class Widget(__Widget):
queyManager = IntelliFluxQueryManager()
# get widget data via query manager
def fetch_widget_data(self):
user_id = current_user.get_user_id()
time_stamp_from = current_user.get_time_stamp_from()
time_stamp_to = current_user.get_time_stamp_to()
database_id = current_user.get_user_database_id()
widget_name = '%s-widget-%s-%s-%s-user-%s' % (self.widget_type,
time_stamp_from, time_stamp_to, database_id, user_id)
sql_query = 'SELECT 0 as i, COUNT(id) as count FROM cleans WHERE relativeIntensity=0 AND startTime BETWEEN \'%s 00:00:00\' AND \'%s 00:00:00\'' % (
time_stamp_from, time_stamp_to)
for i in range(1, self.config['max-intensity']):
sql_query += ' UNION ALL SELECT %s as i, COUNT(id) as count FROM cleans WHERE relativeIntensity=%s AND startTime BETWEEN \'%s 00:00:00\' AND \'%s 00:00:00\'' % (
i, i, time_stamp_from, time_stamp_to)
cleaning_levels_data = self.queyManager.getWidgetDataFromQueryManager(
widget_name, time_stamp_from, time_stamp_to, database_id, sql_query, user_id, True)
self.widget_data = [data for data in cleaning_levels_data.values()]
# return the fetched data
return self.widget_data
# generate data for bar chart
def get_graph_data(self):
if not self.widget_data:
return []
# read the query manager dict into a dataframe
# data = pd.DataFrame.from_dict(self.widget_data, orient="index")
return [
go.Bar(
x=[data['i'] for data in self.widget_data],
y=[data['count'] for data in self.widget_data],
marker_color=['#10739e', '#f2931e', '#ae4132', '#12aab5', '#23445d'],
name='data' # Name the data series
)
]
# additional layout
def get_layout_options(self):
return dict(xaxis=dict(showticklabels=False), yaxis=dict(showticklabels=False))
# get graph in the current widget
def get_widget_graph(self):
return [
dcc.Graph(
figure=go.Figure(
data=self.get_graph_data(),
layout=self.get_graph_layout(
self.get_layout_options())
),
className='m-auto py-3'
)
]
class Widget(__Widget):
queyManager = IntelliFluxQueryManager()
# get widget data via query manager
def fetch_widget_data(self):
self.widget_data = []
user_id = current_user.get_user_id()
time_stamp_from = current_user.get_time_stamp_from()
time_stamp_to = current_user.get_time_stamp_to()
database_id = current_user.get_user_database_id()
widget_name = '%s-widget-%s-%s-%s-user-%s' % (
self.widget_type, time_stamp_from, time_stamp_to, database_id,
user_id)
for mode in self.config['mode'].split('+'):
title = ''
if mode == 'total':
title = 'Total Cleans'
sql_query = 'SELECT COUNT(DISTINCT(startTime)) as count FROM cleans WHERE startTime BETWEEN \'%s 00:00:00\' AND \'%s 00:00:00\'' % (
time_stamp_from, time_stamp_to)
elif mode == 'common':
title = 'Most Common'
sql_query = 'SELECT intensity, count(DISTINCT(startTime)) as count FROM cleans WHERE startTime BETWEEN \'%s 00:00:00\' AND \'%s 00:00:00\' GROUP BY intensity ORDER BY count DESC LIMIT 1' % (
time_stamp_from, time_stamp_to)
elif mode == 'time':
title = 'Clean Time'
sql_query = 'SELECT (SUM(TIMESTAMPDIFF(SECOND, startTime, endTime)) / 60 / 60) as time FROM cleans WHERE startTime BETWEEN \'%s 00:00:00\' AND \'%s 00:00:00\'' % (
time_stamp_from, time_stamp_to)
elif mode == 'use':
title = 'Water Use'
sql_query = 'SELECT SUM(JSON_EXTRACT(profile, \'$.WaterUsage\')) as usage FROM cleans WHERE startTime BETWEEN \'%s 00:00:00\' AND \'%s 00:00:00\'' % (
time_stamp_from, time_stamp_to)
data = self.queyManager.getWidgetDataFromQueryManager(
widget_name, time_stamp_from, time_stamp_to, database_id,
sql_query, user_id, True)
self.widget_data.append(
dict(mode=mode, title=title, value=data[0]['count']))
# return the fetched data
return self.widget_data
def get_widget_graph(self):
return [
dbc.Row([
dbc.Col([
html.H2(widget_data['value'], className='text-center'),
html.H5(widget_data['title'], className='text-center')
],
className='col-6 py-4')
for widget_data in self.widget_data
])
]
class Widget(__Widget):
queyManager = IntelliFluxQueryManager()
# get widget data via query manager
def fetch_widget_data(self):
user_id = current_user.get_user_id()
time_stamp_from = current_user.get_time_stamp_from()
time_stamp_to = current_user.get_time_stamp_to()
database_id = current_user.get_user_database_id()
widget_name = '%s-widget-%s-%s-%s-user-%s' % (
self.widget_type, time_stamp_from, time_stamp_to, database_id,
user_id)
# t_stamp = 'DATE_FORMAT(t_stamp, \'%Y-%m-%d\')'
# sql_query = 'SELECT name, AVG(value) as value, %s as t_stamp FROM data WHERE name=\'%s\' AND value > %s AND t_stamp BETWEEN \'%s\' AND \'%s\' group by %s;' % (
# t_stamp, self.config['metric'], self.config['flow_min'], time_stamp_from, time_stamp_to, t_stamp)
sql_query = 'SELECT t_stamp,value, name FROM data WHERE name=\'%s\' AND value > \'%s\' AND t_stamp BETWEEN \'%s 00:00:00\' AND \'%s 00:00:00\';' % (
self.config['metric'], self.config['flow_min'], time_stamp_from,
time_stamp_to)
flowdata = self.queyManager.getWidgetDataFromQueryManager(
widget_name, time_stamp_from, time_stamp_to, database_id,
sql_query, user_id, True)
temp_flowdata = dict()
for idx in flowdata:
row = flowdata[idx]
t_stamp = datetime.strptime(row['t_stamp'],
'%Y-%m-%dT%H:%M:%S.%fZ')
key = t_stamp.strftime('%Y-%m-%d')
if key not in temp_flowdata:
temp_flowdata[key] = []
temp_flowdata[key].append(
dict(t_stamp=row['t_stamp'], value=row['value']))
del flowdata
self.widget_data = dict()
for key in temp_flowdata:
flowdata = temp_flowdata[key]
prev_time = flowdata[0]['t_stamp']
if isinstance(prev_time, str):
prev_time = datetime.strptime(prev_time,
'%Y-%m-%dT%H:%M:%S.%fZ')
flow_total = 0.0
for row in flowdata[1:]:
# get the seconds between the previous and the current times
t_stamp = datetime.strptime(row['t_stamp'],
'%Y-%m-%dT%H:%M:%S.%fZ')
delta = (t_stamp - prev_time).total_seconds()
# skip rows longer than 2 minutes apart
if delta > 120:
prev_time = t_stamp
continue
# add to the flow totalizer
flow_total += (row['value'] / 3600.0) * delta
self.widget_data[key] = flow_total
# return the fetched data
return self.widget_data
# generate data for bar chart
def get_graph_data(self):
if not self.widget_data:
return []
# read the query manager dict into a dataframe
# data = pd.DataFrame.from_dict(self.widget_data, orient="index")
return [
go.Bar(
x=list(self.widget_data.keys()),
y=list(self.widget_data.values()),
marker_color=[
'#10739e', '#f2931e', '#ae4132', '#12aab5', '#23445d'
],
name='data' # Name the data series
)
]
# additional layout
def get_layout_options(self):
return dict(xaxis=dict(showticklabels=False),
yaxis=dict(showticklabels=False))
# get graph in the current widget
def get_widget_graph(self):
return [
dcc.Graph(figure=go.Figure(data=self.get_graph_data(),
layout=self.get_graph_layout(
self.get_layout_options())),
className='m-auto')
]
class Widget(__Widget):
queryManager = IntelliFluxQueryManager()
def fetch_widget_data(self):
"""
Get widget data via query manager
returns: {Dict} A dictionary of the pandas dataframe data from the query manager
"""
# Create the widget name for the QueryManager
cur_user = User.get_instance()
user_id = cur_user.get_user_id()
time_stamp_from = cur_user.get_time_stamp_from()
time_stamp_to = cur_user.get_time_stamp_to()
database_id = cur_user.get_user_database_id()
widget_name = '%s-widget-%s-%s-%s-%s-user-%s' % (
self.widget_type, self.config['title']['text'], time_stamp_from,
time_stamp_to, database_id, user_id)
# Define the MySQL query to run
sql_query = "SELECT t_stamp, value, name FROM data WHERE name=\'" + self.config[
'metric'] + "\' AND t_stamp BETWEEN \'%s 00:00:00\' AND \'%s 00:00:00\' order by t_stamp" % (
time_stamp_from, time_stamp_to)
# Fetch the data from the query manager
self.widget_data = self.queryManager.getWidgetDataFromQueryManager(
widget_name, time_stamp_from, time_stamp_to, database_id,
sql_query, user_id, True)
# return the fetched data
return self.widget_data
# generate data for bar chart
def get_graph_data(self, marker_props=[]):
"""
Generate data for a scatter plot
Arguments:
marker_props: {List} Properties for the plot markers
returns: {List} A lost containing a graph object
"""
if not self.widget_data:
return []
# read the query manager dict into a dataframe
data = pd.DataFrame.from_dict(self.widget_data, orient="index")
# return the scatter plot configuration
return [
go.Scatter(
# Use the t_stamp column of the dataframe as X
x=data['t_stamp'],
# Use the value column of the dataframe as Y
y=data['value'],
# Set plot mode to use markers
mode=self.config['mode']
if 'mode' in self.config else 'markers',
name='data' # Name the data series
)
]
# additional layout options
def get_layout_options(self):
return dict(xaxis=dict(showticklabels=False),
yaxis=dict(showticklabels=False),
margin=dict(b=30, t=40, r=30))
# get widget graph
def get_widget_graph(self):
return [
dcc.Graph(figure=go.Figure(data=self.get_graph_data(),
layout=self.get_graph_layout(
self.get_layout_options())),
className='m-auto')
]
def __init__(self, config, widget_type, is_child_widget=False):
self.config = config
self.widget_type = widget_type
self.is_child_widget = is_child_widget
self.query_manager = IntelliFluxQueryManager()
self.fetch_widget_data()