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app.py
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import dash
import dash_core_components as dcc
import dash_bootstrap_components as dbc
import dash_html_components as html
from dash.dependencies import Input, Output, State
from dash.exceptions import PreventUpdate
import plotly.express as px
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import plotly
import nrel_dash_components as ndc
import deckgl_ly as dgl
# Data/file handling imports
import pathlib
import glob
import pandas as pd
import numpy as np
import sys
import time
import datetime
import globalsUpdater as gu
import globals as gl
import math
import defines as dn
#-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-#
# Initialization
#-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-#
# ----------------------------------------------------------- #
# Read in the data and do some initial processing
# Set the path to the data
DATA_PATH = pathlib.Path(__file__).parent.joinpath("./data").resolve()
SCENARIO_PATH = DATA_PATH.joinpath("50Scen_3days 2")
# Read in the network
bus = pd.read_csv(DATA_PATH.joinpath("RTS/bus.csv"))
bus = bus[['Bus ID','lat','lng']]
branch = pd.read_csv(DATA_PATH.joinpath("RTS/branch.csv"))
branch = branch[['UID','From Bus','To Bus']]
# Process the branch data
fromPos = []
toPos = []
for index, row in branch.iterrows():
# Get the from bus and the to bus
fromBus = bus.loc[bus['Bus ID'] == row['From Bus']]
toBus = bus.loc[bus['Bus ID'] == row['To Bus']]
fromPos.append([float(fromBus['lng']),float(fromBus['lat'])])
toPos.append([float(toBus['lng']),float(toBus['lat'])])
branch['fromPos'] = fromPos
branch['toPos'] = toPos
# Get the list of summary data sets
summary_files = glob.glob(str(SCENARIO_PATH.joinpath("*.csv")))
summary_files.sort()
res = list(map(lambda st: str.replace(st, str(SCENARIO_PATH.joinpath("")), ""), summary_files))
res = list(map(lambda st: str.replace(st, "_", " "), res))
res = list(map(lambda st: str.replace(st, "/", ""), res))
listOfSummaryResults = list(map(lambda st: str.replace(st, ".csv", ""), res))
# Get the array of timeframes
summary = pd.read_csv(SCENARIO_PATH.joinpath("ac_results.csv"))
timeSteps = summary['DateTime'].to_list()
daterange = timeSteps
# ----------------------------------------------------------- #
# Create the initial map state
viewState ={
"longitude": -116,
"latitude": 34.65,
"zoom": 6,
"maxZoom": 20,
"pitch": 0,
"bearing": 0
}
scatterLayer = {
"type": "ScatterplotLayer",
"id": 'scatterplot-layer2',
"data": bus.to_dict(orient='records'),
"pickable": False,
"opacity": 0.15,
"stroked": True,
"filled": True,
"radiusScale": 1,
"radiusMinPixels": 5,
"lineWidthMinPixels": 1,
"getPosition": "function(d){return [d['lng'], d['lat']]}",
"getRadius": 25,
"getLineColor": [47, 79, 79],
"getFillColor": [248, 248, 255]
}
lineLayer = {
"type": "LineLayer",
"id": 'line-layer',
"data": branch.to_dict(orient='records'),
"pickable": False,
"opacity": 0.15,
"widthScale":2,
"widthMinPixels":1,
"getWidth": 1,
"getSourcePosition": "function(d){return d['fromPos']}",
"getTargetPosition": "function(d){return d['toPos']}",
"getColor": [47, 79, 79]
}
initialLayers = [lineLayer,scatterLayer]
#-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-#
# Layout
#-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-#
#------------------------------------------------#
# Create app and layout
app = dash.Dash(__name__, title='RTS', update_title='', external_stylesheets=[dbc.themes.BOOTSTRAP])
server = app.server # expose server variable for Dash server deployment
app.layout = ndc.NRELApp(
appName="Multi-Fidelity Economic Dispatch Visualizations",
description="Visualization tool for exploration of approximations to stocastic economic dispatch.",
children=[
dcc.Store(id='mode', storage_type='memory'),
dcc.Store(id='runsFile', storage_type='memory'),
dcc.Store(id='compareFile', storage_type='memory'),
dcc.Store(id='basicsFile', storage_type='memory'),
dcc.Store(id='timestep', storage_type='memory'),
dcc.Store(id='summaryExtents', storage_type='memory'),
dcc.Interval(
id='time-interval',
interval=1*100, # in milliseconds
n_intervals=0
),
html.Hr(),
html.Div(className='columns', children=[
html.Div(className='column is-one-quarter notification', children=[
dbc.Button("Investigate Power Flow Runs", id="scenario-collapse-button", className="mb-3"),
dbc.Collapse(
dbc.Card(
dbc.CardBody(children=[
#html.H4("Select Run to Explore", className="is-size-6"),
#html.P("Choose a scenario, results ", className="card-text"),
# Left UI tiles
html.Div(className='tile is-parent is-vertical is-12', children=[
html.P(className="title is-size-6", children=["Select Run to Explore:"]),
html.Div(className="subtitle", children=[
dcc.Dropdown(
id="scenario-dropdown",
style={"fontSize": "14px"},
options=[{ "label": dn.scenarioDirs[i]["label"], "value": i} for i in dn.scenarioDirs.keys()],
),
]),
]),
])
),
id="scenario-collapse",
is_open=True,
className="mb-3",
),
dbc.Button("Compare Power Flow Runs", id="comparison-collapse-button", className="mb-3"),
dbc.Collapse(
dbc.Card(
dbc.CardBody(children=[
html.H4("Choose runs for comparison.", className="is-size-5"),
html.P(className="title is-size-6", children=["Scenario 1:"]),
html.Div(className="subtitle", children=[
dcc.Dropdown(
id="scenario-1-dropdown",
style={"fontSize": "14px"},
options=[{ "label": dn.scenarioDirs[i]["label"], "value": i} for i in dn.scenarioDirs.keys()],
),
]),
html.P(className="title is-size-6", children=["Scenario 2:"]),
html.Div(className="subtitle", children=[
dcc.Dropdown(
id="scenario-2-dropdown",
style={"fontSize": "14px"},
options=[{ "label": dn.scenarioDirs[i]["label"], "value": i} for i in dn.scenarioDirs.keys()],
),
]),
html.P("Choose a map comparison operator and a variable."),
html.P(className="title is-size-6", children=["Operator:"]),
html.Div(className="subtitle", children=[
dcc.Dropdown(
id="operator-dropdown",
style={"fontSize": "14px"},
options=[{ "label": 'overlay', "value": 0}, { "label": 'difference', "value": 1}],
),
]),
html.P(className="title is-size-6", children=["Map Variable:"]),
html.Div(className="subtitle", children=[
dcc.Dropdown(
id="variable-dropdown",
style={"fontSize": "14px"},
options=[{ "label": dn.detailsFiles[i]["label"], "value": i} for i in dn.detailsFiles.keys()],
),
]),
html.P("Choose variables to show on the left and right plots."),
html.P(className="title is-size-6", children=["Left Plot Variable:"]),
html.Div(className="subtitle", children=[
dcc.Dropdown(
id="left-variable-dropdown",
style={"fontSize": "14px"},
options=[{ "label": dn.detailsVars[i]["label"], "value": i} for i in dn.detailsVars.keys()],
),
]),
html.P(className="title is-size-6", children=["Right Plot Variable:"]),
html.Div(className="subtitle", children=[
dcc.Dropdown(
id="right-variable-dropdown",
style={"fontSize": "14px"},
options=[{ "label": dn.detailsVars[i]["label"], "value": i} for i in dn.detailsVars.keys()],
),
]),
])
),
id="comparison-collapse",
is_open=False,
className="mb-3",
),
dbc.Button("Display Basic Info", id="basics-collapse-button", className="mb-3"),
dbc.Collapse(
dbc.Card(
dbc.CardBody(children=[
html.P(className="title is-size-6", children=["Select data to show on the grid:"]),
html.Div(className="subtitle", children=[
dcc.Dropdown(
id="basics-dropdown",
style={"fontSize": "14px"},
options=[{ "label":"Maximal Wind Generation", "value": 0}],
),
]),
])
),
id="basics-collapse",
is_open=False,
className="mb-3",
),
]),
html.Div(className='column is-three-quarters', children=[
# Right Vis tiles
html.Div(className='tile is-parent is-vertical is-12', children=[
# Slider tile
html.Div(className='tile is-child', id="timeDiv", children=[
dbc.Collapse(
dbc.Card(
dbc.CardBody(children=[
html.Div(className="tile", children=[
dbc.Button('Stop', id='stop-val', className="mr-1 mb-2", color="danger", size="sm", outline=True,n_clicks=0, disabled=True),
dbc.Button('Play', id='play-val', className="mr-1 mb-2", color="dark", size="sm", outline=True,n_clicks=0),
html.P(className='tag is-large', id="slider-val", children=[]),
]),
html.Div(className="tile is-child ml-3 pl-6", children=[
dcc.Slider(
id='time-slider',
min = 0,
max = len(timeSteps)+10,
value = 0,
marks=dn.getMarks(timeSteps),
updatemode='drag',
className="sliderSmall ml-3 pl-3"
),
])
])
),
id="slider-collapse",
is_open=True,
)
]),
# Map tile
html.Div(className='tile is-child' , children=[
html.Div(className='tile is-dark mapDiv', children=[
dgl.DeckglLy(id='network-map',
mapboxtoken="pk.eyJ1Ijoia3BvdHRlciIsImEiOiJCNFlOLWVnIn0.IdEiAEoZbboAuuqOYtWg0w",
mapStyle="mapbox://styles/kpotter77/ck6ct8e2w0o1o1imrq0runboi",
viewState = viewState,
layers=initialLayers
),
])
]),
# Graphs tile
html.Div(className='tile is-child' , children=[
dbc.Collapse(
dbc.Card(
dbc.CardBody(children=[
html.Div(className="columns", children=[
html.Div(className='column is-6', children=[
dcc.Graph(id="left-chart", config={'displayModeBar': False}),
]),
html.Div(className='column is-6 ', children=[
dcc.Graph(id="right-chart", config={'displayModeBar': False}),
]),
])
])
),
id="graphs-collapse",
is_open=True,
)
])
])
]),
]),
html.Div(className="hero is-small box", children=[
html.Details(className="", open=False, children=[
html.Summary("Credits"),
html.Div(className="card", children=[
html.Header(className="card-header", children=[
html.P(className="card-header-title",children=[
"Developers and Collaborators"
]),
]),
html.Div(className="card-content", children=[
html.Div(className="content", children=[
html.P(className="instruct-labels", children=[
"Kristi Potter (Kristi.Potter@nrel.gov)",
html.Br(),
"Ryan King (Ryan.King@nrel.gov)",
html.Br(),
"Kinshuk Panda (Kinshuk.Panda@nrel.gov)",
html.Br(),
"Jonathan Maack (Jonathan.Maack@nrel.gov)"
]),
]),
]),
html.Footer(className="card-footer", children=[
html.Div(className="card-footer-item", children=[
html.P(className="subtitle", children=["Continue to check back for updates and new features!"]),
]),
]),
html.Footer(className="card-footer", children=[
html.Div(className="card-footer-item", children=[
html.P(className="acks", children=[
"This work was authored by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308.",
" This work was supported by the Laboratory Directed Research and Development (LDRD) Program at NREL.",
" The research was performed using computational resources sponsored by the Department of Energy’s Office of Energy Efficiency and Renewable Energy and located at the National Renewable Energy Laboratory.",
" The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government.",
" The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes."
])
]),
]),
])
])
])
]
)
#-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-#
# Callbacks
#-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-#
@app.callback(Output("mode", "data"),
Output("scenario-collapse", "is_open"),
Output("comparison-collapse", "is_open"),
Output("basics-collapse", "is_open"),
Input("scenario-collapse-button", "n_clicks"),
Input("comparison-collapse-button", "n_clicks"),
Input("basics-collapse-button", "n_clicks"),
State("scenario-collapse", "is_open"),
State("comparison-collapse", "is_open"),
State("basics-collapse", "is_open"),
)
def toggle_fade(scenario_n, comparison_n, basics_n, scenario_is_open, comparison_is_open, basics_is_open):
# Change outputs based on which input is triggered
ctx = dash.callback_context
triggered = ctx.triggered[0]['prop_id']
mode = None
scenario = scenario_is_open
comparison = comparison_is_open
basics = basics_is_open
if(triggered=="."):
mode = "scenario"
elif(triggered == "scenario-collapse-button.n_clicks"):
basics = False
scenario = not scenario
comparison = not scenario
mode = "scenario" if scenario else "comparison"
elif(triggered == "comparison-collapse-button.n_clicks"):
scenario = False
comparison = not comparison
basics = not comparison
mode = "comparison" if comparison else "basics"
elif(triggered == "basics-collapse-button.n_clicks"):
comparison = False
basics = not basics
scenario = not basics
mode = "basics" if basics else "scenario"
return mode, scenario, comparison, basics
#------------------------------------------------#
# Callback for playback
@app.callback(Output('play-val', 'disabled'),
Output('stop-val', 'disabled'),
Input('play-val', 'n_clicks_timestamp'),
Input('stop-val', 'n_clicks_timestamp'),
prevent_initial_call=True)
def useButtons(play_clicks, stop_clicks):
if(stop_clicks == None):
return True, False
elif(play_clicks > stop_clicks):
return True, False
else:
return False, True
#------------------------------------------------#
# Callback for time interval & time slider
@app.callback(Output('time-slider', 'value'),
Input('time-interval', 'n_intervals'),
State('play-val', 'disabled'), State('timestep', 'data'),
prevent_initial_call=True)
def updateSlider(intervalTick, playVal, timestep):
if(playVal == None and timestep==None):
return 0
else:
if(playVal):
return timestep + 1
else:
raise PreventUpdate()
#------------------------------------------------#
# Callbacks to update time slider
#------------------------------------------------#
@app.callback(Output('timestep', 'data'),
Output('slider-val', 'children'),
Input('time-slider', 'value'),
prevent_initial_call=True)
def updateTimestep(value):
if(value >= len(timeSteps)):
return 0, (" Timestep: "+pd.to_datetime(timeSteps[len(timeSteps)-1]).strftime("%m/%d, %H:%M"))
else:
return value, (" Timestep: "+pd.to_datetime(timeSteps[value]).strftime("%m/%d, %H:%M"))
#------------------------------------------------#
# Callbacks to update the runs data
#------------------------------------------------#
@app.callback(Output('runsFile','data'),
Output('summaryExtents', 'data'),
Input('scenario-dropdown', 'value'),
prevent_initial_call=True)
def updateRunsFile(directory):
haveData = False
# Read in the loss of load
try:
bdLoss = pd.read_csv(SCENARIO_PATH.joinpath(directory+"/"+"real_loss_of_load.csv")).T.reset_index()
bdLoss.columns = bdLoss.iloc[0]
bdLoss = bdLoss.rename(columns={"DateTime": 'Bus ID'})
bdLoss = bdLoss.iloc[1:]
gu.setBusLossData(bdLoss)
haveData = True
except IOError:
gu.setBusLossData(None)
haveData = False
# Read in the thermal set points
try:
bdThermal = pd.read_csv(SCENARIO_PATH.joinpath(directory+"/"+"real_thermal_set_points_processed.csv")).T.reset_index()
bdThermal.columns = bdThermal.iloc[0]
bdThermal = bdThermal.rename(columns={"DateTime": 'Bus ID'})
bdThermal = bdThermal.iloc[1:]
gu.setBusThermalData(bdThermal)
haveData = True
except IOError:
gu.setBusThermalData(None)
haveData = False
# Read in the renewable set points
try:
bdRenewable = pd.read_csv(SCENARIO_PATH.joinpath(directory+"/"+"real_renewable_setpoints_processed.csv")).T.reset_index()
bdRenewable.columns = bdRenewable.iloc[0]
bdRenewable = bdRenewable.rename(columns={"DateTime": 'Bus ID'})
bdRenewable = bdRenewable.iloc[1:]
gu.setBusRenewableData(bdRenewable)
haveData = True
except IOError:
gu.setBusRenewableData(None)
haveData = False
# Read in the summary file
try:
summaryFile = pd.read_csv(SCENARIO_PATH.joinpath(dn.scenarioDirs[directory]['summary']))
summaryFile = summaryFile[['DateTime','ActLossLoad','ActOverLoad','ActRenew','ActSpill','ActFirstStageCost','ActSecondStageCost']]
gu.setSummaryData(summaryFile)
summaryMinCost = summaryFile[['ActFirstStageCost','ActSecondStageCost']]
summaryMinLoad = summaryFile[['ActLossLoad','ActOverLoad','ActRenew','ActSpill']]
summaryExtents ={"cost":[summaryMinCost.values.min(),summaryMinCost.values.max()], "load":[summaryMinLoad.values.min(), 3448.505510]}
haveData = True
except IOError:
gu.setSummaryData(None)
haveData = False
# Read in the actuals
try:
actuals = pd.read_csv(SCENARIO_PATH.joinpath("actuals.csv"))
gu.setActualsData(actuals)
haveData = True
except IOError:
gu.setActualsData(None)
haveData = False
return haveData, summaryExtents
#------------------------------------------------#
# Callbacks to update the basics data
#------------------------------------------------#
@app.callback(Output('basicsFile','data'),
Input('basics-dropdown','value'),
prevent_initial_call=True)
def updateBasicsFile(value):
haveData = False
# The get the maximal generation values
if(value==0):
try:
# Read in the max generation file
gu.setBasicsData(pd.read_csv(DATA_PATH.joinpath("RTS/fullMaxGen.csv")))
haveData = True
except IOError:
gu.setBasicsData(None)
haveData = False
return haveData
#------------------------------------------------#
# Callbacks to update the compare data
#------------------------------------------------#
@app.callback(Output('compareFile','data'),
Input('scenario-1-dropdown','value'),
Input('scenario-2-dropdown','value'),
Input('operator-dropdown', 'value'),
Input('variable-dropdown', 'value'),
Input('left-variable-dropdown', 'value'),
Input('right-variable-dropdown', 'value'),
prevent_initial_call=True)
def updateCompareFile(scenario1, scenario2, operator, mapVar, leftVar, rightVar):
haveData = False
if(scenario1 != None) and (scenario2 != None) and (operator != None) and (mapVar != None) and (leftVar != None and rightVar != None):
try:
# Read in the two runs
s1 = pd.read_csv(SCENARIO_PATH.joinpath(scenario1+"/"+mapVar)).T.reset_index()
s2 = pd.read_csv(SCENARIO_PATH.joinpath(scenario2+"/"+mapVar)).T.reset_index()
# Reset the indexes
s1.columns = s1.iloc[0]
s1 = s1.iloc[1:]
s1 = s1.rename(columns={"DateTime": 'Bus ID'})
s1.set_index('Bus ID', inplace=True, drop=True)
# Reset the indexes
s2.columns = s2.iloc[0]
s2 = s2.iloc[1:]
s2 = s2.rename(columns={"DateTime": 'Bus ID'})
s2.set_index('Bus ID', inplace=True, drop=True)
# If we have the overlay operator
if(operator == 0):
gu.setCompareData({'type':'overlay',
'data': {"s1":s1.reset_index(level=0, inplace=False),
"s2":s2.reset_index(level=0, inplace=False)}})
# If we have a difference operator
elif(operator == 1):
# Get the absolute value of the difference
difference = s1-s2
difference = difference.abs()
difference.reset_index(level=0, inplace=True)
gu.setCompareData({'type':'difference', 'data': difference})
# Get the plot files
summaryFile1 = pd.read_csv(SCENARIO_PATH.joinpath(dn.scenarioDirs[scenario1]['summary']))
summaryFile2 = pd.read_csv(SCENARIO_PATH.joinpath(dn.scenarioDirs[scenario2]['summary']))
leftData1 = summaryFile1[['DateTime',leftVar]]
leftData2 = summaryFile2[['DateTime',leftVar]]
lExtent = [leftData1[leftVar].values.min() if leftData1[leftVar].values.min() < leftData2[leftVar].values.min() else leftData2[leftVar].values.min(),
leftData1[leftVar].values.max() if leftData1[leftVar].values.max() > leftData2[leftVar].values.max() else leftData2[leftVar].values.max()]
gu.setLeftPlotData({"one":leftData1, "two":leftData2,'tag':leftVar, 'oneScen':scenario1,'twoScen':scenario2, 'extents':lExtent})
rightData1 = summaryFile1[['DateTime',rightVar]]
rightData2 = summaryFile2[['DateTime',rightVar]]
r1Min = rightData1[rightVar].values.min()
r2Min = rightData2[rightVar].values.min()
r1Max = rightData1[rightVar].values.max()
r2Max = rightData2[rightVar].values.max()
rExtent = [r1Min if r1Min < r2Min else r2Min, r1Max if r1Max > r2Max else r2Max]
gu.setRightPlotData({"one":rightData1, "two":rightData2, 'tag':rightVar, 'oneScen':scenario1,'twoScen':scenario2, 'extents':rExtent})
haveData = True
except IOError:
gu.setCompareData(None)
gu.setLeftPlotData(None)
gu.setRightPlotData(None)
haveData = False
if(haveData == False):
raise PreventUpdate()
else:
return haveData
#------------------------------------------------#
# Callbacks for the summary/timeseries files
#------------------------------------------------#
@app.callback(Output('left-chart', 'figure'),
Output('right-chart', 'figure'),
Output('slider-collapse', 'is_open'),
Output('graphs-collapse', 'is_open'),
Input('timestep', 'data'),
Input('runsFile', 'data'),
Input('basicsFile', 'data'),
Input('compareFile', 'data'),
Input('mode', 'data'),
State('mode', 'data'),
State('summaryExtents', 'data'),
prevent_initial_call=True)
def createCharts(timestep, runsFile, compareFile, basicsFile, showMode, modeState, summaryExtents):
# Change outputs based on which input is triggered
ctx = dash.callback_context
triggered = ctx.triggered[0]['prop_id']
# Return values
leftFig = dash.no_update
rightFig = dash.no_update
sliderIsOpen = True
graphsIsOpen = True
# Create the runs charts
if(showMode == 'scenario'):
# Get the globally stored files
summaryFile = gl.summaryStore
actuals = gl.actualsStore
if(summaryFile is not None) and (actuals is not None) and (summaryExtents is not None):
# Cost figure
df = summaryFile
date = df['DateTime']
leftFig = go.Figure()
leftFig.add_trace(go.Scatter(x=df['DateTime'], y=df['ActFirstStageCost'], fill='tozeroy', name='ActFirstStageCost', stackgroup='one',line=dict(color="#008B8B")))
leftFig.add_trace(go.Scatter(x=df['DateTime'], y=df['ActSecondStageCost'], fill='tonexty',name='ActSecondStageCost', stackgroup='one',line=dict(color="#F08080")))
leftFig.add_trace(go.Scatter(x=[daterange[timestep], daterange[timestep]], y=[summaryExtents['cost'][0], 110000], name='Time Step', line=dict(color="#2F4F4F")))
# Actuals figure
rightFig = go.Figure()
rightFig.add_trace(go.Scatter(x=df['DateTime'], y=df['ActLossLoad'], fill='tozeroy', name='Actual Loss Load', stackgroup='one',line=dict(color=dn.lossHex)))
rightFig.add_trace(go.Scatter(x=df['DateTime'], y=df['ActSpill'], fill='tonexty',name='Actual Spill', stackgroup='one',line=dict(color='#FF7F50')))
rightFig.add_trace(go.Scatter(x=df['DateTime'], y=df['ActRenew'], fill='tonexty',name='Actual Renewable', stackgroup='one',line=dict(color=dn.renewableHex)))
rightFig.add_trace(go.Scatter(x=actuals['DateTime'], y=actuals['total'],name='Actual Wind', line=dict(color='royalblue', width=4, dash='dot')))
rightFig.add_trace(go.Scatter(x=[daterange[timestep], daterange[timestep]], y=[summaryExtents['load'][0],4500], name='Time Step', line=dict(color="#2F4F4F")))
leftFig.update_layout(
autosize=False,
#width=700,
#height=300,
margin=dict(
l=0,
r=0,
b=0,
t=0,
pad=0
),
legend=dict(
yanchor="bottom",
y=.65,
xanchor="right",
x=0.99
)
)
rightFig.update_layout(
autosize=False,
#width=700,
#height=300,
margin=dict(
l=0,
r=0,
b=0,
t=0,
pad=0
),
legend=dict(
yanchor="bottom",
y=.5,
xanchor="right",
x=0.99
)
)
leftFig.update_xaxes(
title_text = "Time",
range=[daterange[0],daterange[len(daterange)-1]],
showgrid= False,
)
leftFig.update_yaxes(
title_text = "Cost ($/minute)",
showgrid= False,
range=[0, 120000],
title_font=dict(size=10),
)
rightFig.update_xaxes(
title_text = "Time",
range=[daterange[0],daterange[len(daterange)-1]],
showgrid = False)
rightFig.update_yaxes(
title_text = "Capacity kW",
showgrid= False,
range=[0, 5000],
title_font=dict(size=10),
)
# Hide the timestep slider and charts
elif(showMode == 'basics'):
sliderIsOpen = False
graphsIsOpen = False
# Create the compare charts
elif(showMode == "comparison"):
leftData = gl.leftPlotStore
rightData = gl.rightPlotStore
if(leftData is not None) and (rightData is not None):
leftData1 = leftData['one']
leftData2 = leftData['two']
lExtents = leftData['extents']
lTag = leftData['tag']
scn1 = leftData['oneScen']
scn2 = leftData['twoScen']
s1Name = dn.scenarioDirs[scn1]['label'].split("(")[0]
s2Name = dn.scenarioDirs[scn2]['label'].split("(")[0]
leftFig = go.Figure()
leftFig.add_trace(go.Scatter(x=leftData1['DateTime'], y=leftData1[lTag], fill='tozeroy', name=s1Name,line=dict(color="#008B8B")))
leftFig.add_trace(go.Scatter(x=leftData2['DateTime'], y=leftData2[lTag], name=s2Name,line=dict(color="#F08080")))
leftFig.add_trace(go.Scatter(x=[daterange[timestep], daterange[timestep]], y=[lExtents[0], lExtents[1]], name='Time Step', line=dict(color="#2F4F4F")))
rightData1 = rightData['one']
rightData2 = rightData['two']
rTag = rightData['tag']
rExtents = rightData['extents']
rightFig = go.Figure()
rightFig.add_trace(go.Scatter(x=rightData1['DateTime'], y=rightData1[rTag], fill='tozeroy', name=s1Name, line=dict(color="#008B8B")))
rightFig.add_trace(go.Scatter(x=rightData2['DateTime'], y=rightData2[rTag], name=s2Name, line=dict(color="#F08080")))
rightFig.add_trace(go.Scatter(x=[daterange[timestep], daterange[timestep]], y=[rExtents[0], rExtents[1]], name='Time Step', line=dict(color="#2F4F4F")))
leftFig.update_layout(
title={
'text': dn.detailsVars[lTag]['label'],
'y':0.9,
'x':0.15,
'xanchor': 'left',
'yanchor': 'top',
},
autosize=False,
#width=700,
#height=300,
margin=dict(
l=0,
r=0,
b=0,
t=50,
pad=0
),
legend=dict(
yanchor="bottom",
y=1,
xanchor="right",
x=1
)
)
rightFig.update_layout(
title={
'text': dn.detailsVars[rTag]['label'],
'y':0.9,
'x':0.15,
'xanchor': 'left',
'yanchor': 'top',
},
autosize=False ,
#width=700,
#height=300,
margin=dict(
l=0,
r=0,
b=0,
t=50,
pad=0
),
legend=dict(
yanchor="bottom",
y=1,
xanchor="right",
x=1
)
)
leftFig.update_xaxes(
title_text = "Time",
range=[daterange[0],daterange[len(daterange)-1]],
showgrid= False,
)
leftFig.update_yaxes(
title_text = dn.detailsVars[lTag]['label'],
showgrid= False,
#range=[0, 120000],
title_font=dict(size=10),
)
rightFig.update_xaxes(
title_text = "Time",
range=[daterange[0],daterange[len(daterange)-1]],
showgrid = False)
rightFig.update_yaxes(
title_text = dn.detailsVars[rTag]['label'],
showgrid= False,
#range=[0, 5000],
title_font=dict(size=10),
)
return leftFig, rightFig, sliderIsOpen, graphsIsOpen
#------------------------------------------------#
# Callbacks for detail files
#------------------------------------------------#
@app.callback(Output("network-map", "layers"),
Input('timestep', 'data'),
Input('runsFile', 'data'),
Input('basicsFile', 'data'),
Input('compareFile', 'data'),
Input('mode', 'data'),
State('mode', 'data'),
prevent_initial_call=True)
def createMap(timestep, runsFile, basicsFile, compareFile, showMode, modeState):
# Change outputs based on which input is triggered
ctx = dash.callback_context
triggered = ctx.triggered[0]['prop_id']
# Create the map layers
mapLayers=[]
# If we are showing default runs
if(showMode == "scenario"):
# If we have bus data
if(runsFile == True):
# Add the branch layer
mapLayers.append(initialLayers[0])
mapLayers.append(initialLayers[1])
# Grab the loss of load
busLoss = gl.busLossStore[['Bus ID',daterange[timestep]]]
busLoss = busLoss.astype({'Bus ID': 'int64', daterange[timestep]:'float64'})
busLoss = busLoss.rename(columns={daterange[timestep]: "Loss"})
# Grab the thermal generation
busThermal= gl.busThermalStore[['Bus ID',daterange[timestep]]]
busThermal = busThermal.astype({'Bus ID': 'int64', daterange[timestep]:'float64'})
busThermal = busThermal.rename(columns={daterange[timestep]: "Thermal"})
# Grab the renewable generation
busRenewable = gl.busRenewableStore[['Bus ID',daterange[timestep]]]
busRenewable = busRenewable.astype({'Bus ID': 'int64', daterange[timestep]:'float64'})
busRenewable = busRenewable.rename(columns={daterange[timestep]: "Renewable"})
# Append the data to the geometry data
busMapData = pd.merge(busLoss, bus, on='Bus ID')
busMapData = pd.merge(busThermal, busMapData, on='Bus ID')
busMapData = pd.merge(busRenewable, busMapData, on='Bus ID')
# Create the reneweable layer
renewableScatterLayer = {
"type": "ScatterplotLayer",
"id": 'scatterplot-layer-renewable',
"data": busMapData.to_dict(orient='records'),
"pickable": False,
"opacity": .25,
"stroked": True,
"filled": True,
"radiusScale": 50,
"lineWidthScale": 25,
"radiusMinPixels": 0,
"lineWidthMinPixels": 0,
"getPosition": "function(d){return [d['lng'], d['lat']]}",
"getRadius": "function(d){return d['Renewable']}",
"getLineWidth": "function(d){return d['Renewable']}",
"getLineColor": dn.renewableColor,
"getFillColor": dn.renewableColor,
}
mapLayers.append(renewableScatterLayer)
# Create the thermal layer
thermalScatterLayer = {
"type": "ScatterplotLayer",
"id": 'scatterplot-layer-thermal',
"data": busMapData.to_dict(orient='records'),
"pickable": False,
"opacity": .25,
"stroked": True,
"filled": True,
"radiusScale": 50,
"lineWidthScale": 25,
"radiusMinPixels": 0,
"lineWidthMinPixels": 0,
"getPosition": "function(d){return [d['lng'], d['lat']]}",
"getRadius": "function(d){return d['Thermal']}",
"getLineWidth": "function(d){return d['Thermal']}",
"getLineColor": dn.thermalColor,
"getFillColor": dn.thermalColor,
}
mapLayers.append(thermalScatterLayer)
# Create the loss layer
lossScatterLayer = {
"type": "ScatterplotLayer",
"id": 'scatterplot-layer2',
"data": busMapData.to_dict(orient='records'),
"pickable": False,
"opacity": 0.5,
"stroked": True,
"filled": True,
"radiusScale":50,
"lineWidthScale": 25,
"radiusMinPixels": 0,
"lineWidthMinPixels": 0,
"getPosition": "function(d){return [d['lng'], d['lat']]}",
"getRadius": "function(d){return d['Loss']}",
"getLineWidth": "function(d){return d['Loss']}",
"getLineColor": "function(d){ let color = d['Loss']==0 ? [248, 248, 255] : [227,26,28]; return color}",
"getFillColor": "function(d){ let color = d['Loss']==0 ? [248, 248, 255] : [227,26,28]; return color}",
}
mapLayers.append(lossScatterLayer)
elif(showMode == "comparison"):
mapLayers.append(initialLayers[0])
mapLayers.append(initialLayers[1])
if(compareFile == True):
# Create the difference scatter layer
if(gl.compareStore['type'] == "difference"):
diff = gl.compareStore['data'][['Bus ID',daterange[timestep]]]
diff = diff.astype({'Bus ID': 'int64', daterange[timestep]:'float64'})
diff = diff.rename(columns={daterange[timestep]: "diff"})
diffMap = pd.merge(diff, bus, on='Bus ID')
# Create the diff layer
diffScatterLayer = {
"type": "ScatterplotLayer",
"id": 'scatterplot-layer-renewable',
"data": diffMap.to_dict(orient='records'),
"pickable": False,
"opacity": .5,
"stroked": True,
"filled": True,
"radiusScale": 50,
#"lineWidthScale": 25,
"radiusMinPixels": 1,
"lineWidthMinPixels": 1,
"getPosition": "function(d){return [d['lng'], d['lat']]}",
"getRadius": "function(d){return d['diff']}",
#"getLineWidth": "function(d){return d['diff']}",
"getLineColor": dn.lineColor,
"getFillColor": dn.diffColor,
}
mapLayers.append(diffScatterLayer)
elif(gl.compareStore['type'] == "overlay"):
r1 = gl.compareStore['data']['s1'][['Bus ID',daterange[timestep]]]
r1 = r1.astype({'Bus ID': 'int64', daterange[timestep]:'float64'})
r1 = r1.rename(columns={daterange[timestep]: "diff"})
r1 = pd.merge(r1, bus, on='Bus ID')
r2 = gl.compareStore['data']['s2'][['Bus ID',daterange[timestep]]]
r2 = r2.astype({'Bus ID': 'int64', daterange[timestep]:'float64'})
r2 = r2.rename(columns={daterange[timestep]: "diff"})
r2 = pd.merge(r2, bus, on='Bus ID')
# Create the r1 layer
r1ScatterLayer = {
"type": "ScatterplotLayer",
"id": 'scatterplot-layer-renewable',