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Fix : compatibility with plotly 6 #295 #301

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merged 7 commits into from
Mar 8, 2025
Merged

Fix : compatibility with plotly 6 #295 #301

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aebcae2
Fix for plotly 6.0.0
alexbelgium Mar 4, 2025
26557a2
Lint
alexbelgium Mar 4, 2025
1e2ee5b
Fix error "Calling int on a single element Series is deprecated"
alexbelgium Mar 5, 2025
8a4b54c
Fix daily resample
alexbelgium Mar 5, 2025
a6d0c3f
Fix daily resample
alexbelgium Mar 5, 2025
eac6ab6
Force readonly mode
alexbelgium Mar 5, 2025
121c72d
Remove cache=shared
alexbelgium Mar 8, 2025
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30 changes: 16 additions & 14 deletions scripts/plotly_streamlit.py
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Original file line number Diff line number Diff line change
Expand Up @@ -54,7 +54,8 @@

@st.cache_resource()
def get_connection(path: str):
return sqlite3.connect(path, check_same_thread=False)
uri = f"file:{path}?mode=ro&cache=shared"
return sqlite3.connect(uri, uri=True, check_same_thread=False)


def get_data(_conn: Connection):
Expand Down Expand Up @@ -254,14 +255,14 @@ def hms_to_str(t):

# 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', marker_color='seagreen'), row=1, col=1)
fig.add_trace(go.Bar(y=top_N_species.index.tolist(), x=top_N_species.values.tolist(), orientation='h', marker_color='seagreen'), 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)
theta = np.linspace(0.0, 360, 24, endpoint=False).tolist()

specie_filt = df5 == specie
df3 = df5[specie_filt]
Expand All @@ -271,7 +272,7 @@ def hms_to_str(t):
d = pd.DataFrame(np.zeros((23, 1))).squeeze()
detections = hourly.loc[specie]
detections = (d + detections).fillna(0)
fig.add_trace(go.Barpolar(r=detections, theta=theta, marker_color='seagreen'), row=1, col=2)
fig.add_trace(go.Barpolar(r=detections.tolist(), theta=theta, marker_color='seagreen'), row=1, col=2)
fig.update_layout(
autosize=False,
width=1000,
Expand Down Expand Up @@ -299,7 +300,7 @@ def hms_to_str(t):
)

daily = pd.crosstab(df5, df5.index.date, dropna=True, margins=True)
fig.add_trace(go.Bar(x=daily.columns[:-1], y=daily.loc[specie][:-1], marker_color='seagreen'), row=3, col=2)
fig.add_trace(go.Bar(x=daily.columns[:-1].tolist(), y=daily.loc[specie][:-1].tolist(), marker_color='seagreen'), row=3, col=2)
st.plotly_chart(fig, use_container_width=True) # , config=config)

else:
Expand All @@ -310,7 +311,7 @@ def hms_to_str(t):
specs=[[{"type": "polar", "rowspan": 2}], [{"rowspan": 1}], [{"type": "xy", "rowspan": 1}]]
)
# 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).tolist()

specie_filt = df5 == specie
df3 = df5[specie_filt]
Expand All @@ -320,7 +321,7 @@ def hms_to_str(t):
d = pd.DataFrame(np.zeros((23, 1))).squeeze()
detections = hourly.loc[specie]
detections = (d + detections).fillna(0)
fig.add_trace(go.Barpolar(r=detections, theta=theta, marker_color='seagreen'), row=1, col=1)
fig.add_trace(go.Barpolar(r=detections.tolist(), theta=theta, marker_color='seagreen'), row=1, col=1)
fig.update_layout(
autosize=False,
width=1000,
Expand Down Expand Up @@ -348,7 +349,7 @@ def hms_to_str(t):
)

daily = pd.crosstab(df5, df5.index.date, dropna=True, margins=True)
fig.add_trace(go.Bar(x=daily.columns[:-1], y=daily.loc[specie][:-1], marker_color='seagreen'), row=3, col=1)
fig.add_trace(go.Bar(x=daily.columns[:-1].tolist(), y=daily.loc[specie][:-1].tolist(), marker_color='seagreen'), row=3, col=1)
st.plotly_chart(fig, use_container_width=True) # , config=config)
df_counts = int(hourly[hourly.index == specie]['All'].iloc[0])
st.subheader('Total Detect:' + str('{:,}'.format(df_counts))
Expand Down Expand Up @@ -377,8 +378,8 @@ def hms_to_str(t):
species[1:],
index=0)

df_counts = int(hourly[hourly.index == specie]['All'])
fig = st.container()
df_counts = int(hourly.loc[hourly.index == specie, 'All'].iloc[0])

fig = make_subplots(rows=1, cols=1)

df4 = df2['Com_Name'][df2['Com_Name'] == specie].resample('15min').count()
Expand All @@ -390,14 +391,14 @@ def hms_to_str(t):
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()]
day_hour_freq.columns = fig_dec_y
fig_z = day_hour_freq.values.transpose()
fig_z = day_hour_freq.values.transpose().tolist()

color_pals = px.colors.named_colorscales()
selected_pal = st.sidebar.selectbox('Select Color Pallet for Daily Detections', color_pals)

heatmap = go.Heatmap(
x=fig_x,
y=day_hour_freq.columns,
y=day_hour_freq.columns.tolist(),
z=fig_z, # heat.values,
showscale=False,
texttemplate="%{text}", autocolorscale=False, colorscale=selected_pal
Expand Down Expand Up @@ -438,7 +439,7 @@ def hms_to_str(t):

plt_topN_today = (df6['Com_Name'].value_counts()[:readings])
freq_order = pd.value_counts(df6['Com_Name']).iloc[:readings].index
fig.add_trace(go.Bar(y=plt_topN_today.index, x=plt_topN_today, marker_color='seagreen', orientation='h'), row=1,
fig.add_trace(go.Bar(y=plt_topN_today.index.tolist(), x=plt_topN_today.values.tolist(), marker_color='seagreen', orientation='h'), row=1,
col=1)

df6['Hour of Day'] = [r.hour for r in df6.index.time]
Expand All @@ -447,6 +448,7 @@ def hms_to_str(t):
heat.index = pd.CategoricalIndex(heat.index, categories=freq_order)
heat.sort_index(level=0, inplace=True)

heat.index = heat.index.astype(str)
heat_plot_values = ma.log(heat.values).filled(0)

hours_in_day = pd.Series(data=range(0, 24))
Expand All @@ -457,7 +459,7 @@ def hms_to_str(t):

labels = heat.values.astype(int).astype('str')
labels[labels == '0'] = ""
fig.add_trace(go.Heatmap(x=heat.columns, y=heat.index, z=heat_values_normalized, # heat.values,
fig.add_trace(go.Heatmap(x=heat.columns.tolist(), y=heat.index.tolist(), z=heat_values_normalized, # heat.values,
showscale=False,
text=labels, texttemplate="%{text}", colorscale='Blugrn'
), row=1, col=2)
Expand Down