Lint example
@@ -22,9 +22,10 @@ age_max = 54
cohorts = [1940, 1965, None]
# Find volatility profiles using the module
-variances = [sabelhaus_song_var_profile(age_min = age_min,
- age_max = age_max, cohort = c)
- for c in cohorts]
+variances = [
+ sabelhaus_song_var_profile(age_min=age_min, age_max=age_max, cohort=c)
+ for c in cohorts
+]
# %% Plots
@@ -32,9 +33,12 @@ variances = [sabelhaus_song_var_profile(age_min = age_min,
plt.figure()
for i in range(len(cohorts)):
- coh_label = 'aggregate' if cohorts[i] is None else cohorts[i]
- plt.plot(variances[i]['Age'], variances[i]['TranShkStd'],
- label = 'Tran. {} cohort'.format(coh_label))
+ coh_label = "aggregate" if cohorts[i] is None else cohorts[i]
+ plt.plot(
+ variances[i]["Age"],
+ variances[i]["TranShkStd"],
+ label="Tran. {} cohort".format(coh_label),
+ )
plt.legend()
@@ -42,8 +46,11 @@ plt.legend()
plt.figure()
for i in range(len(cohorts)):
- coh_label = 'aggregate' if cohorts[i] is None else cohorts[i]
- plt.plot(variances[i]['Age'], variances[i]['PermShkStd'],
- label = 'Perm. {} cohort'.format(coh_label))
+ coh_label = "aggregate" if cohorts[i] is None else cohorts[i]
+ plt.plot(
+ variances[i]["Age"],
+ variances[i]["PermShkStd"],
+ label="Perm. {} cohort".format(coh_label),
+ )
plt.legend()
