diff --git a/main.py b/main.py
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+
+import time
+import pandas as pd
+import knime.extension as knext
+import numpy as np
+import logging
+import plotly.graph_objects as go
+import pycountry
+from geopy.geocoders import Nominatim
+LOGGER = logging.getLogger(__name__)
+
+
+category = knext.category("/community", "Supply_chain_visualization_node", "Supplychain visualization node", "Supplychain visualization node for KNIME",icon="icons/icon.png")
+@knext.node(name="Supplychain visualization node", node_type=knext.NodeType.LEARNER, category=category, icon_path="icons/icon.png")
+@knext.input_table(name="Input Data 1",description="Input data")
+@knext.output_table(name="Output Data", description="Output data")
+@knext.output_view(name="Output view", description="Output view")
+
+class TemplateNode:
+ def configure(self, configure_context, input_schema_1):
+ return input_schema_1
+
+ def execute(self, exec_context, input_1):
+ df = input_1.to_pandas() # Transform the input table to some processable format (pandas or pyarrow)
+ if df.empty:
+ LOGGER.warning("Input table is empty.")
+ return None, None
+
+ df = df.rename(columns={'Country (from)': 'C_From', 'Country (to)': 'C_To', 'Value (thousands of €)' : 'Value' })
+
+ countries = pd.concat([df['C_From'], df['C_To']], axis=0, ignore_index=True)
+ countries = pd.DataFrame(countries)
+ countries.columns = ['Name']
+
+ countries.drop_duplicates(inplace=True)
+
+
+ # Apply function to DataFrame to get latitude and longitude for each country
+ countries['Latitude'], countries['Longitude'] = zip(*countries['Name'].apply(get_lat_long))
+
+ countries['Country_Code'] = countries['Name'].apply(get_country_code)
+
+ country_code_array = np.array(countries['Country_Code'])
+ country_name_array = np.array(countries['Name'])
+
+
+ country_colour=[]
+ broj_drzava = len(country_code_array)
+ for i in range(0,broj_drzava):
+ country_colour.append(i)
+
+
+
+
+ countries = countries.set_index('Name')
+ df['Value_Normalized']=round(df['Value']*10/max(df['Value']))+1
+
+
+
+ import plotly.graph_objects as go
+
+ # Define your data for the choropleth map
+ data = [
+ go.Choropleth(
+ locations=country_code_array, # Country codes or names
+ z=country_colour, # Values for coloring the map
+ text=country_name_array, # Country names
+ # colorscale='Blues', # Color scale for the map
+ autocolorscale=False, # Disable automatic scaling of colors
+ showscale=False, # Hide the color scale legend
+ # geojson='https://raw.githubusercontent.com/python-visualization/folium/master/examples/data/world-countries.json' # GeoJSON file URL
+ )
+ ]
+
+ # Define the layout of the figure
+ layout = go.Layout(
+ title='Supplychain visualization',
+ geo=dict(
+ showframe=True, # Show the frame around the map
+ showcoastlines=True, # Show coastlines
+ projection_type='natural earth' # Set the projection type
+ )
+ )
+
+ # Create the figure
+ fig = go.Figure(data=data, layout=layout)
+
+ # Display the figure
+ # fig.show()
+
+
+ for index, row in df.iterrows():
+ c_from = row['C_From']
+ c_to = row['C_To']
+ c_th = row['Value_Normalized']
+
+ # Introduce a delay between geocoding requests
+ time.sleep(0.2) # Wait for a second before each geocoding request
+
+ nacrtaj_arrow(fig, countries, c_from, c_to, c_th)
+
+ fig.update_layout(
+ # width=900, height=650,
+ showlegend = False,
+ geo = dict(
+ scope = 'world',
+
+ # landcolor = 'rgb(217, 217, 217)'
+ )
+ )
+
+
+
+
+
+ # x = input_1_pandas.to_html()
+
+ x = countries.to_html()
+
+ # return knext.Table.from_pandas(input_1_pandas), knext.view(input_1_pandas) ### Tutorial step 13: Uncomment
+ # return knext.Table.from_pandas(df), knext.view_html(x) ### Tutorial step 13: Uncomment
+ return knext.Table.from_pandas(df), knext.view(fig) ### Tutorial step 13: Uncomment
+
+
+
+# Define function to get latitude and longitude for a country
+
+def _code(country_name):
+ country = pycountry.countries.get(name=country_name.upper())
+ if country:
+ return country.alpha_3
+ else:
+ LOGGER.warning(f"Country code not found for {country_name}. Skipping this country.")
+ return None
+
+
+
+# Define function to get latitude and longitude for a country
+# Modify get_lat_long function
+def get_lat_long(country):
+ geolocator = Nominatim(user_agent="my_app")
+ try:
+ location = geolocator.geocode(country, timeout=10)
+ if location:
+ return (location.latitude, location.longitude)
+ else:
+ LOGGER.warning(f"Location not found for country: {country}")
+ return (None, None)
+ except GeocoderTimedOut:
+ LOGGER.warning(f"Geocoding request timed out for country: {country}")
+ return (None, None)
+
+
+# Modify get_country_code function
+def get_country_code(country_name):
+ country = pycountry.countries.get(name=country_name.upper())
+ if country:
+ return country.alpha_3
+ else:
+ LOGGER.warning(f"Country code not found for: {country_name}. Skipping this country.")
+ return None
+
+
+def nacrtaj_arrow(fig, countries, c1, c2, thickness):
+ fig.add_trace(go.Scattergeo(
+ lat = [countries.loc[c1][0], countries.loc[c2][0]],
+ lon = [countries.loc[c1][1], countries.loc[c2][1]],
+ mode = 'lines',
+
+ line = dict(width = thickness, color = 'blue'),
+ ))
+
+ #Workaround to get the arrow at the end of an edge AB
+
+ l = 1.1 # the arrow length
+ widh = 0.035 #2*widh is the width of the arrow base as triangle
+
+ B = np.array([countries.loc[c2][1], countries.loc[c2][0]])
+ A = np.array([countries.loc[c1][1], countries.loc[c1][0]])
+ # A = np.array([locations['lon'][4], locations['lat'][4]])
+ # B = np.array([locations['lon'][0], locations['lat'][0]])
+ v = B-A
+ w = v/np.linalg.norm(v)
+ # u = np.array([-v[1], v[0]]) #u orthogonal on w
+ u = np.array([-w[1], w[0]])*10
+
+ P = B-l*w
+ S = P - widh*u
+ T = P + widh*u
+
+ fig.add_trace(go.Scattergeo(lon = [S[0], T[0], B[0], S[0]],
+ lat =[S[1], T[1], B[1], S[1]],
+ mode='lines',
+ fill='toself',
+ fillcolor='blue',
+ line_color='blue'))
+ # #------Display your text at the middle of the segment AB
+ # fig.add_trace(go.Scattergeo(lon =[0.5*(A+B)[0]], lat = [0.5*(A+B)[1]], mode='text', text='Your text'))
+