Replace geonet_gradient_selected.py

geonet_gradient_selected.py

@@ -11,14 +11,15 @@ from collections import OrderedDict
 import matplotlib as mpl
 #shapefile = "D:\\Mes Donnees\\Land Matrix\\Shapefile\\"
 from mpl_toolkits.axes_grid1 import make_axes_locatable
-from geopandas import GeoDataFrame
 from descartes import PolygonPatch
+from scalebar import north_arrow
+import os
 
 #dataset_name = 'mines'
 #dataset_name = "agriculture+biofuel"
 dataset_name = "global"
 
-selected_iso = "USA"
+selected_iso = "BRA"
 
 direction=['in','out','both']
 
@@ -28,11 +29,22 @@ degrees = ['in', 'out','inout']
 
 degree = degrees[2]
 
-path = ".\\data_net\\net_%s_surf_inOperation.ncol" % dataset_name
+#path = ".\\data_net\\net_%s_surf_inOperation.ncol" % dataset_name
+
+
+#path_d = ".\\data_net\\ids_to_countries_%s_inOperation.csv" % dataset_name
+
+os.chdir("D:\\Mes Donnees\\Land Matrix\\_LURKER\\net\\")
+
+degrees = ['in', 'out','inout','inout_num']
+
+path_iso = "ISO country.xlsx"
+
+path_d ="ids_to_countries_global_07072021_inOperation.csv"
+path = "net_global_07072021_inOperation.ncol"
 
 graph = nx.read_edgelist(path, delimiter=';', create_using=nx.DiGraph(), nodetype=int, data=(('weight', int),))
 
-path_d = ".\\data_net\\ids_to_countries_%s_inOperation.csv" % dataset_name
 
 names_dict = {}
 coord = {}
@@ -40,7 +52,9 @@ lat = []
 long = []
 
 
-fc = open(".\\data_net\\countries_to_coord_allTransnational.csv", 'r')
+#fc = open(".\\data_net\\countries_to_coord_allTransnational.csv", 'r')
+fc = open("countries_to_coord_allTransnational.csv", 'r')
+
 for line in fc:
     vals=line.split(';')
     coord[vals[0]] = (float(vals[1]), float(vals[2].strip()))
@@ -83,8 +97,8 @@ for id in names_dict:
         pos[int(id)]=(coord[names_dict[id]][1],coord[names_dict[id]][0])
 
 
-path_iso = ".\\data_net\\ISO country.xlsx"
-iso =  pd.read_excel(path_iso, index_col=0, sep=';')
+path_iso = "ISO country.xlsx"
+iso =  pd.read_excel(path_iso, index_col=0)
 
 iso_dict = {}
 inv_iso_dict= {}
@@ -131,6 +145,9 @@ ax.coastlines()
 #ax.set_extent([-90, -180, 90, 180])
 ax.set_global()
 
+north_arrow(ax, (0.1,0.2), 500)
+
+
 #backround image
 #si = ax.stock_img()
 #si.set_zorder(-1)
@@ -285,7 +302,9 @@ pc.set_array(norm(list(score.values())))
 #cax = divider.append_axes("right", size="5%", pad=0.05)
 
 #plt.colorbar(pc,fraction=0.046, pad=0.05)
-plt.colorbar(pc,fraction=0.023, pad=0.05)
+cb = plt.colorbar(pc,fraction=0.023, pad=0.05)
+cb.ax.tick_params(labelsize=20)
+
 
 #ax.set_axis_off()
 plt.tight_layout()
@@ -309,7 +328,7 @@ nx.draw_networkx(graph, ax=ax,
 """
 
 
-plt.savefig("map_inout_%s_%s.pdf" % (dataset_name,selected_iso), format="pdf", dpi=300)
+#plt.savefig("map_inout_%s_%s_test.pdf" % (dataset_name,selected_iso), format="pdf", dpi=300)
 
 
-#plt.show()
+plt.show()