Plot Regression Line
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| def plot_regression_line(regression_analyses): | |
| """ | |
| This global method is a front-end to the MatplotLib library which receives a set of regression analyses and plots | |
| each one of them onto the canvas. | |
| """ | |
| title = "" | |
| fig, ax = plot.subplots() | |
| # Plot each regression analysis in the set | |
| for regression_i in regression_analyses: | |
| ax.plot(regression_i.dates, regression_i.prices, regression_i.color, label="Values " + regression_i.data_set) | |
| ax.plot(regression_i.dates, regression_i.regression.fittedvalues, regression_i.color + '--', | |
| label="Regression line " + regression_i.data_set) | |
| if regression_i.lower is not None: | |
| ax.plot(regression_i.dates, regression_i.lower, regression_i.color + '--') | |
| if regression_i.upper is not None: | |
| ax.plot(regression_i.dates, regression_i.upper, regression_i.color + '--') | |
| plot.xlabel('Time') | |
| plot.ylabel('Normalized Values') | |
| title += regression_i.data_set + ", " |
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