class PYT(tables.IsDescription):
a = tables.Int32Col()
b = tables.UInt8Col()
c = tables.Float32Col()
d = tables.StringCol(len(str(uuid4())) * 4)
e = tables.Time32Col()
f = tables.Time32Col()
class Volunteer(tables.IsDescription):
idnumber = tables.Int64Col(pos=0)
name = tables.StringCol(128, pos=1)
remarqs = tables.StringCol(128, pos=2) #
time_start = tables.Time32Col(pos=4, shape=MAX_DAYS)
time_end = tables.Time32Col(pos=5, shape=MAX_DAYS)
affected_tasks = tables.Int64Col(pos=3, shape=50, dflt=-1)
def test_create_weather_table(self):
description = {
'event_id': tables.UInt32Col(pos=0),
'timestamp': tables.Time32Col(pos=1),
'temp_inside': tables.Float32Col(pos=2),
'temp_outside': tables.Float32Col(pos=3),
'humidity_inside': tables.Int16Col(pos=4),
'humidity_outside': tables.Int16Col(pos=5),
'barometer': tables.Float32Col(pos=6),
'wind_dir': tables.Int16Col(pos=7),
'wind_speed': tables.Int16Col(pos=8),
'solar_rad': tables.Int16Col(pos=9),
'uv': tables.Int16Col(pos=10),
'evapotranspiration': tables.Float32Col(pos=11),
'rain_rate': tables.Float32Col(pos=12),
'heat_index': tables.Int16Col(pos=13),
'dew_point': tables.Float32Col(pos=14),
'wind_chill': tables.Float32Col(pos=15)
}
file = MagicMock()
result = esd._create_weather_table(file, sentinel.group)
file.create_table.assert_called_once_with(sentinel.group,
'weather',
description,
createparents=True)
self.assertEqual(result, file.create_table.return_value)
def test_create_table(self):
description = {
'event_id': tables.UInt32Col(pos=0),
'timestamp': tables.Time32Col(pos=1),
'nanoseconds': tables.UInt32Col(pos=2),
'ext_timestamp': tables.UInt64Col(pos=3),
'pulseheights': tables.Int16Col(pos=4, shape=4),
'integrals': tables.Int32Col(pos=5, shape=4),
'n1': tables.Float32Col(pos=6),
'n2': tables.Float32Col(pos=7),
'n3': tables.Float32Col(pos=8),
'n4': tables.Float32Col(pos=9),
't1': tables.Float32Col(pos=10),
't2': tables.Float32Col(pos=11),
't3': tables.Float32Col(pos=12),
't4': tables.Float32Col(pos=13),
't_trigger': tables.Float32Col(pos=14)
}
file = MagicMock()
result = esd._create_events_table(file, sentinel.group)
file.create_table.assert_called_once_with(sentinel.group,
'events',
description,
createparents=True)
self.assertEqual(result, file.create_table.return_value)
class LightningEvent(tables.IsDescription):
event_id = tables.UInt32Col(pos=0)
timestamp = tables.Time32Col(pos=1)
corr_distance = tables.Int16Col(pos=2)
uncorr_distance = tables.Int16Col(pos=3)
uncorr_angle = tables.Float32Col(pos=4)
corr_angle = tables.Float32Col(pos=5)
def reset_table():
"""Creates h5f flatfile for storing price data
Returns
-------
h5f handle : returns a writable file handle for pytables table
"""
h5f = tables.openFile('price_data.h5', 'w')
description = {
"ticker": tables.StringCol(itemsize=6, dflt='', pos=1),
"frequency": tables.StringCol(itemsize=1, dflt='d', pos=2),
"date": tables.Time32Col(dflt=0.00, pos=3),
"open": tables.Float32Col(dflt=0.00, pos=4),
"high": tables.Float32Col(dflt=0.00, pos=5),
"low": tables.Float32Col(dflt=0.00, pos=6),
"close": tables.Float32Col(dflt=0.00, pos=7),
"volume": tables.Int64Col(dflt=0.00, pos=8),
"adjustedClose": tables.Float32Col(dflt=0.00, pos=9),
"timestamp": tables.Time64Col(dflt=0.00, pos=10)
}
table = h5f.createTable('/', 'price_data', description)
h5f.close()
def _create_weather_table(file, group):
"""Create weather table in PyTables file
Create a weather table containing the ESD weather columns which are
available in the TSV download.
:param file: PyTables file.
:param group: the group to contain the weather table, which need not
exist.
"""
description = {
'event_id': tables.UInt32Col(pos=0),
'timestamp': tables.Time32Col(pos=1),
'temp_inside': tables.Float32Col(pos=2),
'temp_outside': tables.Float32Col(pos=3),
'humidity_inside': tables.Int16Col(pos=4),
'humidity_outside': tables.Int16Col(pos=5),
'barometer': tables.Float32Col(pos=6),
'wind_dir': tables.Int16Col(pos=7),
'wind_speed': tables.Int16Col(pos=8),
'solar_rad': tables.Int16Col(pos=9),
'uv': tables.Int16Col(pos=10),
'evapotranspiration': tables.Float32Col(pos=11),
'rain_rate': tables.Float32Col(pos=12),
'heat_index': tables.Int16Col(pos=13),
'dew_point': tables.Float32Col(pos=14),
'wind_chill': tables.Float32Col(pos=15)
}
return file.create_table(group, 'weather', description, createparents=True)
class WeatherConfig(tables.IsDescription):
event_id = tables.UInt32Col(pos=0)
timestamp = tables.Time32Col(pos=1)
com_port = tables.UInt8Col(pos=2)
baud_rate = tables.Int16Col(pos=3)
station_id = tables.UInt32Col(pos=4)
database_name = tables.Int32Col(dflt=-1, pos=5)
help_url = tables.Int32Col(dflt=-1, pos=6)
daq_mode = tables.BoolCol(pos=7)
latitude = tables.Float64Col(pos=8)
longitude = tables.Float64Col(pos=9)
altitude = tables.Float64Col(pos=10)
temperature_inside = tables.BoolCol(pos=11)
temperature_outside = tables.BoolCol(pos=12)
humidity_inside = tables.BoolCol(pos=13)
humidity_outside = tables.BoolCol(pos=14)
barometer = tables.BoolCol(pos=15)
wind_direction = tables.BoolCol(pos=16)
wind_speed = tables.BoolCol(pos=17)
solar_radiation = tables.BoolCol(pos=18)
uv_index = tables.BoolCol(pos=19)
evapotranspiration = tables.BoolCol(pos=20)
rain_rate = tables.BoolCol(pos=21)
heat_index = tables.BoolCol(pos=22)
dew_point = tables.BoolCol(pos=23)
wind_chill = tables.BoolCol(pos=24)
offset_inside_temperature = tables.Float32Col(pos=25)
offset_outside_temperature = tables.Float32Col(pos=26)
offset_inside_humidity = tables.Int16Col(pos=27)
offset_outside_humidity = tables.Int16Col(pos=28)
offset_wind_direction = tables.Int16Col(pos=29)
offset_station_altitude = tables.Float32Col(pos=30)
offset_bar_sea_level = tables.Float32Col(pos=31)
def _create_events_table(file, group):
"""Create event table in PyTables file
Create an event table containing the ESD data columns which are
available in the TSV download.
:param file: PyTables file.
:param group: the group to contain the events table, which need not
exist.
"""
description = {
'event_id': tables.UInt32Col(pos=0),
'timestamp': tables.Time32Col(pos=1),
'nanoseconds': tables.UInt32Col(pos=2),
'ext_timestamp': tables.UInt64Col(pos=3),
'pulseheights': tables.Int16Col(pos=4, shape=4),
'integrals': tables.Int32Col(pos=5, shape=4),
'n1': tables.Float32Col(pos=6),
'n2': tables.Float32Col(pos=7),
'n3': tables.Float32Col(pos=8),
'n4': tables.Float32Col(pos=9),
't1': tables.Float32Col(pos=10),
't2': tables.Float32Col(pos=11),
't3': tables.Float32Col(pos=12),
't4': tables.Float32Col(pos=13),
't_trigger': tables.Float32Col(pos=14)
}
return file.create_table(group, 'events', description, createparents=True)
def _create_singles_table(file, group):
"""Create singles table in PyTables file
Create a singles table containing the ESD singles columns which are
available in the TSV download.
:param file: PyTables file.
:param group: the group to contain the singles table, which need not
exist.
"""
description = {
'event_id': tables.UInt32Col(pos=0),
'timestamp': tables.Time32Col(pos=1),
'mas_ch1_low': tables.Int32Col(pos=2),
'mas_ch1_high': tables.Int32Col(pos=3),
'mas_ch2_low': tables.Int32Col(pos=4),
'mas_ch2_high': tables.Int32Col(pos=5),
'slv_ch1_low': tables.Int32Col(pos=6),
'slv_ch1_high': tables.Int32Col(pos=7),
'slv_ch2_low': tables.Int32Col(pos=8),
'slv_ch2_high': tables.Int32Col(pos=9)
}
return file.create_table(group, 'singles', description, createparents=True)
def _create_lightning_table(file, group):
"""Create lightning table in PyTables file
Create an lightning table containing the ESD data columns which are
available in the TSV download.
:param file: PyTables file.
:param group: the group to contain the lightning table, which need not
exist.
"""
description = {
'event_id': tables.UInt32Col(pos=0),
'timestamp': tables.Time32Col(pos=1),
'nanoseconds': tables.UInt32Col(pos=2),
'ext_timestamp': tables.UInt64Col(pos=3),
'latitude': tables.Float32Col(pos=4),
'longitude': tables.Float32Col(pos=5),
'current': tables.Float32Col(pos=6)
}
return file.create_table(group,
'lightning',
description,
createparents=True)
class Tasks(tables.IsDescription):
name = tables.StringCol(128, pos=3)
day = tables.Time32Col(pos=1)
idnumber = tables.Int64Col(pos=0)
task_type = tables.EnumCol(
['welcoming', 'balisage', 'logistics', 'security', 'race', 'other'],
'welcoming',
'int32',
pos=2)
time_start = tables.Time32Col(pos=4)
time_end = tables.Time32Col(pos=5)
N_needed = tables.Int8Col(pos=6)
N_filled = tables.Int8Col(pos=7)
remarqs = tables.StringCol(128, pos=8) #
stuff_needed = tables.StringCol(128, pos=9) #
affected_volunteers = tables.Int64Col(pos=10, shape=50, dflt=-1)
class HisparcComparatorData(tables.IsDescription):
event_id = tables.UInt32Col(pos=0)
timestamp = tables.Time32Col(pos=2)
nanoseconds = tables.UInt32Col(pos=3)
ext_timestamp = tables.UInt64Col(pos=4)
device = tables.UInt8Col(pos=5)
comparator = tables.UInt8Col(pos=6)
count = tables.UInt16Col(pos=7)
class LightningStatus(tables.IsDescription):
event_id = tables.UInt32Col(pos=0)
timestamp = tables.Time32Col(pos=1)
close_rate = tables.Int16Col(pos=2)
total_rate = tables.Int16Col(pos=3)
close_alarm = tables.BoolCol(pos=4)
sever_alarm = tables.BoolCol(pos=5)
current_heading = tables.Float32Col(pos=6)
class DescQuote(tb.IsDescription):
time = tb.Time32Col(pos=0) # Seconds since 1970.1.1): integer
open = tb.Float32Col(pos=1) # open price: float
high = tb.Float32Col(pos=2) # highest price: float
low = tb.Float32Col(pos=3) # lowest price: float
close = tb.Float32Col(pos=4) # close price: float
vol = tb.UInt32Col(pos=5) # volumn(100 share):
sum = tb.Float32Col(pos=6) # sum: float
class HisparcSatellite(tables.IsDescription):
event_id = tables.UInt32Col(pos=0)
timestamp = tables.Time32Col(pos=1)
min_n = tables.UInt16Col(pos=2)
mean_n = tables.Float32Col(pos=3)
max_n = tables.UInt16Col(pos=4)
min_signal = tables.UInt16Col(pos=5)
mean_signal = tables.Float32Col(pos=6)
max_signal = tables.UInt16Col(pos=7)
class HisparcEvent(tables.IsDescription):
event_id = tables.UInt64Col()
timestamp = tables.Time32Col()
nanoseconds = tables.UInt32Col()
ext_timestamp = tables.UInt64Col()
pulseheights = tables.Int16Col(shape=4, dflt=-9999)
integrals = tables.Int32Col(shape=4, dflt=-9999)
n_peaks = tables.Int32Col(shape=4, dflt=-9999)
traces = tables.Int32Col(shape=4, dflt=-1)
class DescSPLITS(tb.IsDescription):
""" struct: date, sending ratio(free), sending ratio (charged),
sending price, dividend
"""
time = tb.Time32Col(pos=0) # seconds ince 1970.1.1): integer
sd = tb.Float32Col(pos=1) # songgu ratio: float
ss = tb.Float32Col(pos=2) # peigu ratio: float
ssp = tb.Float32Col(pos=3) # peigu ratio: float
cd = tb.Float32Col(pos=4) # dividend: float
class Coincidence(tables.IsDescription):
"""Store information about a coincidence of stations within a cluster.
An extensive air shower can trigger multiple stations, resulting in a set
of events which are from the same shower. This is called a coincidence.
This table assigns an :attr:`id` to a coincidence and provides some
additional information. The events making up the coincidence can be looked
up using the :class:`c_index` table. Let ``coincidence`` be a row from
this table, then you can do::
>>> coincidence_id = coincidence['id']
>>> event_ids = c_index[coincidence_id]
>>> coincidence_event_list = [events[u] for u in event_ids]
Note that all events included in the coincidence are not required to
actually have measured particles. For example, simulations include all
events from the same shower in the coincidence, regardless of observed
particles. On the other hand, experimental datasets only include stations
which have triggered, but may include events which have not actually
measured the same shower, but simply measured other particles at the same
time, by chance.
Simulations may set the :attr:`r`, :attr:`phi`, :attr:`x`, :attr:`y` and
:attr:`alpha` attributes to simulation parameters, like core position and
cluster rotation.
.. attribute:: id
a unique identifier for the coincidence (only unique in this table)
.. attribute:: N
the number of triggered stations
.. attribute:: r, phi, x, y
The coordinates of the shower core in a simulation.
.. attribute:: shower_theta, shower_phi
The direction of the (simulated) shower.
"""
id = tables.UInt32Col()
timestamp = tables.Time32Col()
nanoseconds = tables.UInt32Col()
ext_timestamp = tables.UInt64Col()
N = tables.UInt8Col()
r = tables.Float32Col()
phi = tables.Float32Col()
x = tables.Float32Col()
y = tables.Float32Col()
shower_theta = tables.Float32Col()
shower_phi = tables.Float32Col()
shower_size = tables.Float32Col()
class Accessions(tables.IsDescription):
accession_id = tables.Int32Col()
name = tables.StringCol(16)
latitude = tables.Float32Col()
longitude = tables.Float32Col()
country = tables.StringCol(256)
country_ISO = tables.StringCol(3)
collector = tables.StringCol(256)
collection_date = tables.Time32Col()
dataset = tables.EnumCol(['10', '16', 'both'], '10', base='uint8')
class Accessions(tables.IsDescription):
accession_id = tables.Int32Col()
name = tables.StringCol(16)
latitude = tables.Float32Col()
longitude = tables.Float32Col()
country = tables.StringCol(256)
country_ISO = tables.StringCol(3)
collector = tables.StringCol(256)
collection_date = tables.Time32Col()
dataset = tables.StringCol(256)
class HisparcSingle(tables.IsDescription):
event_id = tables.UInt32Col(pos=0)
timestamp = tables.Time32Col(pos=1)
mas_ch1_low = tables.Int32Col(dflt=-1, pos=2)
mas_ch1_high = tables.Int32Col(dflt=-1, pos=3)
mas_ch2_low = tables.Int32Col(dflt=-1, pos=4)
mas_ch2_high = tables.Int32Col(dflt=-1, pos=5)
slv_ch1_low = tables.Int32Col(dflt=-1, pos=6)
slv_ch1_high = tables.Int32Col(dflt=-1, pos=7)
slv_ch2_low = tables.Int32Col(dflt=-1, pos=8)
slv_ch2_high = tables.Int32Col(dflt=-1, pos=9)
class Density(tb.IsDescription):
"""
trade density
Table structure:
- date: 날짜
- price: 가격
- value: 거래량
"""
date = tb.Time32Col(pos=0)
price = tb.Float64Col(pos=1)
value = tb.Float64Col(pos=2)
class EventObservables(tables.IsDescription):
"""Store information about the observables of an event.
The observables are described for each station independently. So, for each
event (with a unique :attr:`id`), there is a table row for each station
(with a unique :attr:`station_id`), such that only the (id, station_id)
combinations are unique in the table.
.. attribute:: id
a unique identifier for the simulated event (only unique in this table)
.. attribute:: station_id
station identifier, such that you can do::
>>> station = cluster.stations[station_id]
.. attribute:: r, phi, x, y
coordinates of the station. Depending on the simulation, this might be
constant throughout the simulation, or it might change event by event.
.. attribute:: alpha
rotation of the station around its center
.. attribute:: N
number of detectors with at least one particle
"""
id = tables.UInt32Col()
station_id = tables.UInt8Col()
timestamp = tables.Time32Col()
nanoseconds = tables.UInt32Col()
ext_timestamp = tables.UInt64Col()
r = tables.Float32Col()
phi = tables.Float32Col()
x = tables.Float32Col()
y = tables.Float32Col()
alpha = tables.Float32Col()
N = tables.UInt8Col()
t1 = tables.Float32Col()
t2 = tables.Float32Col()
t3 = tables.Float32Col()
t4 = tables.Float32Col()
n1 = tables.Float32Col()
n2 = tables.Float32Col()
n3 = tables.Float32Col()
n4 = tables.Float32Col()
class ConfigDescriptionLive(IsDescription):
cutoff_date = tables.Time32Col()
pres_start = tables.Time32Col()
id_assessment = tables.Int32Col()
assessment_name = tables.StringCol(16)
days_to_cutoff = tables.Int32Col()
current_date = tables.Time32Col()
train_labels_from = tables.Time32Col()
train_labels_to = tables.Time32Col()
test_labels_from = tables.Time32Col()
test_labels_to = tables.Time32Col()
class Coincidence(tables.IsDescription):
event_id = tables.UInt64Col()
k_event_id = tables.UInt64Col()
timestamp = tables.Time32Col()
nanoseconds = tables.UInt32Col()
ext_timestamp = tables.UInt64Col()
pulseheights = tables.Int16Col(shape=4, dflt=-9999)
integrals = tables.Int32Col(shape=4, dflt=-9999)
n_peaks = tables.Int32Col(shape=4, dflt=-9999)
traces = tables.Int32Col(shape=4, dflt=-1)
k_timestamp = tables.Time32Col()
k_nanoseconds = tables.UInt32Col()
k_ext_timestamp = tables.UInt64Col()
k_energy = tables.FloatCol()
k_core_pos = tables.FloatCol(shape=2)
k_zenith = tables.FloatCol()
k_azimuth = tables.FloatCol()
k_Num_e = tables.FloatCol()
k_Num_mu = tables.FloatCol()
k_dens_e = tables.FloatCol(shape=4)
k_dens_mu = tables.FloatCol(shape=4)
k_P200 = tables.FloatCol()
k_T200 = tables.FloatCol()
class GenomeTable(tables.IsDescription):
NCBITaxonId = tables.UInt32Col(pos=0)
UniProtSpeciesCode = tables.StringCol(5, pos=1)
TotEntries = tables.UInt32Col(pos=2)
TotAA = tables.UInt32Col(pos=3)
EntryOff = tables.UInt32Col(pos=4)
SciName = tables.StringCol(255, pos=5)
CommonName = tables.StringCol(64, pos=6)
SynName = tables.StringCol(64, pos=7)
Release = tables.StringCol(128, pos=8)
Url = tables.StringCol(255, pos=9)
Source = tables.StringCol(255, pos=10)
Date = tables.Time32Col(pos=11)
IsPolyploid = tables.BoolCol(pos=12)
class HisparcEvent(tables.IsDescription):
# DISCUSS: use of signed (dflt -1) vs unsigned (labview code)
event_id = tables.UInt32Col(pos=0)
timestamp = tables.Time32Col(pos=2)
nanoseconds = tables.UInt32Col(pos=3)
ext_timestamp = tables.UInt64Col(pos=4)
data_reduction = tables.BoolCol(pos=5)
trigger_pattern = tables.UInt32Col(pos=6)
baseline = tables.Int16Col(shape=4, dflt=-1, pos=7)
std_dev = tables.Int16Col(shape=4, dflt=-1, pos=8)
n_peaks = tables.Int16Col(shape=4, dflt=-1, pos=9)
pulseheights = tables.Int16Col(shape=4, dflt=-1, pos=10)
integrals = tables.Int32Col(shape=4, dflt=-1, pos=11)
traces = tables.Int32Col(shape=4, dflt=-1, pos=12)
event_rate = tables.Float32Col(pos=13)
class RunTable(tables.IsDescription):
run_id = tables.StringCol(40) # sha1 hashes are 40 char long
init_type = tables.StringCol(10)
datetime = tables.Time32Col()
num_links = tables.Int32Col()
sim_duration = tables.Float32Col()
sample_rate = tables.Float32Col()
sensor_noise = tables.BoolCol()
num_iterations = tables.Int32Col()
num_obj_evals = tables.Int32Col()
num_obj_grad_evals = tables.Int32Col()
num_con_evals = tables.Int32Col()
num_con_jac_evals = tables.Int32Col()
time_ipopt = tables.Float32Col()
time_func_evals = tables.Float32Col()
class Events(tables.IsDescription):
id = tables.Int32Col()
traces = tables.Float32Col(shape=(N_stations * 4, 80))
labels = tables.Float32Col(shape=3)
timings = tables.Float32Col(shape=4)
pulseheights = tables.Float32Col(shape=4)
integrals = tables.Float32Col(shape=4)
mips = tables.Float32Col(shape=4)
rec_z = tables.Float32Col()
rec_a = tables.Float32Col()
zenith = tables.Float32Col()
azimuth = tables.Float32Col()
timestamp = tables.Time32Col()
core_distance = tables.Float32Col()
mpv = tables.Float32Col()
energy = tables.Float32Col()
