def test_load():
import datetime
"""Load the historical data json file: list(dict(dict()))
Convert to list(list()), print, and return
"""
data=load_json(filename='data/bitcrawl_historical_data.json',verbose=False)
if not data: return data
columns=[]
for record in data:
if 'mtgox' in record.keys():
mtgox = record['mtgox']
columns.append([]) #add an empty row
if 'datetime' in mtgox.keys():
# add the time to the empty row
# leave it as a string and I'll convert to a value
dt = datetime.datetime.strptime(mtgox['datetime'][0:-6],"%Y-%m-%d %H:%M:%S.%f")
dt_value = float(dt.toordinal())+dt.hour/24.+dt.minute/24./60.+dt.second/24./3600.
columns[-1].append(dt_value)
if 'average' in mtgox.keys():
# float() won't work if there's a dollar sign in the price
value = float(mtgox['average'].strip().strip('$').strip())
# add the value to the last row
columns[-1].append(value)
import pprint
pprint.pprint(columns,indent=2)
return columns
)
p.add_argument(
'-f','--path','--filename',
type = str,
#nargs = '*', # other options '*','+', 2
default = bc.FILEPATH,
help = 'File to append the numerical data to (after converting to a string).',
)
return p.parse_args()
if __name__ == "__main__":
o = parse_args()
data = None
if not o.quiet or o.verbose:
data = bc.load_json(filepath=o.path,verbose=-2)
print o.graph
sites, values, datetimes = bc.parse_query(o.graph)
print 'sites',sites
print 'values',values
rows = bc.retrieve_data(sites,values,datetimes)
NM = size(rows)
assert NM[1]>=NM[0], size(rows)
#cols = bc.transpose_lists(rows)
bc.display_correlation(rows=rows, labels=o.graph, leads=o.lead)
#bc.plot_data(columns=cols,normalize=True)
if not o.nomine:
# mine hard-coded urls