-2',
+    'fal': '',
+    'str': 'J m-2',
+    'pcsr': 'J m-2',
+    'u10': 'm s-1',
+    'v10': 'm s-1',
+}

regions/Ecuador/scripts/helpers.py

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+import torch
+import numpy as np
+import random as rd
+import os
+import gc 
+import shutil
+from matplotlib.colors import to_hex
+from matplotlib import pyplot as plt
+
+
+def seed_all(seed=None):
+    """Sets the random seed everywhere for reproducibility.
+    """
+    if seed is None:
+        seed = 10  # Default seed value
+
+    # Python built-in random
+    rd.seed(seed)
+
+    # NumPy random
+    np.random.seed(seed)
+
+    # PyTorch seed
+    torch.manual_seed(seed)
+    torch.cuda.manual_seed(seed)
+    torch.cuda.manual_seed_all(seed)  # If using multiple GPUs
+
+    # Ensuring deterministic behavior in CuDNN
+    torch.backends.cudnn.deterministic = True
+    torch.backends.cudnn.benchmark = False
+
+    # Setting CUBLAS environment variable (helps in newer versions)
+    os.environ["CUBLAS_WORKSPACE_CONFIG"] = ":4096:8"
+
+
+def free_up_cuda():
+    """Frees up unused CUDA memory in PyTorch."""
+    gc.collect()  # Run garbage collection
+    torch.cuda.empty_cache()  # Free unused cached memory
+    torch.cuda.ipc_collect()  # Collect inter-process memory
+
+
+def get_cmap_hex(cmap, length):
+    """
+    Function to get a get a list of colours as hex codes
+
+    :param cmap:    name of colourmap
+    :type cmap:     str
+
+    :return:        list of hex codes
+    :rtype:         list
+    """
+    # Get cmap
+    rgb = plt.get_cmap(cmap)(np.linspace(0, 1, length))
+
+    # Convert to hex
+    hex_codes = [to_hex(rgb[i, :]) for i in range(rgb.shape[0])]
+
+    return hex_codes
+
+def emptyfolder(path):
+    """Removes all files and subdirectories in the given folder."""
+    if os.path.exists(path):
+        for item in os.listdir(path):
+            item_path = os.path.join(path, item)
+            try:
+                if os.path.isfile(item_path):
+                    os.remove(item_path)  # Remove file
+                elif os.path.isdir(item_path):
+                    shutil.rmtree(item_path)  # Remove folder and all contents
+            except Exception as e:
+                print(f"Error removing {item_path}: {e}")
+    else:
+        os.makedirs(path, exist_ok=True)  # Ensure directory exists
+
+# difference between two lists
+def Diff(li1, li2):
+    li_dif = list(set(li1) - set(li2))
+    return li_dif
+
+def format_rgi_code(X):
+    # Convert X to a string, and pad with leading zeros if its length is less than 5
+    Y = str(X).zfill(5)
+    # Return the final formatted string
+    return f"RGI60-11.{Y}"