credibility interval plotting

utilities.py

@@ -341,9 +341,11 @@ def plot_model_output(
  #line_color="red",
  mean_line_width=2,
  #background_color="black"
- show_grid=False, # new option to control grid lines
+ show_grid=True, # new option to control grid lines
  grid_alpha=0.1, # option to control the transparency of grid lines
  grid_style='dashed', # option to control the style of grid lines
+ plot_credibility_interval=True,
+ credibility_intervals=[0.5, 0.8, 0.95] # list of quantiles for intervals
 ):
  """
  This function plots the output of the financial life model.
@@ -395,18 +397,36 @@ def plot_model_output(
  # Transpose the data
  value = np.transpose(value)
 
+ # Plot mean path
  ax.plot(
  value.mean(axis=1),
  color=css.primary_color,
  alpha=mean_line_alpha,
  linewidth=mean_line_width,
- ) # plot mean path
-
- ax.plot(
- value, 
- color=css.primary_color, 
- alpha=alpha
- ) # plot individual paths
+ ) 
+
+ # Plot credibility intervals or individual paths
+ if plot_credibility_interval:
+ sorted_values = np.sort(value, axis=1) # sort values for each time step
+ for i in range(len(credibility_intervals)-1, -1, -1): # iterate over intervals in reverse order
+ lower_quantile = (1-credibility_intervals[i]) / 2 # calculate lower quantile
+ upper_quantile = 1 - lower_quantile # calculate upper quantile
+ ax.fill_between(
+ range(value.shape[0]), # x values (time steps)
+ np.quantile(sorted_values, lower_quantile, axis=1), # lower y values (lower quantile)
+ np.quantile(sorted_values, upper_quantile, axis=1), # upper y values (upper quantile)
+ color=css.primary_color, 
+ alpha=0.5 * (i + 1) / len(credibility_intervals), # transparency
+ label=f'{int(credibility_intervals[i]*100)}% credibility interval' # label for legend
+ )
+
+ ax.legend() # show legend
+ else:
+ ax.plot(
+ value, 
+ color=css.primary_color, 
+ alpha=alpha
+ ) 
 
  ax.set_title(key.replace("_", " ").title()) # prettify title
  ax.yaxis.set_major_formatter(formatter) # format y axis with comma separator