update

new

GMet_location_avgSI.txt

@@ -0,0 +1,23 @@
+
+Navrongo           -1.10    10.90    0.973
+Wa                 -2.50    10.05    0.833
+Tamale             -0.85     9.43    0.838
+Yendi              -0.02     9.45    0.821
+Bole               -2.48     9.03    0.749
+Kete_Krachi        -0.17     7.80    0.818
+Kumasi             -1.60     6.72    0.600
+Sefwi_Bekwai       -2.33     6.20    0.572
+Abetifi            -0.75     6.67    0.609
+Ho                  0.48     6.67    0.595
+Akatsi              0.80     6.12    0.765
+Akuse               0.12     6.10    0.631
+Koforidua          -0.25     6.08    0.562
+Akim_Oda           -0.98     5.93    0.559
+Ada                 0.63     5.78    0.900
+Tema                0.00     5.62    0.862
+Accra              -0.17     5.60    0.810
+Saltpond           -1.07     5.20    0.820
+Takoradi           -1.77     4.88    0.781
+Axim               -2.23     4.87    0.751
+Damongo            -1.826 	 9.091 	 0.990
+Zuarungu 	       -0.810 	 10.800  0.916

Ghana Map plot.py

@@ -0,0 +1,149 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Fri Jan 27 17:32:37 2023
+
+@author: micha
+"""
+
+######  Import required libraries #########
+import cartopy.crs as ccrs
+import cartopy.feature as cf
+from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter
+import pandas as pd
+from pathlib import Path as Path
+import seaborn as sns
+import matplotlib
+from matplotlib import pyplot as plt, dates
+import numpy as np
+import numpy as np
+from matplotlib import gridspec
+import os
+import glob
+import dataframe_image as dfi
+import itertools
+import matplotlib.patheffects as pe
+import matplotlib.dates as mdates
+# from matplotlib.dates import DateFormatter
+from matplotlib.dates import YearLocator, DateFormatter
+from matplotlib.ticker import (
+    MultipleLocator, FormatStrFormatter, AutoMinorLocator)
+
+import warnings
+warnings.filterwarnings('ignore')
+
+################## Reading data for Stations  ###############
+dat = pd.read_fwf('C:/Users/micha/OneDrive/Desktop/Rainfall Analysis Publication/GMet_location_avgSI.txt',
+                  names=['Station', 'Longitude', 'Latitude', 'St'])
+
+##### Functoin to Draw a zebra border around maps ############
+
+crs = ccrs.PlateCarree()
+
+
+def add_zebra_frame(ax, lw=4, crs="pcarree", zorder=None):
+
+    ax.spines["geo"].set_visible(False)
+    left, right, bot, top = ax.get_extent()
+
+    # Alternate black and white line segments
+    bws = itertools.cycle(["k", "white"])
+
+    xticks = sorted([left, *ax.get_xticks(), right])
+    xticks = np.unique(np.array(xticks))
+    yticks = sorted([bot, *ax.get_yticks(), top])
+    yticks = np.unique(np.array(yticks))
+    for ticks, which in zip([xticks, yticks], ["lon", "lat"]):
+        for idx, (start, end) in enumerate(zip(ticks, ticks[1:])):
+            bw = next(bws)
+            if which == "lon":
+                xs = [[start, end], [start, end]]
+                ys = [[bot, bot], [top, top]]
+            else:
+                xs = [[left, left], [right, right]]
+                ys = [[start, end], [start, end]]
+
+            # For first and lastlines, used the "projecting" effect
+            capstyle = "butt" if idx not in (
+                0, len(ticks) - 2) else "projecting"
+            for (xx, yy) in zip(xs, ys):
+                ax.plot(
+                    xx,
+                    yy,
+                    color=bw,
+                    linewidth=lw,
+                    clip_on=False,
+                    transform=crs,
+                    zorder=zorder,
+                    solid_capstyle=capstyle,
+                    # Add a black border to accentuate white segments
+                    path_effects=[
+                        pe.Stroke(linewidth=lw + 1, foreground="black"),
+                        pe.Normal(),
+                    ],
+                )
+
+
+#####################  Plot for  study Area ###########################
+plt.figure(figsize=(10, 9))  # Specifying the size of the figure
+# Specifying the type of geopatial plot
+ax = plt.axes(projection=ccrs.PlateCarree())
+ax.add_feature(cf.COASTLINE, alpha=0.8)
+ax.add_feature(cf.BORDERS)
+# ax.add_feature(cf.LAND)
+ax.set_extent([-3.2, 0.8, 11.2, 7.7])  # setting the map boundaries
+# ax.stock_img()
+ax.add_feature(cf.STATES, alpha=0.1)  # adding territorial boundaries
+
+ax.plot(dat.Longitude,
+        dat.Latitude,
+        'ro',  # plotting the longitudes and latitudes of the station
+        ms=7,
+        color='k')  # ,
+# for longitude, latitude, name in zip(dat.Longitude, dat.Latitude, dat.Station):
+#     if name in ['Damongo', 'Kete_Krachi', 'Wa', 'Bole', 'Tamale', 'Yendi']:
+#         ax.plot(dat.Longitude,
+#                 dat.Latitude,
+#                 'ro',                                       ##### plotting the longitudes and latitudes of the station
+#                 ms=7,
+#                 color = 'k')
+# transform=ccrs.Geodetic(),label='Synoptic stations')
+
+s_stations = np.asarray(dat.Station)
+
+for longitude, latitude, name in zip(dat.Longitude, dat.Latitude, dat.Station):
+    if name in ['Damongo', 'Kete_Krachi', 'Wa', 'Bole', 'Tamale', 'Yendi']:
+        ax.text(longitude + .05, latitude + .15,
+                name,
+                va='center',
+                ha='center', transform=ccrs.Geodetic(), fontweight='bold', fontsize='15')
+    if name in ['Navrongo']:
+        ax.text(longitude - 0.4, latitude,
+                name,
+                va='center',
+                ha='center', transform=ccrs.Geodetic(), fontweight='bold', fontsize='15')
+    if name in ['Zuarungu']:
+        ax.text(longitude, latitude-0.1,
+                name,
+                va='center',
+                ha='center', transform=ccrs.Geodetic(), fontweight='bold', fontsize='15')
+    # else:
+    #     ax.text(longitude + .05, latitude + .12,
+    # else:
+    #     ax.text(longitude + .05, latitude + .12,
+    #             name,
+    #             va='center',
+    #             ha='center', transform=ccrs.Geodetic(), fontweight='bold',fontsize = '10')
+
+
+ax.set_xticks([-3, -2.5, -2.0, -1.5, -1.0, -0.5, 0, 0.5],
+              crs=ccrs.PlateCarree())
+ax.set_yticks([11, 10.5, 10, 9.5, 9.0, 8.5, 8], crs=ccrs.PlateCarree())
+lon_formatter = LongitudeFormatter(zero_direction_label=True)
+lat_formatter = LatitudeFormatter()
+ax.xaxis.set_major_formatter(lon_formatter)
+ax.yaxis.set_major_formatter(lat_formatter)
+add_zebra_frame(ax, lw=4, crs=crs)
+# plt.title('')
+
+# #plt.savefig('Synoptic Stations.pdf',bbox_inches = 'tight')
+# plt.savefig('Graphs/graphs/Study_Area.JPEG',bbox_inches = 'tight')

analyis.ipynb

@@ -0,0 +1,115 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import xarray as xr\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import cartopy as cp\n",
+    "import cartopy.crs as ccrs\n",
+    "import cartopy.feature as cf\n",
+    "from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter\n",
+    "from pathlib import Path\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore')\n",
+    "from mpl_toolkits.basemap import Basemap"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data = xr.open_dataset(\"./data/Ghana_chirps_dRR_1991_2020.nc\")\n",
+    "data = data.sel(latitude = slice(4,12), longitude = slice(-3,1.5)).precip\n",
+    "data = data.resample(time = 'y').sum('time')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "location = pd.read_fwf(\"GMet_location_avgSI.txt\",  names = ['Station','longitude','latitude','g'])\n",
+    "path_to_file=Path('data/')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import netCDF4 as nc\n",
+    "import numpy as np\n",
+    "import os\n",
+    "\n",
+    "# Function to read NetCDF file and save station data into individual text files\n",
+    "def separate_stations_to_txt(nc_file, output_dir):\n",
+    "    # Open the NetCDF file\n",
+    "    ds = nc.Dataset(\"./data/Ghana_chirps_dRR_1991_2020.nc\")\n",
+    "    \n",
+    "    # Assuming the structure of the dataset\n",
+    "    # Dimensions: time, station\n",
+    "    # Variables: time, station, rainfall\n",
+    "    \n",
+    "    # Extract the dimensions and variables\n",
+    "    times = ds.variables['time'][:]  # or appropriate time variable\n",
+    "    stations = ds.variables['station'][:]  # or appropriate station variable\n",
+    "    rainfall = ds.variables['rainfall'][:]  # or appropriate rainfall variable\n",
+    "    \n",
+    "    # Ensure output directory exists\n",
+    "    if not os.path.exists(\"data\"):\n",
+    "        os.makedirs(\"data\")\n",
+    "    \n",
+    "    # Loop through each station and save the data\n",
+    "    for i, station in enumerate(stations):\n",
+    "        # Create a filename for each station\n",
+    "        station_id = str(station)\n",
+    "        filename = os.path.join(\"data\", f'station_{station_id}.txt')\n",
+    "        \n",
+    "        # Open a text file for the station\n",
+    "        with open(filename, 'w') as f:\n",
+    "            f.write('Time\\tRainfall\\n')\n",
+    "            for j, time in enumerate(times):\n",
+    "                f.write(f'{time}\\t{rainfall[j, i]}\\n')\n",
+    "    \n",
+    "    # Close the dataset\n",
+    "    ds.close()\n",
+    "\n",
+    "# Example usage\n",
+    "#nc_file = 'path/to/ghana_rainfall_data.nc'\n",
+    "#output_dir = 'output_directory'\n",
+    "#separate_stations_to_txt(nc_file, output_dir)\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.11.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}