Update GOES_temp_nuvem.py

GOES_temp_nuvem.py

@@ -111,7 +111,14 @@ def read_gzbin(f_name, threshold):
 # Plote a temperatura negativa no mapa
 plt.imshow(temperatura_negativa,  cmap='BuPu_r', origin='lower', 
            transform = ccrs.PlateCarree(), vmin=limite_negativo, vmax= 0)
-
+ #X, Y = np.meshgrid(df.columns, df.index)
+  #  Z = df.values
+#    img = ax.pcolormesh(
+   #     X, Y, Z, 
+  #      vmin = 0, 
+     #   vmax = 5, 
+     #   cmap = 'rainbow'
+     #   ) 
 # Adicione uma barra de cores
 plt.colorbar(shrink=0.7, label='Temperatura (°C)')
 
@@ -120,4 +127,4 @@ def read_gzbin(f_name, threshold):
 plt.tight_layout()
 
 # Mostra o mapa
-plt.show()
+plt.show()

Temp_Binary_Data_GOES.py

@@ -0,0 +1,145 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Tue Sep 19 08:57:00 2023
+
+@author: Anderson Bilibio
+"""
+
+import matplotlib.pyplot as plt
+import cartopy.crs as ccrs
+import cartopy.feature as cfeature
+import numpy as np
+# import xarray as xr
+# from cartopy.mpl.gridliner import LATITUDE_FORMATTER, LONGITUDE_FORMATTER
+# import matplotlib.ticker as mticker
+# from matplotlib import ticker, cm
+# import time 
+# import cartopy.io.img_tiles as cimgt
+# import matplotlib.colors as mcolors
+# from mpl_toolkits.basemap import Basemap 
+
+
+# Carregue seus dados binários aqui (depende do formato)
+def read_gzbin(f_name, threshold):
+    # import necessary libraries
+    import numpy as np
+    import gzip
+    from datetime import datetime
+
+    # extract date and time from file name
+    date_str = f_name[-15:-3]
+    date_obj = datetime.strptime(date_str, '%Y%m%d%H%M')#%S
+
+    # read binary data from gzip-compressed file
+    with gzip.open(f_name, 'rb') as f:
+        uncompressed_data = f.read()
+        dados_binarios = np.frombuffer(uncompressed_data, dtype=np.int16)
+
+
+        # reshape binary data into a 2D numpy array
+        imageSize = [1800,1800]
+        dados_binarios = dados_binarios.reshape(imageSize)
+
+
+        # Define x and y positions
+        dlon=np.arange(dados_binarios.shape[1]) * 0.04 - 100
+        dlat=np.arange(dados_binarios.shape[0]) * 0.04 - 50
+
+
+        # return the 2D numpy array, dlon, dlat, and date_obj
+        return dados_binarios, dlon, dlat, date_obj
+
+
+caminho = 'C:/2023/Beckup_note/ANDERSON/PCI_D_inpe_2023\
+/mapas_temp_nuvem_python/03-06-2005-goes12_ch4/'                              
+
+# f_name='gcr.050602.0200_0200g.ch4'
+nome = 'S10216956_200506020330.gz'
+
+f_name = caminho+nome
+
+saida = caminho 
+
+#Deletes values higher than -65 celcius degress
+threshold = -40
+dados_temperatura, longitude, latitude, date_obj = read_gzbin(f_name, threshold)
+###============================================================================
+
+# Etapa 2: Identifique as regiões de convecção (substitua com seus próprios critérios)
+temperatura_negativa = np.where(dados_temperatura > -40, np.nan, dados_temperatura)
+limite_temperatura = -80  # Limite de temperatura para identificar a convecção
+regioes_conveccao = np.where(temperatura_negativa < limite_temperatura, np.nan, temperatura_negativa)
+
+# Etapa 4: Plote o mapa da América Latina com destaque nas regiões de convecção
+fig = plt.figure(figsize=(10, 8))
+ax = plt.axes(projection=ccrs.PlateCarree())
+
+
+# Plote um mapa da América Latina (substitua com seus próprios dados geoespaciais)
+# Use 'latitude' e 'longitude' para definir os limites geográficos do mapa.
+ax.set_extent([-90, -20, -40, 20], ccrs.PlateCarree())
+
+#? Adiciona os cortornos#===========================================
+ax.add_feature(cfeature.COASTLINE)
+ax.add_feature(cfeature.BORDERS)
+
+states = cfeature.NaturalEarthFeature(category='cultural', 
+                                      name='admin_1_states_provinces_lines', 
+                                      scale='50m', 
+                                      facecolor='none')
+
+ax.add_feature(states, edgecolor='black', linestyle=':', linewidth=1)
+
+#? construindo a grade do mapa#===========================================
+g1 = ax.gridlines(crs=ccrs.PlateCarree(), 
+                  draw_labels=True, 
+                  linestyle='--', 
+                  linewidth=1, 
+                  color='black',
+                  )
+
+#? Utilizar como base mapa quando nao for usar do google
+ax.stock_img() 
+
+
+# Mostre o mapa
+plt.imshow(temperatura_negativa/100.-273.13, cmap='magma',  
+           origin='lower', 
+           extent=[longitude.min(), longitude.max(), 
+                   latitude.min(), latitude.max()], 
+           transform = ccrs.PlateCarree()
+           )
+
+
+plt.colorbar(label='Temperatura (°C) -' +' '+ str(date_obj), shrink=0.80)
+
+# Ajusta o espaçamento entre os subplots
+plt.tight_layout()
+
+# Personalize o mapa (adicionando contornos de países, títulos, etc.)
+# Add a label to the plot
+plt.title('Regiões de Convecção')
+
+plt.text(-55, -44, 'Longitude ($^{\circ}$)', transform=ccrs.PlateCarree(), 
+         fontsize=12, color='black')
+
+plt.text(-97, -15, 'Latitude ($^{\circ}$)', transform=ccrs.PlateCarree(), 
+         fontsize=12, color='black', rotation=90 )
+
+plt.subplots_adjust(wspace=0.15, hspace=0.02, left=0.12, right=0.98, top=0.95, bottom=0.005)
+
+plt.text(-87, 17, '${\lambda_{H}}=$', transform=ccrs.PlateCarree(), 
+         fontsize=15, color='black')
+
+plt.text(-35, 17, '${c_{H}}=$', transform=ccrs.PlateCarree(), 
+         fontsize=15, color='black')
+
+plt.text(-35, -37, '${\phi}=$', transform=ccrs.PlateCarree(), 
+         fontsize=15, color='black')
+
+plt.text(-87, -37, '${per}=$', transform=ccrs.PlateCarree(), 
+         fontsize=15, color='black')
+
+plt.show()
+
+