def corrConvergencePlot(self, simId, scenario, resultName):
df = self.getCorrByTrials(simId, scenario, resultName)
params = list(df['paramName'].unique())
traces = []
count = max(df['count'])
# create a trace for each parameter
for paramName in params:
paramData = df.query('paramName == "%s"' % paramName)
trace = go.Scatter(x=list(paramData['count']),
y=list(paramData['spearman']),
name=paramName,
mode='lines')
traces.append(trace)
# Round up to nearest integral value of CORR_STEP
endX = count + (CORR_STEP - count % CORR_STEP)
# I cannot center a narrower plot for reasons I don't understand
layout = updateStyle('Plot',
width=None,
title='Correlation Convergence for %s' %
resultName,
xaxis=dict(range=[CORR_STEP, endX]))
# margin=updateStyle('PlotMargin', l=40)
figure = dict(data=traces, layout=layout)
return figure
def tornadoPlot(self, simId, scenario, resultName, tornadoType,
sliderValue, selectedData):
corrDF = self.getCorrDF(simId, scenario, resultName)
if tornadoType == 'normalized':
squared = corrDF.spearman**2
corrDF['normalized'] = squared / squared.sum()
corrDF['sign'] = 1
corrDF.ix[(corrDF.spearman < 0), 'sign'] = -1
corrDF[
'value'] = corrDF.normalized * corrDF.sign # normalized squares with signs restored
plotColumn = 'value'
title = 'Normalized rank correlation'
else:
plotColumn = 'spearman'
title = 'Rank correlation'
title += ' of {} for scenario {}'.format(resultName, scenario)
varCount = min(
20, len(corrDF)
) # if sliderValue is None else len(corrDF[corrDF['abs'] >= sliderValue]))
varNames = list(reversed(corrDF.index[:varCount]))
values = list(reversed(corrDF[plotColumn][:varCount]))
plotData = go.Bar(
orientation='h',
x=values,
y=varNames,
width=0.6,
marker=dict(
color=getColor('TornadoPlotBar'),
line=dict(color=getColor('TornadoPlotLine'), width=0),
),
textposition='none',
name='Rank correlation',
hoverinfo='skip', # prevents hover events
)
layout = updateStyle('Plot',
title=title,
margin=updateStyle('PlotMargin', l=300),
xaxis=dict(range=[-1, 1]),
dragmode='select')
figure = dict(data=[plotData], layout=layout)
return figure
def showDistribution(project, simId, scenario, outputName, sliderInfo,
distOptions, selectedData):
_logger.debug('showDistribution(%s, %s, %s, %s, %s)' %
(project, simId, scenario, outputName, selectedData))
# Clear selectedData if context changes
context = (project, simId, scenario, outputName)
if not data.histogramContext or context != data.histogramContext:
_logger.debug('showDistribution: clearing context')
selectedData = sliderInfo = None
data.histogramContext = context
# if called before values are known, return an empty plot
if not (project and scenario and outputName) or simId is None:
plotData = {'x': []}
title = 'Please select a model output to plot'
annotations = None
else:
plotData, title, annotations = data.distPlot(
simId, scenario, outputName, sliderInfo, distOptions,
selectedData)
# TBD: generalize this
if Oct16:
if outputName == 'percent-change':
xtitle = 'Change from baseline fuel'
xticksuffix = '%'
else:
# latex formatting is broken, but HTML works fine
# xtitle = '$g CO_2 MJ^{-1}$' if Oct16 else ''
xtitle = 'g CO<sub>2</sub> MJ<sup>-1</sup>'
xticksuffix = None
else:
xtitle = data.db.getOutputUnits(outputName)
xticksuffix = ''
layout = updateStyle('Plot',
title=title,
yaxis={
'title': 'Probability density',
'tickvals': []
},
xaxis={
'title': xtitle,
'ticksuffix': xticksuffix,
},
margin=getStyle('PlotMarginWithXTitle'),
dragmode='select',
showLegend=True,
legend=dict(x=0.0,
y=1.0,
bgcolor=getColor('PlotBg')))
if annotations:
layout['annotations'] = annotations
figure = dict(data=plotData, layout=layout)
return figure
def tornadoSectionLayout(self):
layout = [
html.P([
html.Span(
'Adjust the number of variables to show by setting the correlation cut-off'
),
html.Span(id='corr-cutoff-text')
],
style=updateStyle(
'HelpText', display='none')), # getStyle('HelpText')),
html.Div([
html.Div(
[
dcc.Slider(id='tornado-slider',
disabled=True,
min=0,
max=0.4,
step=0.01,
marks={
value: sliderLabel(value)
for value in np.arange(0, 0.4, 0.1)
},
updatemode='drag',
value=0.01),
],
style={
'width': 300,
# 'display': 'inline-block'
'display': 'none'
}),
]),
html.Div(dcc.Graph(id='tornado'), style={'margin-top':
74}), # 20}),
dcc.RadioItems(id='tornado-type-chooser',
options=[{
'label': 'Rank correlation',
'value': 'spearman'
}, {
'label': 'Normalized',
'value': 'normalized'
}],
value='normalized',
labelStyle={
'display': 'inline-block',
'margin': '6px'
})
]
return layout
def layout(self):
layout = html.Div(
[
dataStore(id='paraCoords-vars'),
dataStore(id='dist-selected'),
html.H1('Monte Carlo Simulation Explorer', className='title'),
html.Table(
[
html.Tr([
html.Th('Project'),
html.Th('Simulation'),
html.Th('Scenario'),
html.Th('Model Output'),
]),
html.Tr([
html.Td(self.projectChooser()),
html.Td(self.simChooser()),
html.Td(self.scenarioChooser()),
html.Td(self.outputChooser())
])
],
style={
'width': '100%',
'border': '1px solid black',
'table-layout': 'fixed',
'background-color': getColor('ChooserBgColor')
}),
html.Div(
[
# distribution cluster and tornado chart
html.Div([
html.Div(self.distributionSectionLayout(),
className='cell twocol'),
html.Div(self.tornadoSectionLayout(),
className='cell twocol')
],
className='row'),
# parallel coordinates section
html.Div([
html.Div([
html.P([
'Brush vertically over ranges to filter; click outside the selected range to reset. ',
'Drag variable names below to reorder. Slider sets the number of vars to plot'
],
style=getStyle('HelpText')),
html.Div(
[
dcc.Slider(
id='paraCoords-slider',
min=1,
max=10,
step=1,
marks={
value:
sliderLabel(value)
for value in range(1, 11, 1)
},
updatemode='drag',
value=6),
],
style={
'margin-bottom': 30,
'margin-left': 'auto',
'margin-right': 'auto',
'width': 400
}),
html.Div(dcc.Graph(id='paraCoords')),
],
className='cell onecol')
],
className='row'),
# Correlation convergence section
html.Div([
html.Div([
html.Span('Correlation convergence',
style=getStyle('Label')),
html.Div('', style={'height': 15}),
html.Div(dcc.Graph(id='corr-convergence')),
],
className='cell onecol')
],
className='row'),
# Scatterplot section
html.Div([
html.Div([
html.Div([
html.Div(style={'height': 15}),
html.Span(
'Model Inputs (random variables)',
style=getStyle('Label')),
html.Div(style={'height': 15}),
self.inputChooser(multi=True)
],
style=updateStyle('Chooser',
width=900)),
html.Div(style={'height': 15}),
html.Div([
html.Span('Model Outputs',
style=getStyle('Label')),
self.multiOutputChooser()
],
style=updateStyle('Chooser',
width=900)),
html.Div([
html.Button('Create scatterplot',
id='scatterplot-button',
style=getStyle('Button'))
],
style={'margin': 5}),
html.Div([dcc.Graph(id='scatter-matrix')],
style=updateStyle('AutoMargins'))
],
className='cell onecol')
],
className='row'),
],
className='table',
style={
'width': 1200,
'margin-left': 'auto',
'margin-right': 'auto'
}),
],
style=getStyle('Page'))
return layout