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fixed timing and added some css

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This commit is contained in:
mcguirepr89
2022-03-17 13:55:18 -04:00
parent ba87759d7d
commit 3b71c59bdb
1 changed files with 14 additions and 10 deletions
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scripts/plotly_streamlit.py
+14 -10
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@@ -1,7 +1,6 @@
#!/home/pi/BirdNET-Pi/birdnet/bin/python3 #!/home/pi/BirdNET-Pi/birdnet/bin/python3
import streamlit as st import streamlit as st
import pandas as pd import pandas as pd
import plotly.express as px
import numpy as np import numpy as np
import plotly.graph_objects as go import plotly.graph_objects as go
from plotly.subplots import make_subplots from plotly.subplots import make_subplots
@@ -40,7 +39,9 @@ Specie_Count=df2['Com_Name'].value_counts()
#Create species treemap #Create species treemap
# Create Hourly Crosstab # Create Hourly Crosstab
hourly=pd.crosstab(df2['Com_Name'],df2.index.hour)
hourly=pd.crosstab(df2['Com_Name'],df2.index.hour, dropna=False)
# Filter on species # Filter on species
species = list(hourly.index) species = list(hourly.index)
@@ -48,7 +49,7 @@ species = list(hourly.index)
top_N = st.sidebar.select_slider( top_N = st.sidebar.select_slider(
'Select Number of Birds to Show', 'Select Number of Birds to Show',
list(range(1,len(Specie_Count))), list(range(1,len(Specie_Count))),
value=(10)) value=min(10,len(Specie_Count)-1))
top_N_species = (df2['Com_Name'].value_counts()[:top_N]) top_N_species = (df2['Com_Name'].value_counts()[:top_N])
@@ -67,11 +68,11 @@ df_counts=df2[filt].resample('D').count()
fig = make_subplots( fig = make_subplots(
rows=2, cols =2, rows=2, cols =2,
specs= [[{"type":"xy","rowspan":2}, {"type":"polar"}], [None, {"type":"xy"}]], specs= [[{"type":"xy","rowspan":2}, {"type":"polar"}], [None, {"type":"xy"}]],
subplot_titles=('<b>Species in Date Range</b>', subplot_titles=('<b style="font-size:x-large;">Species in Date Range</b>',
'<b>'+specie+'</b>' '<b style="font-size:large;">'+specie+'</b><br>'
'<br>Total Detections:'+str('{:,}'.format(sum(df_counts.Time)))+ '<span style="font-size:medium;">Total Detections:'+str('{:,}'.format(sum(df_counts.Time)))+'<br>'
'<br>''Max Confidence:'+str('{:.2f}%'.format(max(df2[df2['Com_Name']==specie]['Confidence'])*100))+ 'Max Confidence:'+str('{:.2f}%'.format(max(df2[df2['Com_Name']==specie]['Confidence'])*100))+'<br>'
'<br>''Median Confidence:'+str('{:.2f}%'.format(np.median(df2[df2['Com_Name']==specie]['Confidence'])*100)) 'Median Confidence:'+str('{:.2f}%'.format(np.median(df2[df2['Com_Name']==specie]['Confidence'])*100))+'</span>'
) )
) )
@@ -87,7 +88,10 @@ fig.update_layout(
# Set 360 degrees, 24 hours for polar plot # Set 360 degrees, 24 hours for polar plot
theta = np.linspace(0.0, 360, 24, endpoint=False) theta = np.linspace(0.0, 360, 24, endpoint=False)
fig.add_trace(go.Barpolar(r = hourly.loc[specie], theta=theta), row=1, col=2) d=pd.DataFrame(np.zeros((23,1))).squeeze()
radius = hourly.loc[specie]
radius=(d+radius).fillna(0)
fig.add_trace(go.Barpolar(r = radius, theta=theta), row=1, col=2)
fig.update_layout( fig.update_layout(
autosize=True, autosize=True,
@@ -110,7 +114,7 @@ fig.update_layout(
), ),
) )
fig.layout.annotations[1].update(x=0.8,y=0.4, font_size=25) fig.layout.annotations[1].update(x=0.775,y=0.4, font_size=25)
x=df_counts.index x=df_counts.index
y=df_counts['Com_Name'] y=df_counts['Com_Name']