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linted plotly

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This commit is contained in:
mcguirepr89
2022-06-24 09:15:59 -04:00
parent 3d991d6cab
commit 5a971cea41
1 changed files with 80 additions and 87 deletions
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scripts/plotly_streamlit.py
+28 -35
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@@ -6,13 +6,11 @@ from numpy import ma
import plotly.graph_objects as go import plotly.graph_objects as go
from plotly.subplots import make_subplots from plotly.subplots import make_subplots
import plotly.io as pio import plotly.io as pio
from datetime import timedelta, datetime from datetime import timedelta
from pathlib import Path
import sqlite3 import sqlite3
from sqlite3 import Connection from sqlite3 import Connection
import plotly.express as px import plotly.express as px
from sklearn.preprocessing import normalize from sklearn.preprocessing import normalize
import time
pio.templates.default = "plotly_white" pio.templates.default = "plotly_white"
@@ -40,7 +38,6 @@ st.markdown("""
""", unsafe_allow_html=True) """, unsafe_allow_html=True)
@st.cache(hash_funcs={Connection: id}) @st.cache(hash_funcs={Connection: id})
# @st.cache(allow_output_mutation=True) # @st.cache(allow_output_mutation=True)
def get_connection(path: str): def get_connection(path: str):
@@ -69,8 +66,7 @@ if daily:
min_value=Start_Date, min_value=Start_Date,
max_value=End_Date, max_value=End_Date,
value=(End_Date), value=(End_Date),
help= 'Select date for single day view' help='Select date for single day view')
)
start_date = end_date start_date = end_date
else: else:
Start_Date = pd.to_datetime(df2.index.min()).date() Start_Date = pd.to_datetime(df2.index.min()).date()
@@ -81,8 +77,7 @@ else:
min_value=Start_Date-timedelta(days=1), min_value=Start_Date-timedelta(days=1),
max_value=End_Date, max_value=End_Date,
value=(Start_Date, End_Date), value=(Start_Date, End_Date),
help= 'Select start and end date, if same date get a clockplot for a single day' help='Select start and end date, if same date get a clockplot for a single day')
)
# start_date, end_date = cols1.date_input( # start_date, end_date = cols1.date_input(
# "Date Input for Analysis - select Range for single specie analysis, select single date for daily view", # "Date Input for Analysis - select Range for single specie analysis, select single date for daily view",
@@ -93,12 +88,14 @@ else:
# start_date = datetime(2022 ,5 ,17).date() # start_date = datetime(2022 ,5 ,17).date()
# end_date = datetime(2022 ,5 ,17).date() # end_date = datetime(2022 ,5 ,17).date()
@st.cache() @st.cache()
def date_filter(df, start_date, end_date): def date_filter(df, start_date, end_date):
filt = (df2.index >= pd.Timestamp(start_date)) & (df2.index <= pd.Timestamp(end_date + timedelta(days=1))) filt = (df2.index >= pd.Timestamp(start_date)) & (df2.index <= pd.Timestamp(end_date + timedelta(days=1)))
df = df[filt] df = df[filt]
return(df) return(df)
df2 = date_filter(df2, start_date, end_date) df2 = date_filter(df2, start_date, end_date)
st.write('<style>div.row-widget.stRadio > div{flex-direction:row;justify-content: left;} </style>', st.write('<style>div.row-widget.stRadio > div{flex-direction:row;justify-content: left;} </style>',
@@ -134,6 +131,7 @@ else:
} }
resample_time = resample_times[resample_sel] resample_time = resample_times[resample_sel]
@st.cache() @st.cache()
def time_resample(df, resample_time): def time_resample(df, resample_time):
if resample_time == 'Raw': if resample_time == 'Raw':
@@ -143,6 +141,8 @@ def time_resample(df, resample_time):
df_resample = df.resample(resample_time)['Com_Name'].aggregate('unique').explode() df_resample = df.resample(resample_time)['Com_Name'].aggregate('unique').explode()
return(df_resample) return(df_resample)
top_bird = df2['Com_Name'].mode()[0] top_bird = df2['Com_Name'].mode()[0]
df5 = time_resample(df2, resample_time) df5 = time_resample(df2, resample_time)
@@ -168,7 +168,7 @@ top_N_species = (df5.value_counts()[:top_N])
font_size = 15 font_size = 15
if daily == False: if daily is False:
if resample_time != '1D': if resample_time != '1D':
specie = st.selectbox( specie = st.selectbox(
@@ -177,13 +177,13 @@ if daily == False:
species, species,
index=0) index=0)
# filt = df2['Com_Name'] == specie # filt = df2['Com_Name'] == specie
if specie == 'All': if specie == 'All':
df_counts = int(hourly[hourly.index == specie]['All']) df_counts = int(hourly[hourly.index == specie]['All'])
fig = make_subplots( fig = make_subplots(
rows=3, cols=2, rows=3, cols=2,
specs=[[{"type": "xy", "rowspan": 3}, {"type": "polar", "rowspan": 2}], [{"rowspan": 1}, {"rowspan": 1}], specs=[[{"type": "xy", "rowspan": 3}, {"type": "polar", "rowspan": 2}],
[{"rowspan": 1}, {"rowspan": 1}],
[None, {"type": "xy", "rowspan": 1}]], [None, {"type": "xy", "rowspan": 1}]],
subplot_titles=('<b>Top ' + str(top_N) + ' Species in Date Range ' + str(start_date) + ' to ' + str( subplot_titles=('<b>Top ' + str(top_N) + ' Species in Date Range ' + str(start_date) + ' to ' + str(
end_date) + '<br>for ' + str(resample_sel) + ' sampling interval.' + '</b>', end_date) + '<br>for ' + str(resample_sel) + ' sampling interval.' + '</b>',
@@ -232,10 +232,11 @@ if daily == False:
rotation=-90, rotation=-90,
direction='clockwise', direction='clockwise',
tickmode='array', tickmode='array',
tickvals=[0, 15, 35, 45, 60, 75, 90, 105, 120, 135, 150, 165, 180, 195, 210, 225, 240, 255, 270, tickvals=[0, 15, 35, 45, 60, 75, 90, 105, 120, 135, 150, 165, 180, 195, 210,
285, 300, 315, 330, 345], 225, 240, 255, 270, 285, 300, 315, 330, 345],
ticktext=['12am', '1am', '2am', '3am', '4am', '5am', '6am', '7am', '8am', '9am', '10am', '11am', ticktext=['12am', '1am', '2am', '3am', '4am', '5am', '6am', '7am', '8am', '9am',
'12pm', '1pm', '2pm', '3pm', '4pm', '5pm', '6pm', '7pm', '8pm', '9pm', '10pm', '11pm'], '10am', '11am', '12pm', '1pm', '2pm', '3pm', '4pm', '5pm', '6pm',
'7pm', '8pm', '9pm', '10pm', '11pm'],
hoverformat="#%{theta}: <br>Popularity: %{percent} </br> %{r}" hoverformat="#%{theta}: <br>Popularity: %{percent} </br> %{r}"
), ),
), ),
@@ -280,10 +281,11 @@ if daily == False:
rotation=-90, rotation=-90,
direction='clockwise', direction='clockwise',
tickmode='array', tickmode='array',
tickvals=[0, 15, 35, 45, 60, 75, 90, 105, 120, 135, 150, 165, 180, 195, 210, 225, 240, 255, 270, tickvals=[0, 15, 35, 45, 60, 75, 90, 105, 120, 135, 150, 165, 180, 195,
285, 300, 315, 330, 345], 210, 225, 240, 255, 270, 285, 300, 315, 330, 345],
ticktext=['12am', '1am', '2am', '3am', '4am', '5am', '6am', '7am', '8am', '9am', '10am', '11am', ticktext=['12am', '1am', '2am', '3am', '4am', '5am', '6am', '7am', '8am',
'12pm', '1pm', '2pm', '3pm', '4pm', '5pm', '6pm', '7pm', '8pm', '9pm', '10pm', '11pm'], '9am', '10am', '11am', '12pm', '1pm', '2pm', '3pm', '4pm', '5pm',
'6pm', '7pm', '8pm', '9pm', '10pm', '11pm'],
hoverformat="#%{theta}: <br>Popularity: %{percent} </br> %{r}" hoverformat="#%{theta}: <br>Popularity: %{percent} </br> %{r}"
), ),
), ),
@@ -294,15 +296,13 @@ if daily == False:
st.plotly_chart(fig, use_container_width=True) # , config=config) st.plotly_chart(fig, use_container_width=True) # , config=config)
df_counts = int(hourly[hourly.index == specie]['All']) df_counts = int(hourly[hourly.index == specie]['All'])
st.subheader('Total Detect:' + str('{:,}'.format(df_counts)) st.subheader('Total Detect:' + str('{:,}'.format(df_counts))
+ ' Confidence Max:' + str( + ' Confidence Max:' +
'{:.2f}%'.format(max(df2[df2['Com_Name'] == specie]['Confidence']) * 100)) + str('{:.2f}%'.format(max(df2[df2['Com_Name'] == specie]['Confidence']) * 100))
' ' + ' Median:' + str( + ' ' + ' Median:' +
'{:.2f}%'.format(np.median(df2[df2['Com_Name'] == specie]['Confidence']) * 100))) str('{:.2f}%'.format(np.median(df2[df2['Com_Name'] == specie]['Confidence']) * 100)))
recordings = df2[df2['Com_Name'] == specie]['File_Name'] recordings = df2[df2['Com_Name'] == specie]['File_Name']
with col2: with col2:
try: try:
recording = st.selectbox('Available recordings', recordings.sort_index(ascending=False)) recording = st.selectbox('Available recordings', recordings.sort_index(ascending=False))
@@ -311,7 +311,7 @@ if daily == False:
specie_dir = date_specie['Com_Name'].values[0].replace(" ", "_") specie_dir = date_specie['Com_Name'].values[0].replace(" ", "_")
st.image(userDir + '/BirdSongs/Extracted/By_Date/' + date_dir + '/' + specie_dir + '/' + recording + '.png') st.image(userDir + '/BirdSongs/Extracted/By_Date/' + date_dir + '/' + specie_dir + '/' + recording + '.png')
st.audio(userDir + '/BirdSongs/Extracted/By_Date/' + date_dir + '/' + specie_dir + '/' + recording) st.audio(userDir + '/BirdSongs/Extracted/By_Date/' + date_dir + '/' + specie_dir + '/' + recording)
except: except Exception:
st.title('RECORDING NOT AVAILABLE :(') st.title('RECORDING NOT AVAILABLE :(')
# try: # try:
# con = sqlite3.connect(userDir + '/BirdNET-Pi/scripts/birds.db') # con = sqlite3.connect(userDir + '/BirdNET-Pi/scripts/birds.db')
@@ -337,25 +337,20 @@ if daily == False:
# print("Database busy") # print("Database busy")
# time.sleep(2) # time.sleep(2)
else: else:
specie = st.selectbox( specie = st.selectbox('Which bird would you like to explore for the dates '
'Which bird would you like to explore for the dates '
+ str(start_date) + ' to ' + str(end_date) + '?', + str(start_date) + ' to ' + str(end_date) + '?',
species[1:], species[1:],
index=0) index=0)
# filt = df2[df2['Com_Name'] == specie] # filt = df2[df2['Com_Name'] == specie]
df_counts = int(hourly[hourly.index == specie]['All']) df_counts = int(hourly[hourly.index == specie]['All'])
fig = st.container() fig = st.container()
fig = make_subplots( fig = make_subplots(rows=1, cols=1)
rows=1, cols =1)
# specs= [[{"type":"xy","rowspan":1},{"type":"heatmap","rowspan":1}]], # specs= [[{"type":"xy","rowspan":1},{"type":"heatmap","rowspan":1}]],
# subplot_titles=('<b>Daily Top '+ str(top_N) + ' Species in Date Range '+ str(start_date) +' to '+ str(end_date) +'</b>', # subplot_titles=('<b>Daily Top '+ str(top_N) + ' Species in Date Range '+ str(start_date) +' to '+ str(end_date) +'</b>',
# '<b>Daily ' + specie+ ' Detections on 15 minute intervals </b>'), # '<b>Daily ' + specie+ ' Detections on 15 minute intervals </b>'),
# # 'Total Detect:'+str('{:,}'.format(df_counts))+ # # 'Total Detect:'+str('{:,}'.format(df_counts))+
@@ -436,9 +431,7 @@ else:
st.plotly_chart(fig, use_container_width=True) # , config=config) st.plotly_chart(fig, use_container_width=True) # , config=config)
# cols3,cols4=st.columns((1,1)) # cols3,cols4=st.columns((1,1))
#
# extract_date=Date_Slider # extract_date=Date_Slider
#
# audio_file = open('/home/*/BirdSongs/Extracted/By_Date/2022-03-22/Yellow-streaked_Greenbul/Yellow-streaked_Greenbul-77-2022-03-22-birdnet-15:04:28.mp3', 'rb') # audio_file = open('/home/*/BirdSongs/Extracted/By_Date/2022-03-22/Yellow-streaked_Greenbul/Yellow-streaked_Greenbul-77-2022-03-22-birdnet-15:04:28.mp3', 'rb')
# audio_bytes = audio_file.read() # audio_bytes = audio_file.read()
# cols4.audio(audio_bytes, format='audio/mp3') # cols4.audio(audio_bytes, format='audio/mp3')