FranciscoLozDataScience commited on
Commit
be63294
·
1 Parent(s): 88cd75b

fix some labels and plot

Browse files
Files changed (1) hide show
  1. app.py +3 -3
app.py CHANGED
@@ -14,7 +14,7 @@ def filter_map(uhi, longitude, latitude):
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  This function generates a map based on uhi prediction
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  '''
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  #set up custom data
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- data = [uhi, longitude, latitude]
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  # Create the plot
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  fig = go.Figure(go.Scattermapbox(
@@ -150,7 +150,7 @@ def load_interface():
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  # set inputs and outputs for the model
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  longitude = gr.Number(label="Longitude", precision=5, info="The Longitude of the location")
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  latitude = gr.Number(label="Latitude", precision=5, info="The Latitude of the location")
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- m50_NPCRI = gr.Number(label="50m NPCRI", precision=5, info="The average Normalized Difference Vegetation Index in a 50m Buffer Zone")
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  m100_Ground_Elevation = gr.Number(label="100m Ground Elevation", precision=5, info="The average Ground Elevation in a 100m Buffer Zone")
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  avg_wind_speed = gr.Number(label="Avg Wind Speed [m/s]", precision=5, info="The average Wind Speed at the location")
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  wind_direction = gr.Number(label="Wind Direction [degrees]", precision=5, info="The average Wind Direction at the location")
@@ -171,7 +171,7 @@ def load_interface():
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  m300_NDBI = gr.Number(label="300m NDBI", precision=5, info="The average Normalized Difference Built-up Index in a 300m Buffer Zone")
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  m300_Building_Density = gr.Number(label="300m Building Density", precision=5, info="The average Building Density in a 300m Buffer Zone")
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  solar_flux = gr.Number(label="Solar Flux [W/m^2]", precision=5, info="The average Solar Flux at the location")
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- inputs = [longitude, latitude, m50_NPCRI, m100_Ground_Elevation, avg_wind_speed, wind_direction,
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  traffic_volume, m150_Ground_Elevation, relative_humidity, m150_NDVI,
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  m150_NDBI, m300_SI, m300_NPCRI, m300_Coastal_Aerosol, m300_Total_Building_Area_m2,
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  m300_Building_Construction_Year, m300_Ground_Elevation, m300_Building_Height, m300_Building_Count,
 
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  This function generates a map based on uhi prediction
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  '''
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  #set up custom data
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+ data = [[uhi, longitude, latitude]]
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  # Create the plot
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  fig = go.Figure(go.Scattermapbox(
 
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  # set inputs and outputs for the model
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  longitude = gr.Number(label="Longitude", precision=5, info="The Longitude of the location")
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  latitude = gr.Number(label="Latitude", precision=5, info="The Latitude of the location")
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+ m150_NPCRI = gr.Number(label="150m NPCRI", precision=5, info="The average Normalized Difference Vegetation Index in a 150m Buffer Zone")
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  m100_Ground_Elevation = gr.Number(label="100m Ground Elevation", precision=5, info="The average Ground Elevation in a 100m Buffer Zone")
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  avg_wind_speed = gr.Number(label="Avg Wind Speed [m/s]", precision=5, info="The average Wind Speed at the location")
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  wind_direction = gr.Number(label="Wind Direction [degrees]", precision=5, info="The average Wind Direction at the location")
 
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  m300_NDBI = gr.Number(label="300m NDBI", precision=5, info="The average Normalized Difference Built-up Index in a 300m Buffer Zone")
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  m300_Building_Density = gr.Number(label="300m Building Density", precision=5, info="The average Building Density in a 300m Buffer Zone")
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  solar_flux = gr.Number(label="Solar Flux [W/m^2]", precision=5, info="The average Solar Flux at the location")
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+ inputs = [longitude, latitude, m150_NPCRI, m100_Ground_Elevation, avg_wind_speed, wind_direction,
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  traffic_volume, m150_Ground_Elevation, relative_humidity, m150_NDVI,
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  m150_NDBI, m300_SI, m300_NPCRI, m300_Coastal_Aerosol, m300_Total_Building_Area_m2,
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  m300_Building_Construction_Year, m300_Ground_Elevation, m300_Building_Height, m300_Building_Count,