def pd_acct_balances(self, company_id, dates, paths=None, acct_list=None, excl_contra=None, excl_interco=False, cp=None, with_tags=None, excl_tags=None):
if not acct_list:
if paths:
accts = list(itertools.chain(*[api_func('gl', 'path_accounts', p) for p in paths]))
acct_list = [x['id'] for x in accts]
else:
acct_list = [x['id'] for x in api_func('gl', 'path_accounts', '')]
dates_dict = dict((dt, utils.get_dates_dict(dates[dt])) for dt in dates)
with_counterparties = [cp.id] if cp else None
date_indexed_account_balances = self.gl_strategy.account_balances_for_dates(company_id, acct_list, dates_dict, with_counterparties, excl_interco, excl_contra, with_tags, excl_tags)
# filter empties
for dt in date_indexed_account_balances:
d = date_indexed_account_balances[dt]
date_indexed_account_balances[dt] = {k:d[k] for k in d if d[k] != 0.0}
output = pd.DataFrame(date_indexed_account_balances)
if paths:
a = [[x['id'] for x in api_func('gl', 'path_accounts', path)] for path in paths]
accts_list = list(itertools.chain(*a))
return output[output.index.isin(acct_list)]
elif acct_list:
filtered_output = output[output.index.isin(acct_list)]
return filtered_output
return output
def pd_path_balances(self, company_id, dates, paths, filter_zeros=True, assets=False, excl_contra=None, excl_interco=False, with_tags=None, excl_tags=None):
path_accts = dict((p, [x['id'] for x in api_func('gl', 'path_accounts', p)]) for p in paths)
acct_list = list(itertools.chain(*[path_accts[p] for p in paths]))
dates_dict = dict((dt, utils.get_dates_dict(dates[dt])) for dt in dates)
date_indexed_account_balances = self.gl_strategy.account_balances_for_dates(company_id, acct_list, dates_dict, None, excl_interco, excl_contra, with_tags, excl_tags)
data = {}
for dt in date_indexed_account_balances:
account_balances = date_indexed_account_balances[dt]
tuples = []
for path in paths:
path_sum = 0
for account_id in path_accts[path]:
if account_id in account_balances:
path_sum -= account_balances[account_id]
tuples.append((path, path_sum))
data[dt] = dict(tuples)
output = pd.DataFrame(data)
if filter_zeros:
output['empty'] = output.apply(lambda row: np.all(row.values == 0.0), axis=1)
output = output[output['empty']==False]
output.drop('empty', axis=1, inplace=True)
# adjust assets sign
if assets:
asset_factor = output.index.map(lambda x: -1.0 if x[:6] == 'assets' else 1.0)
for col in output.columns:
output[col] = output[col] * asset_factor
return output
def pd_path_balances(self,
company_id,
dates,
paths,
filter_zeros=True,
assets=False,
excl_contra=None,
excl_interco=False,
with_tags=None,
excl_tags=None):
path_accts = dict(
(p, [x['id'] for x in api_func('gl', 'path_accounts', p)])
for p in paths)
acct_list = list(itertools.chain(*[path_accts[p] for p in paths]))
dates_dict = dict(
(dt, utils.get_dates_dict(dates[dt])) for dt in dates)
date_indexed_account_balances = self.gl_strategy.account_balances_for_dates(
company_id, acct_list, dates_dict, None, excl_interco, excl_contra,
with_tags, excl_tags)
data = {}
for dt in date_indexed_account_balances:
account_balances = date_indexed_account_balances[dt]
tuples = []
for path in paths:
path_sum = 0
for account_id in path_accts[path]:
if account_id in account_balances:
path_sum -= account_balances[account_id]
tuples.append((path, path_sum))
data[dt] = dict(tuples)
output = pd.DataFrame(data)
if filter_zeros:
output['empty'] = output.apply(
lambda row: np.all(row.values == 0.0), axis=1)
output = output[output['empty'] == False]
output.drop('empty', axis=1, inplace=True)
# adjust assets sign
if assets:
asset_factor = output.index.map(lambda x: -1.0
if x[:6] == 'assets' else 1.0)
for col in output.columns:
output[col] = output[col] * asset_factor
return output
def pd_acct_balances(self,
company_id,
dates,
paths=None,
acct_list=None,
excl_contra=None,
excl_interco=False,
cp=None,
with_tags=None,
excl_tags=None):
if not acct_list:
if paths:
accts = list(
itertools.chain(
*[api_func('gl', 'path_accounts', p) for p in paths]))
acct_list = [x['id'] for x in accts]
else:
acct_list = [
x['id'] for x in api_func('gl', 'path_accounts', '')
]
dates_dict = dict(
(dt, utils.get_dates_dict(dates[dt])) for dt in dates)
with_counterparties = [cp.id] if cp else None
date_indexed_account_balances = self.gl_strategy.account_balances_for_dates(
company_id, acct_list, dates_dict, with_counterparties,
excl_interco, excl_contra, with_tags, excl_tags)
# filter empties
for dt in date_indexed_account_balances:
d = date_indexed_account_balances[dt]
date_indexed_account_balances[dt] = {
k: d[k]
for k in d if d[k] != 0.0
}
output = pd.DataFrame(date_indexed_account_balances)
if paths:
a = [[x['id'] for x in api_func('gl', 'path_accounts', path)]
for path in paths]
accts_list = list(itertools.chain(*a))
return output[output.index.isin(acct_list)]
elif acct_list:
filtered_output = output[output.index.isin(acct_list)]
return filtered_output
return output
