def test_coefficients_to_points_corrupted_model(postprocess_profiles):
""" Test conversion from models coefficients to points on a profile with invalid model.
Expecting to catch InvalidModelException exception.
"""
# Acquire the corrupted models query profile with invalid model
models_profile = profile_filter(postprocess_profiles,
'complexity-models-corrupted-model.perf')
assert models_profile is not None
# Get all models and perform the conversion on all of them
models = list(query.all_models_of(models_profile))
with pytest.raises(exceptions.InvalidModelException):
for model in models:
convert.plot_data_from_coefficients_of(model[1])
def create_parametric_model(graph, model, colour):
"""
Rendering the parametric models according to its coefficients.
:param charts.Graph graph: the scatter plot to render new models
:param model: the parametric model to be render to the graph
:param colour: the color of the current model to distinguish in the case of several models in the graph
:return charts.Graph: the modified graph with new model curves
"""
# Convert the coefficients to points that can be plotted
model = convert.plot_data_from_coefficients_of(model)
# Create legend for the plotted model
coeffs = ', '.join('{}={:f}'.format(c['name'], c['value'])
for c in model['coeffs'])
legend = '{0}: {1}, r^2={2:f}'.format(model['model'], coeffs,
model['r_square'])
# Plot the model
graph.line(x=model['plot_x'],
y=model['plot_y'],
line_color='#000000',
line_width=7.5,
legend=legend)
graph.line(x=model['plot_x'],
y=model['plot_y'],
line_color=colour,
line_width=3.5,
legend=legend)
return graph
def test_coefficients_to_points_correct(postprocess_profiles):
""" Test correct conversion from models coefficients to points that can be used for plotting.
Expecting no errors and updated dictionary
"""
# Acquire the models query profile
models_profile = profile_filter(postprocess_profiles,
'complexity-models.perf')
assert models_profile is not None
# Get all models and perform the conversion on all of them
# TODO: add more advanced checks
models = list(query.all_models_of(models_profile))
for model in models:
data = convert.plot_data_from_coefficients_of(model[1])
assert 'plot_x' in data
assert 'plot_y' in data
def draw_models(graph, models):
""" Add models renderers to the graph.
Arguments:
graph(charts.Graph): the scatter plot without models
models(list): list of models to plot
Returns:
charts.Graph: the modified graph with model curves renderers
"""
# Get unique colors for the model curves
colour_palette = palettes.viridis(len(models))
for idx, model in enumerate(models):
# Convert the coefficients to points that can be plotted
model = convert.plot_data_from_coefficients_of(model)
# Create legend for the plotted model
coeffs = ', '.join('{}={:f}'.format(c['name'], c['value']) for c in model['coeffs'])
legend = '{0}: {1}, r^2={2:f}'.format(model['model'], coeffs, model['r_square'])
# Plot the model
graph.line(x=model['plot_x'], y=model['plot_y'],
line_color=colour_palette[idx], line_width=2.5, legend=legend)
return graph