def update_prediction_convergence(static, inputs, models):
if (inputs is not None) and (models is not None):
# Filter inputs
file = models
inputs = sorted(inputs)
# Make filename
for parameter in inputs:
temp = parameter.strip(" ")
file += "_" + temp
# Initialise model
model = Predictor(dataset, inputs=inputs, model=models, filename=file)
# Run
results = model.check()
return {
'data': [{
'x': results[-1],
'y': results[1],
'line': dict(color='black')
}]
}
def convergence_block():
model = Predictor(dataset,
inputs=['Max Temp', 'Min Temp', 'Rain'],
model='svr',
filename='svr_Max Temp_Min Temp_Rain')
results = model.check()
layout = html.Div(
[
# Left Plot
html.Div(dcc.Graph(
id='fit_convergence_plot',
config={'displayModeBar': False},
animate=True,
figure={
'data': [{
'x': results[-1],
'y': results[0],
'line': dict(color='grey')
}],
'layout':
go.Layout(
title="Loss Scores: Fitting",
xaxis={'title': "Number of Data Points"},
yaxis={'range': [0, 0.3]},
margin={
'l': 50,
'b': 50,
't': 100,
'r': 50
},
)
},
),
style={
'width': '50%',
'display': 'inline-block'
}),
# Right Plot
html.Div(dcc.Graph(
id='pred_convergence_plot',
config={'displayModeBar': False},
animate=True,
figure={
'data': [{
'x': results[-1],
'y': results[1],
'line': dict(color='black')
}],
'layout':
go.Layout(
title="Loss Scores: Prediction",
xaxis={'title': "Number of Data Points"},
yaxis={'range': [0, 0.3]},
margin={
'l': 50,
'b': 50,
't': 100,
'r': 50
},
)
},
),
style={
'width': '50%',
'display': 'inline-block'
}),
],
className='container',
style={'margin-top': '10px'},
)
return layout