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linted

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This commit is contained in:
mcguirepr89
2022-05-28 09:52:39 -04:00
parent ecd367b22c
commit 8408e7dfdf
1 changed files with 31 additions and 28 deletions
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scripts/plotly_streamlit.py
+31 -28
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@@ -39,7 +39,6 @@ st.markdown("""
""", unsafe_allow_html=True)
# @st.cache(hash_funcs={Connection: id})
@st.cache(allow_output_mutation=True)
def get_connection(path: str):
@@ -57,19 +56,19 @@ df2 = df.copy()
df2['DateTime'] = pd.to_datetime(df2['Date'] + " " + df2['Time'])
df2 = df2.set_index('DateTime')
daily = st.sidebar.checkbox('Single Day View', help= 'Select if you want single day view, unselect for multi-day views')
daily = st.sidebar.checkbox('Single Day View', help='Select if you want single day view, unselect for multi-day views')
if daily:
# Date as slider
# Date as slider
Start_Date = pd.to_datetime(df2.index.min()).date()
End_Date = pd.to_datetime(df2.index.max()).date()
# cols1, cols2 = st.columns((1, 1))
end_date = st.sidebar.slider('Date to View',
min_value = Start_Date,
max_value = End_Date,
value=(End_Date),
help= 'Select date for single day view'
)
min_value=Start_Date,
max_value=End_Date,
value=(End_Date),
help='Select date for single day view'
)
start_date = end_date
else:
Start_Date = pd.to_datetime(df2.index.min()).date()
@@ -77,11 +76,11 @@ else:
# cols1, cols2 = st.columns((1, 1))
start_date, end_date = st.sidebar.slider('Date Range',
min_value = Start_Date-timedelta(days=1),
max_value = End_Date,
value=(Start_Date, End_Date),
help= 'Select start and end date, if same date get a clockplot for a single day'
)
min_value=Start_Date - timedelta(days=1),
max_value=End_Date,
value=(Start_Date, End_Date),
help='Select start and end date, if same date get a clockplot for a single day'
)
# start_date, end_date = cols1.date_input(
# "Date Input for Analysis - select Range for single specie analysis, select single date for daily view",
@@ -92,12 +91,14 @@ else:
# start_date = datetime(2022 ,5 ,17).date()
# end_date = datetime(2022 ,5 ,17).date()
@st.cache()
def date_filter(df, start_date, end_date):
filt = (df2.index >= pd.Timestamp(start_date)) & (df2.index <= pd.Timestamp(end_date + timedelta(days=1)))
df = df[filt]
return(df)
df2 = date_filter(df2, start_date, end_date)
st.write('<style>div.row-widget.stRadio > div{flex-direction:row;justify-content: left;} </style>',
@@ -111,7 +112,7 @@ st.write('<style>div.st-bf{flex-direction:column;} div.st-ag{font-weight:bold;pa
if start_date == end_date:
resample_sel = st.sidebar.radio(
"Resample Resolution",
('Raw', '15 minutes', 'Hourly'), index=1, help= 'Select resolution for single day - larger times run faster' )
('Raw', '15 minutes', 'Hourly'), index=1, help='Select resolution for single day - larger times run faster')
resample_times = {'Raw': 'Raw',
'1 minute': '1min',
@@ -123,7 +124,7 @@ if start_date == end_date:
else:
resample_sel = st.sidebar.radio(
"Resample Resolution",
('Raw', '15 minutes', 'Hourly', 'DAILY'), index=1, help= 'Select resolution for species - DAILY provides time series')
('Raw', '15 minutes', 'Hourly', 'DAILY'), index=1, help='Select resolution for species - DAILY provides time series')
resample_times = {'Raw': 'Raw',
'1 minute': '1min',
@@ -133,6 +134,7 @@ else:
}
resample_time = resample_times[resample_sel]
@st.cache()
def time_resample(df, resample_time):
if resample_time == 'Raw':
@@ -142,6 +144,8 @@ def time_resample(df, resample_time):
df_resample = df.resample(resample_time)['Com_Name'].aggregate('unique').explode()
return(df_resample)
top_bird = df2['Com_Name'].mode()[0]
df5 = time_resample(df2, resample_time)
@@ -169,10 +173,10 @@ font_size = 15
if daily == False:
specie = st.selectbox(
'Which bird would you like to explore for the dates '
+ str(start_date) + ' to ' + str(end_date) + '?',
'Which bird would you like to explore for the dates '
+ str(start_date) + ' to ' + str(end_date) + '?',
species,
index = species.index(top_bird))
index=species.index(top_bird))
filt = df2['Com_Name'] == specie
@@ -191,7 +195,7 @@ if daily == False:
'{:.2f}%'.format(max(df2[df2['Com_Name'] == specie]['Confidence']) * 100)) +
' ' + ' Median:' + str(
'{:.2f}%'.format(np.median(df2[df2['Com_Name'] == specie]['Confidence']) * 100))
)
)
)
fig.layout.annotations[1].update(x=0.7, y=0.25, font_size=15)
@@ -245,9 +249,8 @@ if daily == False:
else:
fig = st.container()
fig = make_subplots(
rows=1, cols =1)
rows=1, cols=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>',
# '<b>Daily ' + specie+ ' Detections on 15 minute intervals </b>'),
@@ -258,9 +261,9 @@ if daily == False:
# )
# fig.add_trace(go.Bar(y=top_N_species.index, x=top_N_species, orientation='h'), row=1,col=1)
df4=df2['Com_Name'][df2['Com_Name']==specie].resample('15min').count()
df4.index=[df4.index.date, df4.index.time]
day_hour_freq=df4.unstack().fillna(0)
df4 = df2['Com_Name'][df2['Com_Name'] == specie].resample('15min').count()
df4.index = [df4.index.date, df4.index.time]
day_hour_freq = df4.unstack().fillna(0)
fig_x = [d.strftime('%d-%m-%Y') for d in day_hour_freq.index.tolist()]
fig_y = [h.strftime('%H:%M') for h in day_hour_freq.columns.tolist()]
@@ -270,9 +273,9 @@ if daily == False:
# fig.update_layout(
# margin=dict(l=0, r=0, t=50, b=0),
# yaxis={'categoryorder':'total ascending'})
color_pals= px.colors.named_colorscales()
color_pals = px.colors.named_colorscales()
selected_pal = st.sidebar.selectbox('Select Color Pallet for Daily Detections', color_pals)
fig.add_trace(go.Heatmap(x=fig_x,y=fig_y,z=fig_z, autocolorscale = False, colorscale = selected_pal), row=1, col=1)
fig.add_trace(go.Heatmap(x=fig_x, y=fig_y, z=fig_z, autocolorscale=False, colorscale=selected_pal), row=1, col=1)
else:
fig = make_subplots(
@@ -329,9 +332,9 @@ else:
st.plotly_chart(fig, use_container_width=True) # , config=config)
# cols3,cols4=st.columns((1,1))
#
#
# 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_bytes = audio_file.read()
# cols4.audio(audio_bytes, format='audio/mp3')