class TelTableRow(IsDescription):
"""Describe row format for telescope type table.
Contains parameter information for each telescope type in the data. NOTE:
Additional columns are added dynamically to some tables,
see the github wiki page for the full table/data format descriptions.
Attributes
----------
type : tables.StringCol
Telescope type name (i.e. 'LST:LSTCam')
optics : tables.StringCol
Telescope optics type name (i.e. 'LST').
camera : tables.StringCol
Telescope camera type name (i.e. 'LSTCam').
num_pixels: tables.UInt32Col
Number of pixels in the telescope camera.
pix_rotation: tables.Float32Col
Rotation angle in deg.
cam_rotation: tables.Float32Col
Overall camera rotation in deg.
"""
type = StringCol(20)
optics = StringCol(20)
camera = StringCol(20)
num_pixels = UInt32Col()
pix_rotation = Float32Col()
cam_rotation = Float32Col()
class Test_GrainData(IsDescription):
"""
Description class specifying structured storage for tests
"""
idnumber = Int32Col() # Signed 64-bit integer
volume = Float32Col() # float
center = Float32Col(shape=(3, )) # float
class Array(IsDescription):
"""Row descriptor class for Pytables array data table.
Contains parameter information for each selected telescope
in the data.
Attributes
----------
tel_id : UInt8Col
UInt8 placeholder type for the telescope id (in the array)
tel_x : Float32Col
Float32 placeholder type for the telescope position x coordinate
relative to the center of the array.
tel_y : Float32Col
Float32 placeholder type for the telescope position y coordinate
relative to the center of the array.
tel_z : Float32Col
Float32 placeholder type for the telescope position z coordinate
(height) relative to the CORSIKA observatory altitude.
tel_type : StringCol
String placeholder type for the telescope type name (i.e. 'LST')
run_array_direction: Float32Col(2)
Float32 tuple placeholder type for the array pointing direction for
a given run (az,alt)
"""
tel_id = UInt8Col()
tel_x = Float32Col()
tel_y = Float32Col()
tel_z = Float32Col()
tel_type = StringCol(8)
run_array_direction = Float32Col(2)
class PowerScanTableDescription(IsDescription):
"""
"""
power_requested = Float32Col()
power_achieved = Float32Col()
voltage = Float32Col()
class ArrayTableRow(IsDescription):
"""Describe row format for telescope array table.
Contains parameter information for each telescope in the array.
NOTE: Additional columns are added dynamically to some tables, see the
github wiki page for the full table/data format descriptions.
Attributes
----------
id : tables.UInt8Col
Telescope id (unique).
type : tables.StringCol
Telescope type name (i.e. 'LST:LSTCam').
x : tables.Float32Col
Telescope position x coordinate relative to the center of the array.
y : tables.Float32Col
Telescope position y coordinate relative to the center of the array.
z : tables.Float32Col
Telescope position z coordinate (height) relative to the CORSIKA
observatory altitude.
"""
id = UInt16Col()
type = StringCol(20)
x = Float32Col()
y = Float32Col()
z = Float32Col()
class CameraScanTableDescription(IsDescription):
"""
"""
setpoint = Float32Col()
frame_path = StringCol(140)
ravg = Float32Col()
gavg = Float32Col()
bavg = Float32Col()
class PowerMapTableDescription(IsDescription):
"""
"""
row = Float32Col()
col = Float32Col()
x = Float32Col()
y = Float32Col()
power = Float32Col()
class StrokelitudeDataDescription(IsDescription):
frame = UInt64Col(pos=0)
trigger_timestamp = FloatCol(pos=1) # when the image trigger happened
processing_timestamp = FloatCol(pos=2) # when the analysis was done
left = Float32Col(pos=3) # angle, degrees
right = Float32Col(pos=4) # angle, degrees
left_antenna = Float32Col(pos=5) # angle, degrees
right_antenna = Float32Col(pos=6) # angle, degrees
head = Float32Col(pos=7) # angle, degrees
class EventTableRow(IsDescription):
"""Describe row format for event table.
Contains event-level information, mostly from Monte Carlo simulation
parameters. NOTE: Additional columns are added dynamically to some tables,
see the github wiki page for the full table/data format descriptions.
Attributes
----------
event_id : tables.UInt32Col
Shower event id.
obs_id : tables.UInt32Col
Shower observation (run) id. Replaces old "run_id" in ctapipe r0
container.
true_shower_primary_id : tables.UInt8Col
Particle type id for the shower primary particle. From Monte Carlo
simulation parameters.
true_core_x : tables.Float32Col
Shower core position x coordinate. From Monte Carlo simulation
parameters.
true_core_y : tables.Float32Col
Shower core position y coordinate. From Monte Carlo simulation
parameters.
true_h_first_int : tables.Float32Col
Height of shower primary particle first interaction. From Monte Carlo
simulation parameters.
true_energy : tables.Float32Col
Energy of the shower primary particle in TeV. From Monte Carlo simulation
parameters.
log_true_energy : tables.Float32Col
Energy of the shower primary particle in log(TeV). From Monte Carlo simulation
parameters.
true_az : tables.Float32Col
Shower azimuth angle. From Monte Carlo simulation parameters.
true_alt : tables.Float32Col
Shower altitude (zenith) angle. From Monte Carlo simulation parameters.
array_pointing_az : tables.Float32Col
Array pointing azimuth angle.
array_pointing_alt : tables.Float32Col
Array pointing altitude (zenith) angle.
"""
event_id = UInt32Col()
obs_id = UInt32Col()
true_shower_primary_id = UInt8Col()
true_core_x = Float32Col()
true_core_y = Float32Col()
true_h_first_int = Float32Col()
true_x_max = Float32Col()
true_energy = Float32Col()
log_true_energy = Float32Col()
true_az = Float32Col()
true_alt = Float32Col()
array_pointing_az = Float32Col()
array_pointing_alt = Float32Col()
class SSelectorOnMeshElement(IsDescription):
shortName = StringCol(ELEMENT_LENGTH, pos=0)
imin = Int32Col(pos=1)
jmin = Int32Col(pos=2)
kmin = Int32Col(pos=3)
imax = Int32Col(pos=4)
jmax = Int32Col(pos=5)
kmax = Int32Col(pos=6)
v1 = Float32Col()
v2 = Float32Col()
v3 = Float32Col()
class ncdf_weather(IsDescription):
day = Time32Col(pos=1)
tmax = Float32Col(pos=2)
tmin = Float32Col(pos=3)
temp = Float32Col(pos=4)
rain = Float32Col(pos=5)
irrad = Float32Col(pos=6)
wind = Float32Col(pos=7)
vap = Float32Col(pos=8)
e0 = Float32Col(pos=9)
es0 = Float32Col(pos=10)
et0 = Float32Col(pos=11);
class Preopen(IsDescription):
symbol = StringCol(50)
xDt = StringCol(50)
caAct = StringCol(50)
iep = Float32Col()
chn = Float16Col()
perChn = Float16Col()
pCls = Float32Col()
trdQnty = Int32Col()
iVal = Float16Col()
sumVal = Float32Col()
sumQnty = Int32Col()
finQnty = Int32Col()
sumfinQnty = Int32Col()
class Derivative(IsDescription):
INSTRUMENT = StringCol(6)
SYMBOL = StringCol(50)
EXPIRY_DT = StringCol(11)
STRIKE_PR = Int32Col()
OPTION_TYP = StringCol(2)
OPEN = Float32Col()
HIGH = Float32Col()
LOW = Float32Col()
CLOSE = Float32Col()
SETTLE_PR = Float32Col()
CONTRACTS = Int32Col()
VAL_INLAKH = Float64Col()
OPEN_INT = Int32Col()
CHG_IN_OI = Int32Col()
TIMESTAMP = StringCol(11)
class SSReadoutTableDs(IsDescription):
iro = UInt64Col() # readout numner/index
time = UInt64Col() # TACK timestamp
cpu_t = Float64Col() # native python timestamp float64
cpu_t_s = UInt64Col() # seconds time stamp uint64
cpu_t_ns = UInt64Col() # nano seconds time stamp uint64
data = Float32Col((N_TM, N_TM_PIX)) # 2D data array containing
class Record(tables.IsDescription):
var1 = StringCol(itemsize=4, dflt=b"abcd", pos=0)
var2 = StringCol(itemsize=1, dflt=b"a", pos=1)
var3 = BoolCol(dflt=1)
var4 = Int8Col(dflt=1)
var5 = UInt8Col(dflt=1)
var6 = Int16Col(dflt=1)
var7 = UInt16Col(dflt=1)
var8 = Int32Col(dflt=1)
var9 = UInt32Col(dflt=1)
var10 = Int64Col(dflt=1)
var11 = Float32Col(dflt=1.0)
var12 = Float64Col(dflt=1.0)
var13 = ComplexCol(itemsize=8, dflt=(1. + 0.j))
var14 = ComplexCol(itemsize=16, dflt=(1. + 0.j))
if hasattr(tables, 'Float16Col'):
var15 = tables.Float16Col(dflt=1.0)
if hasattr(tables, 'Float96Col'):
var16 = tables.Float96Col(dflt=1.0)
if hasattr(tables, 'Float128Col'):
var17 = tables.Float128Col(dflt=1.0)
if hasattr(tables, 'Complex196Col'):
var18 = tables.ComplexCol(itemsize=24, dflt=(1. + 0.j))
if hasattr(tables, 'Complex256Col'):
var19 = tables.ComplexCol(itemsize=32, dflt=(1. + 0.j))
class _VariantDescription(IsDescription):
CHROM = StringCol(256)
POS = Int32Col()
ID = StringCol(256)
REF = StringCol(256)
ALT = StringCol(256)
QUAL = Float32Col()
CAF = StringCol(256)
CLNDISDB = StringCol(256)
CLNDN = StringCol(256)
CLNSIG = StringCol(256)
CLNREVSTAT = StringCol(256)
CLNVI = StringCol(256)
effect = StringCol(256)
impact = StringCol(256)
gene_name = StringCol(256)
GT = StringCol(256)
class TwoGenomeWideAssociationLocusMapTable(tables.IsDescription):
"""
2013.1.26 further attributes associated with this table:
input1_fname, input2_fname,
gw_association_locus1 (id, call-method, analysis-method-ls), gw_association_locus2 (id, cm, am)
if "pos=.." is not added, they are sorted alphabetically by their names.
"""
id = UInt64Col(pos=0)
#2013.2.24 overall position of the locus
chromosome = StringCol(64, pos=1) #64 byte-long
start = UInt64Col(pos=2)
stop = UInt64Col(pos=3)
input1_locus_id = UInt64Col(pos=4)
input1_chromosome = StringCol(64, pos=5)
input1_start = UInt64Col(pos=6)
input1_stop = UInt64Col(pos=7)
input2_locus_id = UInt64Col(pos=8)
input2_chromosome = StringCol(64, pos=9)
input2_start = UInt64Col(pos=10)
input2_stop = UInt64Col(pos=11)
locusOverlapFraction = Float64Col(pos=12)
no_of_total_phenotypes = UInt32Col(pos=13) #all significant phenotypes
total_phenotype_ls_in_str = StringCol(1000, pos=14)
fraction_of_total_phenotypes = Float32Col(
pos=15) #divided by all phenotypes with association
no_of_overlap_phenotypes = UInt32Col(pos=16)
overlap_phenotype_ls_in_str = StringCol(1000, pos=17)
fraction_of_overlap_phenotypes = Float32Col(
pos=18
) #divided by the no_of_total_phenotypes (3 cols above, with significant hits)
no_of_input1_only_phenotypes = UInt32Col(pos=19)
input1_only_phenotype_ls_in_str = StringCol(1000, pos=20)
fraction_of_input1_only_phenotypes = Float32Col(pos=21)
no_of_input2_only_phenotypes = UInt32Col(pos=22)
input2_only_phenotype_ls_in_str = StringCol(1000, pos=23)
fraction_of_input2_only_phenotypes = Float32Col(pos=24)
class Particle(IsDescription):
name = StringCol(16) # 16-character String
idnumber = Int64Col() # Signed 64-bit integer
ADCcount = UInt16Col() # Unsigned short integer
TDCcount = UInt8Col() # unsigned byte
grid_i = Int32Col() # 32-bit integer
grid_j = Int32Col() # 32-bit integer
pressure = Float32Col() # float (single-precision)
energy = Float64Col() # double (double-precision)
def setup_peakmap_table(self):
if not hasattr(self.node, "pm_table"):
description = {}
description["unique_id"] = StringCol(itemsize=64, pos=0)
description["index"] = UInt32Col(pos=1)
description["ms_levels"] = StringCol(
itemsize=self.MSLEVEL_FIELD_SIZE, pos=2)
description["rtmin"] = Float32Col(pos=3)
description["rtmax"] = Float32Col(pos=4)
description["mzmin"] = Float32Col(pos=5)
description["mzmax"] = Float32Col(pos=6)
pm_table = self.file_.create_table(self.node,
'pm_table',
description,
filters=filters)
# every colums which appears in a where method call should/must be indexed !
# this is not only for performance but for correct lookup as well (I had strange bugs
# else)
pm_table.cols.unique_id.create_index()
pm_table.cols.index.create_index()
def init_dynamic_scalars_and_fields(self, shape, scalars, fields):
# create scalars tab
self.dynamic_scalars = set(scalars)
cols_desc = {c: Float64Col() for c in scalars}
cols_desc['t'] = Float32Col()
self.tab_dynamic_scalars = self.f.create_table(self.f.root,
'dynamic_scalars',
cols_desc,
'Dynamic scalars')
self.tab_dynamic_scalars.row.append()
self.tab_dynamic_scalars.flush()
# create fields tab
self.dynamic_fields = set(fields)
cols_desc = {f: Float64Col(shape) for f in fields}
cols_desc['t'] = Float32Col()
self.tab_dynamic_fields = self.f.create_table(self.f.root,
'dynamic_fields',
cols_desc,
'Dynamic fields')
# snapshot
self.snapshot(t=0.0, **scalars, **fields)
def setup_spec_table(self):
if not hasattr(self.node, "ms1_spec_table"):
for level in (1, 2):
description = {}
description["pm_index"] = UInt32Col(pos=0)
description["rt"] = Float32Col(pos=1)
description["scan_number"] = Int32Col(pos=2)
description["start"] = UInt64Col(pos=3)
description["end"] = UInt64Col(pos=4)
t = self.file_.create_table(self.node, 'ms%d_spec_table' % level, description,
filters=filters)
# every colums which appears in a where method call should/must be indexed !
# this is not only for performance but for correct lookup as well (I had strange bugs
# else)
t.cols.pm_index.create_index()
t.cols.rt.create_index()
class StrokelitudeDataDescription(IsDescription):
frame = UInt64Col(pos=0)
trigger_timestamp = FloatCol(pos=1) # when the image trigger happened
processing_timestamp = FloatCol(pos=2) # when the analysis was done
left = Float32Col(pos=3) # angle, degrees
right = Float32Col(pos=4) # angle, degrees
left_antenna = Float32Col(pos=5) # angle, degrees
right_antenna = Float32Col(pos=6) # angle, degrees
head = Float32Col(pos=7) # angle, degrees
pulse_width = Float32Col(
pos=8) # random pulse width, 0 = short, 1 = long, 2 = unknown
pulse_frame = UInt64Col(pos=9) # frame number associated with random pulse
def setup_spec_table(self):
if not hasattr(self.node, "spec_table"):
description = {}
description["pm_index"] = UInt32Col(pos=0)
description["rt"] = Float32Col(pos=1)
description["ms_level"] = UInt8Col(pos=2)
description["start"] = UInt64Col(pos=3)
description["size"] = UInt32Col(pos=4)
spec_table = self.file_.create_table(self.node,
'spec_table',
description,
filters=filters)
# every colums which appears in a where method call should/must be indexed !
# this is not only for performance but for correct lookup as well (I had strange bugs
# else)
spec_table.cols.pm_index.create_index()
spec_table.cols.rt.create_index()
class Tel(IsDescription):
"""Row descriptor class for Pytables telescope data table.
Contains parameter information for each selected telescope
in the data.
Attributes
----------
tel_type : StringCol
String placeholder type for the telescope type name (i.e. 'LST')
num_pixels: UInt32Col
UInt32 placeholder type for telescope's number of pixels
pixel_pos: Float32Col
Float32Col placeholder type for pixel's coordinates
"""
tel_type = StringCol(8)
num_pixels = UInt32Col()
pixel_pos = Float32Col(2)
class Equity(IsDescription):
SYMBOL = StringCol(50)
SERIES = StringCol(2)
OPEN = Float32Col()
HIGH = Float32Col()
LOW = Float32Col()
CLOSE = Float32Col()
LAST = Float32Col()
PREVCLOSE = Float32Col()
TOTTRDQTY = Int32Col()
TOTTRDVAL = Float64Col()
TIMESTAMP = StringCol(12)
TOTALTRADES = Int32Col()
ISIN = StringCol(12)
class _VariantDescription(IsDescription):
"""
Describe VariantHDF5 table columns.
"""
# TODO: Optimize
CHROM = StringCol(8)
POS = Int32Col()
ID = StringCol(16)
REF = StringCol(256)
ALT = StringCol(256)
QUAL = Float32Col()
# INFO
CAF = StringCol(16)
CLNSIG = StringCol(8)
CLNDBN = StringCol(256)
# INFO ANN
effect = StringCol(32)
impact = StringCol(32)
gene_name = StringCol(32)
# FORMAT & sample
GT = StringCol(8)
class Event(IsDescription):
"""Row descriptor class for Pytables event table.
Contains event-level parameters, mostly from Monte Carlo simulation
parameters.
Attributes
----------
event_number : UInt32Col
UInt32 placeholder type for the shower event id
run_number : UInt32Col
UInt32 placeholder type for the run number
particle_id : UInt8Col
UInt8 placeholder type for the CORSIKA-simulated primary particle type
code.
core_x : Float64Col
Float64 placeholder type for the Monte Carlo shower core
position x coordinate.
core_y : Float64Col
Float64 placeholder type for the Monte Carlo shower core
position y coordinate.
h_first_int : Float64Col
Float64 placeholder type for the Monte Carlo height of first
interaction of the primary particle.
mc_energy : Float64Col
Float64 placeholder type for the Monte Carlo energy of the
primary particle.
az : Float32Col
Float32 placeholder type for the shower azimuth angle.
alt : Float32Col
Float32 placeholder type for the shower altitude (zenith) angle
"""
event_number = UInt32Col()
run_number = UInt32Col()
particle_id = UInt8Col()
core_x = Float32Col()
core_y = Float32Col()
h_first_int = Float32Col()
mc_energy = Float32Col()
az = Float32Col()
alt = Float32Col()
class Record(tables.IsDescription):
var1 = StringCol(itemsize=4) # 4-character String
var2 = IntCol() # integer
var3 = Int16Col() # short integer
var4 = FloatCol() # double (double-precision)
var5 = Float32Col() # float (single-precision)
class Jaszczak(IsDescription):
jaszczak = Float32Col([256, 256])
radius = Float32Col(10)
inten = Float32Col(10)
class description(IsDescription):
time = Int32Col()
st = Int8Col(shape=(N_CH, ))
wave = Float32Col(shape=(S_TOTAL, N_CH))
fet = Float32Col(shape=(N_CH, FPC))
clu = Int32Col()
