single URL installation -- 1 custom URL

2022-03-14 09:58:19 -04:00
parent 98d7ee2b08
commit 3f5c667fa1
7 changed files with 173 additions and 133 deletions
@@ -0,0 +1,121 @@
+#!/home/pi/BirdNET-Pi/birdnet/bin/python3
+import streamlit as st
+import pandas as pd
+import plotly.express as px
+import numpy as np
+import plotly.graph_objects as go
+from plotly.subplots import make_subplots
+from datetime import timedelta, datetime
+
+@st.cache()
+def load_data():
+    df1 = pd.read_csv('/home/pi/BirdNET-Pi/BirdDB.txt', sep=';')
+    return df1
+
+
+# Read in the cereal data
+df = load_data()
+df2=df.copy()
+df2['DateTime']=pd.to_datetime(df2['Date'] + " " + df2['Time'])
+df2=df2.set_index('DateTime')
+
+# Filter on date range
+# Date as calendars
+#Start_Date1 = pd.to_datetime(st.sidebar.date_input('Which date do you want to start?', value = df2.index.min()))
+#End_Date1 =   pd.to_datetime(st.sidebar.date_input('Which date do you want to end?',  value = df2.index.max()))
+# Date as slider
+Start_Date = pd.to_datetime(df2.index.min())
+End_Date =   pd.to_datetime(df2.index.max())
+Date_Slider = st.sidebar.slider('Date Range',
+                                value=(Start_Date.to_pydatetime(),
+                                       End_Date.to_pydatetime())                                       
+                                )
+filt = (df2.index >= Date_Slider[0]) &  (df2.index <= Date_Slider[1]+timedelta(days=1))
+df2 = df2[filt]
+
+#Create species count for selected date range
+
+Specie_Count=df2['Com_Name'].value_counts()
+
+#Create species treemap
+
+# Create Hourly Crosstab
+hourly=pd.crosstab(df2['Com_Name'],df2.index.hour)
+
+# Filter on species
+species = list(hourly.index)
+
+top_N = st.sidebar.select_slider(
+    'Select Number of Birds to Show',
+    list(range(1,len(Specie_Count))),
+    value=(10))
+
+top_N_species = (df2['Com_Name'].value_counts()[:top_N])
+
+
+specie = st.sidebar.selectbox('Which bird would you like to explore?', species, index=species.index(list(top_N_species.index)[0]))
+
+
+font_size=15
+
+
+#specie filter
+filt=df2['Com_Name']==specie
+
+df_counts=df2[filt].resample('D').count()
+
+fig = make_subplots(
+                    rows=2, cols =2,
+                    specs= [[{"type":"xy","rowspan":2}, {"type":"polar"}], [None, {"type":"xy"}]],
+                    subplot_titles=('<b>Species in Date Range</b>',
+                                    '<b>'+specie+'</b>'
+                                    '<br>Total Detections:'+str('{:,}'.format(sum(df_counts.Time)))+
+                                    '<br>''Max Confidence:'+str('{:.2f}%'.format(max(df2[df2['Com_Name']==specie]['Confidence'])*100))+
+                                    '<br>''Median Confidence:'+str('{:.2f}%'.format(np.median(df2[df2['Com_Name']==specie]['Confidence'])*100))
+                                    
+                                    )
+                    )
+# fig.layout.height=900
+# fig.layout.width=1500
+
+#Plot seen species for selected date range and number of species
+fig.add_trace(go.Bar(y=top_N_species.index, x=top_N_species, orientation='h'), row=1,col=1)
+
+fig.update_layout(
+    margin=dict(l=0, r=0, t=50, b=0),
+    yaxis={'categoryorder':'total ascending'})
+# Set 360 degrees, 24 hours for polar plot
+theta = np.linspace(0.0, 360, 24, endpoint=False)
+
+fig.add_trace(go.Barpolar(r = hourly.loc[specie], theta=theta), row=1, col=2)
+
+fig.update_layout(
+    autosize=True,
+    width = 1000,
+    height = 750,
+    showlegend=False,
+    polar = dict(
+        radialaxis = dict(
+            tickfont_size = font_size,
+            showticklabels = False),
+        angularaxis = dict(
+            tickfont_size= font_size,
+            rotation = -90,
+            direction = 'clockwise',
+            tickmode='array',
+            tickvals=[0,45,90,135,180,225,270,315],
+            ticktext=['12am','3am', '6am','9am','12pm','3pm', '6pm','9pm'],
+            hoverformat = ""#"%{theta}: <br>Popularity: %{percent} </br> %{r}"
+        ),
+        ),
+    )
+
+fig.layout.annotations[1].update(x=0.8,y=0.4, font_size=25)
+
+x=df_counts.index
+y=df_counts['Com_Name']
+
+fig.add_trace(go.Bar(x=df_counts.index,y=df_counts['Time']), row=2, col=2)
+
+container=st.container()
+container.plotly_chart(fig, use_container_width=True)