#!/usr/bin/env python
# coding: utf-8

# In[2]:


import xarray as xr
import pandas as pd
import os
import geopandas as gpd
import numpy as np
import matplotlib.pyplot as plt
import regionmask


# In[3]:


era_data_path="C:/Users/dboateng/Desktop/Datasets/ERA5/monthly_1950_2021/"
path_shapefile="C:/Users/dboateng/Desktop/Datasets/Station/Ghana/Ghana_ShapeFile/gh_wgs16dregions.shp"
afr_shape = "C:/Users/dboateng/Desktop/Datasets/Station/Ghana/Africa_shapefile/afr_g2014_2013_0.shp"

from1979to2012 = pd.date_range(start="1979-01-01", end="2012-12-31", freq="MS")


# In[4]:


tp_monthly= xr.open_dataset(os.path.join(era_data_path, "tp_monthly.nc"))
tp_monthly = tp_monthly["tp"].sel(time=from1979to2012).mean(dim="time")


# In[5]:


ghana_shape = gpd.read_file(path_shapefile)


# In[15]:


np.array(ghana_shape.geometry[0])


# In[16]:


poly = regionmask.Regions(np.array(ghana_shape.geometry[0]))


# In[8]:


poly


# In[9]:


mask = poly.mask(tp_monthly, lat_name="latitude", lon_name="longitude", wrap_lon=True)


# In[10]:


mask


# In[11]:


pr_mask = tp_monthly.where(mask==0)


# In[12]:


pr_mask