def getShapeOfKey(key):
ch = db.getChunkstore()
data = db.getLatestRow(ch, key)
data[key] = data[key].apply(
db.decodeObject) #decode it because we encode numpy arrays
val = data[key].values[-1] #get the latest item
return val.shape
def test_labels():
lib = db.getChunkstore()
#get the whole history of the course
course = db.loadData(lib, db.dbKeys['tick'], None, None, False)
filename = "data/dataset_test.pickle"
start = None
end = None
#generate a sample dataset
ds.run("matrix", "openPrice,closePrice,gasPrice", start, end, filename,
"boolean", '1', False)
sleep(1) #delay between saving and reading
with open(filename, 'rb') as f:
res = pickle.load(f) #load the result
i = 0
indices = course.index.values
for j, date in enumerate(res['dates']):
#
i = course.index[course['date'] == date]
#while course.get_value(indices[i], 'date') != date:
# i+=1
currPrice = course.get_value(i[0], 'close')
nextPrice = course.get_value(i[0] + 1, 'close')
#print("Checking prices %s %s with value of label %s" % (currPrice, nextPrice, res['labels'][j]))
if res['labels'][j] != (nextPrice > currPrice):
print(
"Debug info: Date %s at course index %s (len=%s). Curr / next prices are %s and %s."
% (date, i, len(course), currPrice, nextPrice))
assert False
assert True
from propertyGasPrice import PropertyGasPrice
from propertyGasUsed import PropertyGasUsed
from propertyHighPrice import PropertyHighPrice
from propertyLowPrice import PropertyLowPrice
from propertyNetworkHashrate import PropertyNetworkHashrate
from propertyOpenPrice import PropertyOpenPrice
#from propertyQuoteVolume import PropertyQuoteVolume
from propertyStickPrice import PropertyStickPrice
from propertyTransactionCount import PropertyTransactionCount
from propertyUniqueAccounts import PropertyUniqueAccounts
#from propertyVolume import PropertyVolume
from propertyVolumeFrom import PropertyVolumeFrom
from propertyVolumeTo import PropertyVolumeTo
#from propertyWeightedAverage import PropertyWeightedAverage
chunkStore = db.getChunkstore()
globalProperties = [
PropertyAccountBalanceDistribution(),
PropertyBalanceLastSeenDistribution(),
PropertyBlockDifficulty(),
PropertyBlockSize(),
PropertyClosePrice(),
PropertyGasLimit(),
PropertyGasPrice(),
PropertyGasUsed(),
PropertyHighPrice(),
PropertyLowPrice(),
PropertyNetworkHashrate(),
PropertyOpenPrice(),
PropertyStickPrice(),
default=None,
help='The end date. YYYY-MM-DD-HH')
args, _ = parser.parse_known_args()
start = dateutil.parser.parse(
args.start) if args.start is not None else None
end = dateutil.parser.parse(args.end) if args.end is not None else None
if args.type == 'file':
with open(args.data, 'rb') as f:
data = pickle.load(f)
if type(data) != list:
data = [data] #turn to single element list
for dataset in data:
values = dataset['dataset'][:, -1, args.index]
dates = dataset['dates']
print(values, dates)
plot(values, dates, 'Value of ' + args.data)
plot(dataset['labels'], dataset['dates'], 'Correct labels')
elif args.type == 'key':
data = db.loadData(db.getChunkstore(), args.data, start, end, True)
values = data[args.data].values
dates = data['date'].values
plot(values, dates, 'Value of ' + args.data)
frame = dataset['dataset'][
-1, -1, :, :] #shape is samples, layers, width, height
print(frame)
print(dataset['dataset'].shape)
print(dataset['dates'][-1])
plotImage(frame)
if args.target:
plot(dataset['labels'], dataset['dates'],
'Correct labels')
elif args.type == 'key':
prop = args.data
data = db.loadData(db.getChunkstore(), prop, start, end, True)
if type(
data.iloc[0][prop]
) == str: #if the property values have been encoded, decode them
print("Running numpy array Arctic workaround for prop %s..." %
prop)
data[prop] = data[prop].apply(lambda x: db.decodeObject(x))
values = data[prop].values
dates = data['date'].values
if type(values[0]) != np.ndarray:
plot(values, dates, 'Value of ' + prop)
else: #if we are dealing with complex property, visualize it
if args.renderTimelapse is not None:
def test_connection():
lib = db.getChunkstore()
assert lib
def __init__(self):
super().__init__()
self.name = 'blockchain'
self.store = db.getChunkstore()
self.id_cache = None
