def get_month_after_limited(percent_change_file):
econ_seq = load_percent_change(percent_change_file)
sorted_econ = sorted(econ_seq, key=econ_seq.get)
for x in sorted_econ:
print (x, econ_seq[x])
# take top 10% as good months and bottom 10% as bad months
num = int(len(econ_seq) / 6)
prev_bad = sorted_econ[:num]
prev_good = sorted_econ[-num:]
prev_good = reversed(prev_good)
def plus_month(seq):
next_month = timedelta(days=31)
new_seq = []
year_to_count = defaultdict(int)
for x in seq:
if year_to_count[x.year] >= 2:
continue
year_to_count[x.year] += 1
new_date = x + next_month
floored_date = date(new_date.year, new_date.month, 1)
new_seq.append(floored_date)
return new_seq
return plus_month(prev_good), plus_month(prev_bad)
def get_same_month(percent_change_file):
econ_seq = load_percent_change(percent_change_file)
sorted_econ = sorted(econ_seq, key=econ_seq.get)
# take top 10% as good months and bottom 10% as bad months
num = int(len(econ_seq) / 6)
prev_bad = sorted_econ[:num]
prev_good = sorted_econ[-num:]
return prev_good, prev_bad
def get_month_just_after(percent_change_file):
econ_seq = load_percent_change(percent_change_file)
sorted_econ = sorted(econ_seq, key=econ_seq.get)
# take top 10% as good months and bottom 10% as bad months
num = int(len(econ_seq) / 6)
prev_bad = sorted_econ[:num]
prev_good = sorted_econ[-num:]
def plus_month(seq):
next_month = timedelta(days=31)
new_seq = []
for x in seq:
new_date = x + next_month
floored_date = date(new_date.year, new_date.month, 1)
new_seq.append(floored_date)
return new_seq
return plus_month(prev_good), plus_month(prev_bad)
def get_good_month_prev(percent_change_file, percent=6):
econ_seq = load_percent_change(percent_change_file)
sorted_econ = sorted(econ_seq, key=econ_seq.get)
# take top 10% as bad months and following 10% as good months
num = int(len(econ_seq) / percent)
prev_good = sorted_econ[-num:]
def plus_month(seq):
next_month = timedelta(days=31)
new_seq = []
for x in seq:
new_date = x + next_month
floored_date = date(new_date.year, new_date.month, 1)
new_seq.append(floored_date)
return new_seq
# take month of upturn as "bad" and next month as "good"
return plus_month(prev_good), prev_good
# take month of upturn as "good" and previous month as bad
return prev_good, minus_month(prev_good)
def main():
parser = argparse.ArgumentParser()
parser.add_argument(
"--percent_change",
default=
"/usr1/home/anjalief/corpora/russian/percent_change/russian_rtsi_rub.csv"
)
parser.add_argument(
"--input_path",
default="/usr1/home/anjalief/corpora/russian/yearly_mod_subs/iz_lower/"
)
parser.add_argument("--keywords", default="./keywords.txt")
args = parser.parse_args()
# DANGER DANGER DANGER
keywords = [l.strip() for l in open(args.keywords).readlines()]
econ_dict = load_percent_change(args.percent_change)
econ_seq = [econ_dict[d] for d in sorted(econ_dict)]
prior = LoadBackgroundCorpus(args.input_path)
frame_to_lex = pickle.load(open("frame_to_lex.pickle", "rb"))
date_seq, filenames = get_files_by_time_slice(args.input_path, "monthly")
prev_e = None
prev_i = None
frame_to_seq_e = defaultdict(list)
frame_to_seq_i = defaultdict(list)
for d, filename in zip(date_seq, filenames):
curr_e, curr_i, _, _, _ = LoadCountsExternal(filename, keywords)
if not prev_e:
prev_e = curr_e
prev_i = curr_i
continue
delta_e = write_log_odds(prev_e, curr_e, prior)
delta_i = write_log_odds(prev_i, curr_i, prior)
for c in frame_to_lex:
summary_e = 0
summary_i = 0
for word in frame_to_lex[c]:
if word in delta_e:
summary_e += delta_e[word]
else:
print("E Skipping ", word)
if word in delta_i:
summary_i += delta_i[word]
else:
print("I Skipping ", word)
frame_to_seq_e[c].append(summary_e)
frame_to_seq_i[c].append(summary_i)
prev_e = curr_e
prev_i = curr_i
# Done processing files
print(
"-------------------------------------------------------------------------------"
)
print("EXTERNAL")
print(
"-------------------------------------------------------------------------------"
)
for c in frame_to_seq_e:
print(c)
print_stats(econ_seq, frame_to_seq_e[c])
print(
"******************************************************************************"
)
print(
"-------------------------------------------------------------------------------"
)
print("INTERNAL")
print(
"-------------------------------------------------------------------------------"
)
for c in frame_to_seq_i:
print(c)
print_stats(econ_seq, frame_to_seq_i[c])
print(
"******************************************************************************"
)