from scipy.stats import norm from general_setup import smooth_data,median_over_months,sum_over_patterns,filter_for_specific_day,plot_me from load_data import good_XXth_data,bad_XXth_data,bad_nth_data # Good medians good_XXth_medians = median_over_months(good_XXth_data) good_XXth_medians_smooth = smooth_data(good_XXth_medians, 5) # The day of interest only_11th = filter_for_specific_day(good_XXth_data, '11th') only_11th_medians_smooth = good_XXth_medians_smooth[['year','11th']] # Bad sums sum_bad_XXth = sum_over_patterns(bad_XXth_data, new_name='badth') # Sum of good and bad sum_bad_XXth_and_11th = sum_over_patterns(only_11th.merge(bad_XXth_data, on='year'), new_name='allth') sum_bad_XXth_and_11th_medians = median_over_months(sum_bad_XXth_and_11th) sum_bad_XXth_and_11th_medians_smooth = smooth_data(sum_bad_XXth_and_11th_medians, 5) # Difference between good and sum of bad and good (not necessarily equal to sum of bad alone) sum_XXth_minus_bad_medians = sum_bad_XXth_and_11th_medians.copy() sum_XXth_minus_bad_medians.columns = ['year', 'diffth'] sum_XXth_minus_bad_medians['diffth'] = sum_bad_XXth_and_11th_medians['allth'] - good_XXth_medians['11th'] sum_XXth_minus_bad_medians_smooth = smooth_data(sum_XXth_minus_bad_medians) # Sum of good and nth sum_bad_11th_and_nth = sum_over_patterns(only_11th.merge(bad_nth_data, on='year'), new_name='allth') sum_bad_11th_and_nth_medians = median_over_months(sum_bad_11th_and_nth)
from scipy.stats import norm
from general_setup import smooth_data, median_over_months, sum_over_patterns, filter_for_specific_day, plot_me
from load_data import good_XXth_data, bad_XXth_data, bad_nth_data
# Good medians
good_XXth_medians = median_over_months(good_XXth_data)
good_XXth_medians_smooth = smooth_data(good_XXth_medians, 5)
# The day of interest
only_11th = filter_for_specific_day(good_XXth_data, '11th')
only_11th_medians_smooth = good_XXth_medians_smooth[['year', '11th']]
# Bad sums
sum_bad_XXth = sum_over_patterns(bad_XXth_data, new_name='badth')
# Sum of good and bad
sum_bad_XXth_and_11th = sum_over_patterns(only_11th.merge(bad_XXth_data,
on='year'),
new_name='allth')
sum_bad_XXth_and_11th_medians = median_over_months(sum_bad_XXth_and_11th)
sum_bad_XXth_and_11th_medians_smooth = smooth_data(
sum_bad_XXth_and_11th_medians, 5)
# Difference between good and sum of bad and good (not necessarily equal to sum of bad alone)
sum_XXth_minus_bad_medians = sum_bad_XXth_and_11th_medians.copy()
sum_XXth_minus_bad_medians.columns = ['year', 'diffth']
sum_XXth_minus_bad_medians['diffth'] = sum_bad_XXth_and_11th_medians[
'allth'] - good_XXth_medians['11th']
sum_XXth_minus_bad_medians_smooth = smooth_data(sum_XXth_minus_bad_medians)
old_style_medians_smooth = smooth_data(old_style_medians) # Extract new-style days only_2nd = filter_for_specific_day(good_XXth_data, '2nd') only_3rd = filter_for_specific_day(good_XXth_data, '3rd') only_22nd = filter_for_specific_day(good_XXth_data, '22nd') only_23rd = filter_for_specific_day(good_XXth_data, '23rd') # Extract old-style days only_2d = filter_for_specific_day(old_style_data, '2d') only_3d = filter_for_specific_day(old_style_data, '3d') only_22d = filter_for_specific_day(old_style_data, '22d') only_23d = filter_for_specific_day(old_style_data, '23d') # Sum old and new style sum_2nd_2d = sum_over_patterns(only_2nd.merge(only_2d, on='year'), new_name='2xx') sum_3rd_3d = sum_over_patterns(only_3rd.merge(only_3d, on='year'), new_name='3xx') sum_22nd_22d = sum_over_patterns(only_22nd.merge(only_22d, on='year'), new_name='22xx') sum_23rd_23d = sum_over_patterns(only_23rd.merge(only_23d, on='year'), new_name='23xx') # Merge data sum_new_old = merge_data(sum_2nd_2d, sum_3rd_3d, sum_22nd_22d, sum_23rd_23d) sum_new_old_medians = median_over_months(sum_new_old) sum_new_old_medians_smooth = smooth_data(sum_new_old_medians) # Plot new-style ax = plot_me(good_XXth_medians_smooth) ax.plot(good_XXth_medians_smooth['year'], good_XXth_medians_smooth['2nd'], 'g-', linewidth=4) ax.plot(good_XXth_medians_smooth['year'], good_XXth_medians_smooth['3rd'], 'r-', linewidth=4) ax.plot(good_XXth_medians_smooth['year'], good_XXth_medians_smooth['22nd'], 'c-', linewidth=4) ax.plot(good_XXth_medians_smooth['year'], good_XXth_medians_smooth['23rd'], 'm-', linewidth=4)
old_style_medians_smooth = smooth_data(old_style_medians)
# Extract new-style days
only_2nd = filter_for_specific_day(good_XXth_data, '2nd')
only_3rd = filter_for_specific_day(good_XXth_data, '3rd')
only_22nd = filter_for_specific_day(good_XXth_data, '22nd')
only_23rd = filter_for_specific_day(good_XXth_data, '23rd')
# Extract old-style days
only_2d = filter_for_specific_day(old_style_data, '2d')
only_3d = filter_for_specific_day(old_style_data, '3d')
only_22d = filter_for_specific_day(old_style_data, '22d')
only_23d = filter_for_specific_day(old_style_data, '23d')
# Sum old and new style
sum_2nd_2d = sum_over_patterns(only_2nd.merge(only_2d, on='year'),
new_name='2xx')
sum_3rd_3d = sum_over_patterns(only_3rd.merge(only_3d, on='year'),
new_name='3xx')
sum_22nd_22d = sum_over_patterns(only_22nd.merge(only_22d, on='year'),
new_name='22xx')
sum_23rd_23d = sum_over_patterns(only_23rd.merge(only_23d, on='year'),
new_name='23xx')
# Merge data
sum_new_old = merge_data(sum_2nd_2d, sum_3rd_3d, sum_22nd_22d, sum_23rd_23d)
sum_new_old_medians = median_over_months(sum_new_old)
sum_new_old_medians_smooth = smooth_data(sum_new_old_medians)
# Plot new-style
ax = plot_me(good_XXth_medians_smooth)
ax.plot(good_XXth_medians_smooth['year'],