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%matplotlib inline
import imdlib as imd
import numpy as np
import string

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# load data
start_yr, end_yr = 2015, 2019

variable = 'rain'
rain = imd.open_data(variable, start_yr, end_yr,'yearwise', '../data')
# Fill Missing Data
rain.fill_na()
# Clip data for the Godavari River Basin (using Shapefile)
rain.clip('../gis/god.shp')

variable = 'tmax'
tmax = imd.open_data(variable, start_yr, end_yr,'yearwise', '../data')
# Fill Missing Data
tmax.fill_na()
# Clip data for the Godavari River Basin (using Shapefile)
tmax.clip('../gis/god.shp')


variable = 'tmin'
tmin = imd.open_data(variable, start_yr, end_yr,'yearwise', '../data')
# Fill Missing Data
tmin.fill_na()
# Clip data for the Godavari River Basin (using Shapefile)
tmin.clip('../gis/god.shp')

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cwd = rain.copy()
cwd.compute('cwd', 'A')

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dr = rain.copy()
dr.compute('dr', 'A')

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dtr_tmax = tmax.copy()
dtr_tmin = tmin.copy()
dtr_tmax.compute('dtr', 'A', tmin=dtr_tmin)

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d64 = rain.copy()
d64.compute('d64', 'A')

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mmk_hr = rain.copy()
mmk_hr.compute('mmk_hr', 'A')

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mnadt = tmin.copy()
mnadt.compute('mnadt', 'A')

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mxadt = tmax.copy()
mxadt.compute('mxadt', 'A')

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pci = rain.copy()
pci.compute('pci', 'A')

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rtwd = rain.copy()
rtwd.compute('rtwd', 'A')

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rx5d = rain.copy()
rx5d.compute('rx5d', 'A')

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rxa = rain.copy()
rxa.compute('rxa', 'A')

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sdii = rain.copy()
sdii.compute('sdii', 'A')

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spr = rain.copy()
spr.compute('spr', 'A')

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sse = rain.copy()
sse.compute('sse', 'A')

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sstr = rain.copy()
sstr.compute('sstr', 'A')

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# IMD to Netcdf and prepare for plot

cwd = cwd.get_xarray()
cwd = cwd.isel(time=-1)
cwd = cwd.cwd

dr = dr.get_xarray()
dr = dr.isel(time=-1)
dr = dr.dr

dtr_tmax = dtr_tmax.get_xarray()
dtr_tmax = dtr_tmax.isel(time=-1)
dtr_tmax = dtr_tmax.dtr

d64 = d64.get_xarray()
d64 = d64.isel(time=-1)
d64 = d64.d64

mmk_hr = mmk_hr.get_xarray()
mmk_hr = mmk_hr.isel(time=-1)
mmk_hr = mmk_hr.mmk_hr

mnadt = mnadt.get_xarray()
mnadt = mnadt.isel(time=-1)
mnadt = mnadt.mnadt

mxadt = mxadt.get_xarray()
mxadt = mxadt.isel(time=-1)
mxadt = mxadt.mxadt

pci = pci.get_xarray()
pci = pci.isel(time=-1)
pci = pci.pci

rtwd = rtwd.get_xarray()
rtwd = rtwd.isel(time=-1)
rtwd = rtwd.rtwd

rx5d = rx5d.get_xarray()
rx5d = rx5d.isel(time=-1)
rx5d = rx5d.rx5d

rxa = rxa.get_xarray()
rxa = rxa.isel(time=-1)
rxa = rxa.rxa

sdii = sdii.get_xarray()
sdii = sdii.isel(time=-1)
sdii = sdii.sdii

spr = spr.get_xarray()
spr = spr.isel(time=-1)
spr = spr.spr

sse = sse.get_xarray()
sse = sse.isel(time=-1)
sse = sse.sse

sstr = sstr.get_xarray()
sstr = sstr.isel(time=-1)
sstr = sstr.sstr

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import cartopy.crs as ccrs
import cartopy
from cartopy.feature import ShapelyFeature
from cartopy.io.shapereader import Reader
from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter
import cmaps
import matplotlib.colors as colors
import matplotlib.image as mpimg
from matplotlib.ticker import MultipleLocator
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
import matplotlib as mpl
    
class MidpointNormalize(colors.Normalize):
    def __init__(self, vmin=None, vmax=None, midpoint=None, clip=False):
        self.midpoint = midpoint
        colors.Normalize.__init__(self, vmin, vmax, clip)

    def __call__(self, value, clip=None):
        # I'm ignoring masked values and all kinds of edge cases to make a
        # simple example...
        x, y = [self.vmin, self.midpoint, self.vmax], [0, 0.5, 1]
        return np.ma.masked_array(np.interp(value, x, y), np.isnan(value))
    
proj = ccrs.PlateCarree() 
lon_formatter = LongitudeFormatter(zero_direction_label=True)
# lon_formatter = LongitudeFormatter()
lat_formatter = LatitudeFormatter()



# Shapefile Read
sp_nm = '../gis/god.shp'
shape_feature = ShapelyFeature(Reader(sp_nm).geometries(), proj, edgecolor='black')


# # Get bounding box
# import geopandas as gpd
# tmp = gpd.read_file(sp_nm)
# print(tmp.total_bounds) # print lower left (lon, lat) and upper right (lon, lat)
# # 73.47881334, 16.53814697, 83.15886298, 22.69166667

fig, ax = plt.subplots(5, 3, figsize=(8, 11), subplot_kw={'projection':proj})
fig.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=0.25, hspace=-0.5)

plt.rcParams['axes.xmargin'] = 0
plt.rcParams['font.size'] = 11
plt.rcParams["font.family"] = "Times New Roman"
plt.rcParams["font.weight"] = "normal"
fs = 10
plt_lab = string.ascii_lowercase[:15]
plt_tit = ['cwd', 'dr', 'dtr', 'd64', 'mmk_hr', 'mnadt', 'mxadt', 'pci', 'rtwd', 'rx5d', 'rxa', 'sdii', 'spr', 'sse', 'sstr']


f1_1 = cwd.plot(ax=ax[0, 0], transform=proj, cmap = cmaps.WhiteGreen,
               cbar_kwargs={'ticks': [5, 10, 15, 20, 25],
                            "shrink":0.34, "aspect":10, 'label':'Days'})
f1_2 = dr.plot(ax=ax[0, 1], transform=proj, cmap = cmaps.MPL_Blues,
              cbar_kwargs={'ticks': [38, 68, 98, 128],
                            "shrink":0.34, "aspect":10, 'label':'Days'})
f1_3 = dtr_tmax.plot(ax=ax[0, 2], transform=proj, cmap = cmaps.MPL_Oranges,
                    cbar_kwargs={'ticks': [9.8, 11.1, 12.4, 13.7],
                            "shrink":0.34, "aspect":10, 'label':'$^o$C'})
f1_4 = d64.plot(ax=ax[1, 0], transform=proj, cmap = 'Blues',
               cbar_kwargs={'ticks': [0, 6, 12, 18],
                            "shrink":0.34, "aspect":10, 'label':'Days'})

vmin_f1_4 = -2
vmax_f1_4 = 2
norm_f1_4 = colors.TwoSlopeNorm(vmin=vmin_f1_4, vcenter=0, vmax=vmax_f1_4)
f1_5 = mmk_hr.plot(ax=ax[1, 1], transform=proj, cmap = cmaps.CBR_coldhot_r,
                  vmin=vmin_f1_4, vmax=vmax_f1_4, norm=norm_f1_4,
                  cbar_kwargs={'ticks': [-2, -1, 0, 1, 2],
                            "shrink":0.34, "aspect":10, 'label':'Z'})                     
f1_6 = mnadt.plot(ax=ax[1, 2], transform=proj, cmap = cmaps.MPL_YlGnBu_r,
                 cbar_kwargs={'ticks': [4, 8, 12],
                            "shrink":0.34, "aspect":10, 'label':'$^o$C'})
f1_7 = mxadt.plot(ax=ax[2, 0],  transform=proj, cmap = 'Reds',
                 cbar_kwargs={'ticks': [40, 42, 44, 46],
                            "shrink":0.34, "aspect":10, 'label':'$^o$C'})

f1_8 = pci.plot(ax=ax[2, 1], transform=proj, cmap = cmaps.spread_15lev,
               cbar_kwargs={'ticks': [18, 22, 26, 30],
                            "shrink":0.34, "aspect":10, 'label':''})
f1_9 = rtwd.plot(ax=ax[2, 2], transform=proj, cmap = 'jet_r',
                cbar_kwargs={'ticks': [500, 1500, 2500, 3500],
                            "shrink":0.34, "aspect":10, 'label':'mm/y'})
f1_10 = rx5d.plot(ax=ax[3, 0],transform=proj, cmap = cmaps.spread_15lev,
                 cbar_kwargs={'ticks': [80, 320, 550, 780],
                            "shrink":0.34, "aspect":10, 'label':'mm/y'})
f1_11 = rxa.plot(ax=ax[3, 1],transform=proj, cmap = cmaps.spread_15lev,
                cbar_kwargs={'ticks': [40, 120, 200, 280],
                            "shrink":0.34, "aspect":10, 'label':'mm'})
f1_12 = sdii.plot(ax=ax[3, 2],transform=proj, cmap = cmaps.ncview_default_r,
                 cbar_kwargs={'ticks': [11, 19, 27, 35],
                            "shrink":0.34, "aspect":10, 'label':''})
f1_13 = spr.plot(ax=ax[4, 0],
                 cbar_kwargs={'ticks': [-3, -1, 1, 3],
                            "shrink":0.34, "aspect":10, 'label':'Zsr'})
f1_14 = sse.plot(ax=ax[4, 1],
                 cbar_kwargs={'ticks': [-400, 0, 400],
                            "shrink":0.34, "aspect":10, 'label':''})
f1_15 = sstr.plot(ax=ax[4, 2],
                 cbar_kwargs={'ticks': [-100, -50, 0, 50, 100],
                            "shrink":0.34, "aspect":10, 'label':'%'})


count=0
for t_ax in ax.reshape(-1):
    t_ax.text(0.05, 0.85, f'({plt_lab[count]})', size=15, color='black', transform=t_ax.transAxes)
    t_ax.text(0.35, 1.02, f'{plt_tit[count]}',   size=18, color='black', transform=t_ax.transAxes)
    t_ax.set(facecolor = "#f6f7f6") 
    t_ax.add_feature(shape_feature, facecolor="None")
    t_ax.set_yticks([16.3, 18.5, 20.7, 22.9], crs=proj)
    t_ax.yaxis.set_major_formatter(lat_formatter)
    # t_ax.yaxis.set_minor_locator(MultipleLocator(0.1))
    t_ax.set_xticks([73.1, 76.6, 80.1, 83.6], minor=False, crs=proj)
    t_ax.xaxis.set_major_formatter(lon_formatter)
    # t_ax.xaxis.set_minor_locator(MultipleLocator(0.1))
    t_ax.gridlines(linewidth=1, color='gray', alpha=0.25, linestyle='--')
    
    t_ax.set_xlabel('')
    t_ax.set_ylabel('')
    t_ax.set_title("") 
    
    if count in range(12):
         t_ax.set_xticklabels("") 
    if count % 3!=0:
        t_ax.set_ylabel("")
        t_ax.set_yticklabels("")
        
            
    count+=1