Skip to content

Commit

Permalink
Les stations non monitorés par algo sont affiché de façon distinctes …
Browse files Browse the repository at this point in the history 
…(plotly & KeplerGL). Gestion des couleurs suivant l'état des stations sur KeplerGL graph. Les function KeplerGL retourn maintenant le graph (et non plus l'export HTML). Fix #49
  • Loading branch information
@armgilles
armgilles committed Apr 9, 2021
1 parent 48c909a commit 90a9396
Show file tree
Hide file tree
Showing 2 changed files with 54 additions and 21 deletions.
4 changes: 2 additions & 2 deletions notebooks/02_Features/07_visualisation_map_stations #49.ipynb
View file
Git LFS file not shown
71 changes: 52 additions & 19 deletions vcub_keeper/visualisation.py
View file
Original file line number Diff line number Diff line change
@@ -1,3 +1,4 @@
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
Expand All @@ -11,7 +12,8 @@
get_transactions_out,
get_transactions_all,
get_consecutive_no_transactions_out)
from vcub_keeper.config import NON_USE_STATION_ID, MAPBOX_TOKEN
from vcub_keeper.config import (NON_USE_STATION_ID, MAPBOX_TOKEN,
THRESHOLD_PROFILE_STATION)


def plot_station_activity(data, station_id,
Expand Down Expand Up @@ -375,6 +377,10 @@ def plot_map_station_with_plotly(station_control,
# Preprocess avant graphique
station_control['etat'] = 'normal'

# Non monitoré
station_control.loc[station_control['mean_activity'] < THRESHOLD_PROFILE_STATION,
'etat'] = 'non surveillée'

# En anoamlie (HS prediction)
station_control.loc[station_control['is_anomaly'] == 1, 'etat'] = 'anomaly'

Expand All @@ -389,7 +395,8 @@ def plot_map_station_with_plotly(station_control,
# Color for etat
color_etat = {'anomaly': '#EB4D50',
'inactive': '#5E9BE6',
'normal': '#6DDE75'}
'normal': '#6DDE75',
'non surveillée': '#696A6A'}

# To know when use add_trace after init fig
wtf_compteur = 0
Expand Down Expand Up @@ -452,12 +459,6 @@ def plot_map_station_with_kepler(station_control, station_id=None):
Si "station_id" est indiqué, alors la cartographie est focus sur la lat / lon de station (Numéro)
Export la cartographie sous le nom :
- "keplergl_map_global.html" si "station_id" n'est pas indiqué.
- "keplergl_map_station.html" si "station_id" est indiqué.
Ouvrir ensuite le fichier sur le browser.
Parameters
----------
data : pd.DataFrame
Expand All @@ -466,12 +467,12 @@ def plot_map_station_with_kepler(station_control, station_id=None):
Numéro de station que l'on souhaite voir (en focus) sur la cartographie.
Returns
-------
None
map_kepler : Graphique
Examples
--------
plot_map_station_with_kepler(station_control=station_control, station_id=6)
map_kepler = plot_map_station_with_kepler(data=station_control, station_id=6)
"""

# Global config plot
Expand Down Expand Up @@ -510,9 +511,10 @@ def plot_map_station_with_kepler(station_control, station_id=None):
"type": "custom",
"category": "Custom",
"colors": [
"#696A6A",
"#6DDE75",
"#EB4D50",
"#5E9BE6",
"#6DDE75"
"#5E9BE6"
]
},
"strokeColorRange": {
Expand Down Expand Up @@ -555,8 +557,8 @@ def plot_map_station_with_kepler(station_control, station_id=None):
},
"visualChannels": {
"colorField": {
"name": "etat",
"type": "string"
"name": "etat_id_sort",
"type": "integer"
},
"colorScale": "ordinal",
"strokeColorField": None,
Expand Down Expand Up @@ -650,6 +652,10 @@ def plot_map_station_with_kepler(station_control, station_id=None):
# Preprocess avant graphique
station_control['etat'] = 'normal'

# Non monitoré
station_control.loc[station_control['mean_activity'] < THRESHOLD_PROFILE_STATION,
'etat'] = 'non surveillée'

# En anoamlie (HS prediction)
station_control.loc[station_control['is_anomaly'] == 1, 'etat'] = 'anomaly'

Expand All @@ -662,7 +668,32 @@ def plot_map_station_with_kepler(station_control, station_id=None):
station_control['anomaly_since_str'] = station_control['anomaly_since_str'].fillna('-')

# Drop date for Kepler
station_control_kepler = station_control.drop(['last_date_anomaly', 'anomaly_since'], axis=1)
station_control = station_control.drop(['last_date_anomaly', 'anomaly_since'], axis=1)

# Add fake stations to have every type of etat (anomaly / normal / inactive
# & non surveillée) to match with fill color in plot

fake_station_every_etat = \
[[990, 0.4, 1, 0, 35, 60.9616624, -39.1527227, 'Station fake anomaly',
'anomaly', '2021-04-07 09:00'],
[991, 0.42, 1, 0, 21, 60.9616624, -39.1527227, 'Station fake normal',
'normal', '-'],
[992, 0.36, 0, 1, 22, 60.9616624, -39.1527227, 'Station fake inactive',
'inactive', '-'],
[993, 0.0, 0, 0, 22, 60.9616624, -39.1527227, 'Station non surveillée',
'non surveillée', '-']]

fake_station_every_etat_df = pd.DataFrame(fake_station_every_etat, columns=station_control.columns)
station_control = pd.concat([station_control, fake_station_every_etat_df])

# Sorting DataFrame to fill color in correct order
etat_id_sort = {'non surveillée': 0,
'normal': 1,
'anomaly': 2,
'inactive': 3}

station_control['etat_id_sort'] = station_control['etat'].map(etat_id_sort)
station_control = station_control.sort_values('etat_id_sort')

# Param plot with a given station_id
if station_id is not None:
Expand All @@ -680,12 +711,14 @@ def plot_map_station_with_kepler(station_control, station_id=None):
config_global['config']['mapState']['pitch'] = 54
# Building 3D
config_global['config']['mapStyle']['visibleLayerGroups']['3d building'] = True
file_name = 'keplergl_map_station.html'
# file_name = 'keplergl_map_station.html'
else:
file_name = 'keplergl_map_global.html'
# file_name = 'keplergl_map_global.html'
pass

# Load kepler.gl with map data and config
map_kepler = KeplerGl(height=400, data={"data_1": station_control_kepler}, config=config_global)
map_kepler = KeplerGl(height=400, data={"data_1": station_control}, config=config_global)

# Export
map_kepler.save_to_html(file_name=file_name)
# map_kepler.save_to_html(file_name=file_name) # No more export
return map_kepler

0 comments on commit 90a9396

Please sign in to comment.