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How to use the tables.UInt8Col function in tables

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github braingram / pywaveclus / pywaveclus / operations / fio / hdf5.py View on Github external
def make_spike_table_description(self, pre, post, nfeatures):
        class SpikeTableDescription(tables.IsDescription):
            time = tables.UInt64Col()
            channel = tables.UInt8Col()
            wave = tables.Float64Col(shape=(pre + post))
            cluster = tables.UInt8Col()
            features = tables.Float64Col(shape=(nfeatures))
        return SpikeTableDescription
github fasiondog / hikyuu / hikyuu / data / common_h5.py View on Github external
transAmount = tb.UInt64Col()     #IGNORE:E1101
    transCount = tb.UInt64Col()      #IGNORE:E1101


class H5Index(tb.IsDescription):
    """HDF5扩展K线数据格式（周线、月线、季线、半年线、年线、15分钟线、30分钟线、60分钟线"""
    datetime = tb.UInt64Col()        #IGNORE:E1101
    start    = tb.UInt64Col()        #IGNORE:E1101


class H5Transaction(tb.IsDescription):
    """分笔数据"""
    datetime = tb.UInt64Col()
    price = tb.UInt64Col()
    vol = tb.UInt64Col()
    buyorsell = tb.UInt8Col()


class H5TransactionIndex(tb.IsDescription):
    """分笔数据按天索引"""
    datetime = tb.UInt64Col()
    start = tb.UInt64Col()


class H5MinuteTime(tb.IsDescription):
    """分时线"""
    datetime = tb.UInt64Col()
    price = tb.UInt64Col()
    vol = tb.UInt64Col()


#------------------------------------------------------------------------------
github HiSPARC / sapphire / scripts / kascade / read_sqldump / storage.py View on Github external
slv_ch2_voltage = tables.Float64Col()
    slv_ch1_current = tables.Float64Col()
    slv_ch2_current = tables.Float64Col()
    slv_comp_thres_low = tables.Float64Col()
    slv_comp_thres_high = tables.Float64Col()
    slv_max_voltage = tables.Float64Col()
    slv_reset = tables.BoolCol()
    slv_ch1_gain_pos = tables.UInt8Col()
    slv_ch1_gain_neg = tables.UInt8Col()
    slv_ch2_gain_pos = tables.UInt8Col()
    slv_ch2_gain_neg = tables.UInt8Col()
    slv_ch1_offset_pos = tables.UInt8Col()
    slv_ch1_offset_neg = tables.UInt8Col()
    slv_ch2_offset_pos = tables.UInt8Col()
    slv_ch2_offset_neg = tables.UInt8Col()
    slv_common_offset = tables.UInt8Col()
    slv_internal_voltage = tables.UInt8Col()
    slv_ch1_adc_gain = tables.Float64Col()
    slv_ch1_adc_offset = tables.Float64Col()
    slv_ch2_adc_gain = tables.Float64Col()
    slv_ch2_adc_offset = tables.Float64Col()
    slv_ch1_comp_gain = tables.Float64Col()
    slv_ch1_comp_offset = tables.Float64Col()
    slv_ch2_comp_gain = tables.Float64Col()
    slv_ch2_comp_offset = tables.Float64Col()


class HisparcWeather(tables.IsDescription):
    event_id = tables.UInt32Col(pos=0)
    timestamp = tables.Time32Col(pos=1)
    temp_inside = tables.Float32Col(pos=2)
    temp_outside = tables.Float32Col(pos=3)
github hyeshik / tailseeker / scripts / write-sqi-to-table.py View on Github external
def create_tables(h5, group, samplename, tileid, ncycles, nchannels):

    class SeqQual(tables.IsDescription):
        gcid = tables.Int64Col(pos=0)
        istart = tables.Int16Col(pos=1)
        seq = tables.StringCol(ncycles, pos=2)
        qual = tables.UInt8Col(shape=(ncycles,), pos=3)
        #intensity = tables.Int16Col(shape=(ncycles, nchannels), pos=5)

    subgroup = h5.create_group(group, samplename,
                    'SQI arrays for sample {} from tile {}'.format(samplename, tileid))

    seqqual = h5.create_table(subgroup, 'seqqual', SeqQual,
                              'Sequences and quality scores for sample {} from '
                              'tile {}'.format(samplename, tileid))
    intensities = h5.create_earray(subgroup, 'intensities', tables.UInt8Atom(),
                                   (0, ncycles, nchannels),
                'Signal intensities for sample {} from tile {}'.format(samplename, tileid))

    return seqqual, intensities
github HiSPARC / sapphire / deprecated / storage.py View on Github external
rotation of the station around its center

    .. attribute:: N

        number of detectors with at least one particle

    """
    id = tables.UInt32Col()
    station_id = tables.UInt8Col()
    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 ShowerParticle(tables.IsDescription):
    """Store information about shower particles reaching round level

    This table stores particles from shower simulations.  For example, AIRES
    simulations produce ``grdpcles`` files containing all particles which
    reached ground level.  These files can be read and their contents can be
github PyTables / PyTables / examples / tutorial1-1.py View on Github external
"""

from __future__ import print_function
import numpy as np
import tables


        #'-**-**-**-**-**-**- user record definition  -**-**-**-**-**-**-**-'

# Define a user record to characterize some kind of particles
class Particle(tables.IsDescription):
    name = tables.StringCol(16)     # 16-character String
    idnumber = tables.Int64Col()    # Signed 64-bit integer
    ADCcount = tables.UInt16Col()   # Unsigned short integer
    TDCcount = tables.UInt8Col()    # unsigned byte
    grid_i = tables.Int32Col()      # integer
    grid_j = tables.Int32Col()      # integer
    pressure = tables.Float32Col()  # float  (single-precision)
    energy = tables.Float64Col()    # double (double-precision)

print()
print('-**-**-**-**-**-**- file creation  -**-**-**-**-**-**-**-')

# The name of our HDF5 filename
filename = "tutorial1.h5"

print("Creating file:", filename)

# Open a file in "w"rite mode
h5file = tables.open_file(filename, mode="w", title="Test file")
github HiSPARC / sapphire / scripts / kascade / read_sqldump / storage.py View on Github external
slv_ch1_thres_low = tables.Float64Col()
    slv_ch1_thres_high = tables.Float64Col()
    slv_ch2_thres_low = tables.Float64Col()
    slv_ch2_thres_high = tables.Float64Col()
    slv_ch1_inttime = tables.Float64Col()
    slv_ch2_inttime = tables.Float64Col()
    slv_ch1_voltage = tables.Float64Col()
    slv_ch2_voltage = tables.Float64Col()
    slv_ch1_current = tables.Float64Col()
    slv_ch2_current = tables.Float64Col()
    slv_comp_thres_low = tables.Float64Col()
    slv_comp_thres_high = tables.Float64Col()
    slv_max_voltage = tables.Float64Col()
    slv_reset = tables.BoolCol()
    slv_ch1_gain_pos = tables.UInt8Col()
    slv_ch1_gain_neg = tables.UInt8Col()
    slv_ch2_gain_pos = tables.UInt8Col()
    slv_ch2_gain_neg = tables.UInt8Col()
    slv_ch1_offset_pos = tables.UInt8Col()
    slv_ch1_offset_neg = tables.UInt8Col()
    slv_ch2_offset_pos = tables.UInt8Col()
    slv_ch2_offset_neg = tables.UInt8Col()
    slv_common_offset = tables.UInt8Col()
    slv_internal_voltage = tables.UInt8Col()
    slv_ch1_adc_gain = tables.Float64Col()
    slv_ch1_adc_offset = tables.Float64Col()
    slv_ch2_adc_gain = tables.Float64Col()
    slv_ch2_adc_offset = tables.Float64Col()
    slv_ch1_comp_gain = tables.Float64Col()
    slv_ch1_comp_offset = tables.Float64Col()
    slv_ch2_comp_gain = tables.Float64Col()
    slv_ch2_comp_offset = tables.Float64Col()
github HiSPARC / sapphire / scripts / kascade / read_sqldump / storage.py View on Github external
slv_ch2_inttime = tables.Float64Col()
    slv_ch1_voltage = tables.Float64Col()
    slv_ch2_voltage = tables.Float64Col()
    slv_ch1_current = tables.Float64Col()
    slv_ch2_current = tables.Float64Col()
    slv_comp_thres_low = tables.Float64Col()
    slv_comp_thres_high = tables.Float64Col()
    slv_max_voltage = tables.Float64Col()
    slv_reset = tables.BoolCol()
    slv_ch1_gain_pos = tables.UInt8Col()
    slv_ch1_gain_neg = tables.UInt8Col()
    slv_ch2_gain_pos = tables.UInt8Col()
    slv_ch2_gain_neg = tables.UInt8Col()
    slv_ch1_offset_pos = tables.UInt8Col()
    slv_ch1_offset_neg = tables.UInt8Col()
    slv_ch2_offset_pos = tables.UInt8Col()
    slv_ch2_offset_neg = tables.UInt8Col()
    slv_common_offset = tables.UInt8Col()
    slv_internal_voltage = tables.UInt8Col()
    slv_ch1_adc_gain = tables.Float64Col()
    slv_ch1_adc_offset = tables.Float64Col()
    slv_ch2_adc_gain = tables.Float64Col()
    slv_ch2_adc_offset = tables.Float64Col()
    slv_ch1_comp_gain = tables.Float64Col()
    slv_ch1_comp_offset = tables.Float64Col()
    slv_ch2_comp_gain = tables.Float64Col()
    slv_ch2_comp_offset = tables.Float64Col()


class HisparcWeather(tables.IsDescription):
    event_id = tables.UInt32Col(pos=0)
    timestamp = tables.Time32Col(pos=1)
github klusta-team / klustaviewa / klustaviewa / dataio / hdf5tools.py View on Github external
def get_spikes_description(fetcol=None):
    spikes_description = OrderedDict([
        ('time', tables.UInt64Col()),
        ('features', tables.Float32Col(shape=(fetcol,))),
        ('cluster_auto', tables.UInt32Col()),
        ('cluster_manual', tables.UInt32Col()),
        ('masks', tables.UInt8Col(shape=(fetcol,))),])
    return spikes_description
github HiSPARC / sapphire / scripts / kascade / read_sqldump / storage.py View on Github external
slv_ch2_thres_high = tables.Float64Col()
    slv_ch1_inttime = tables.Float64Col()
    slv_ch2_inttime = tables.Float64Col()
    slv_ch1_voltage = tables.Float64Col()
    slv_ch2_voltage = tables.Float64Col()
    slv_ch1_current = tables.Float64Col()
    slv_ch2_current = tables.Float64Col()
    slv_comp_thres_low = tables.Float64Col()
    slv_comp_thres_high = tables.Float64Col()
    slv_max_voltage = tables.Float64Col()
    slv_reset = tables.BoolCol()
    slv_ch1_gain_pos = tables.UInt8Col()
    slv_ch1_gain_neg = tables.UInt8Col()
    slv_ch2_gain_pos = tables.UInt8Col()
    slv_ch2_gain_neg = tables.UInt8Col()
    slv_ch1_offset_pos = tables.UInt8Col()
    slv_ch1_offset_neg = tables.UInt8Col()
    slv_ch2_offset_pos = tables.UInt8Col()
    slv_ch2_offset_neg = tables.UInt8Col()
    slv_common_offset = tables.UInt8Col()
    slv_internal_voltage = tables.UInt8Col()
    slv_ch1_adc_gain = tables.Float64Col()
    slv_ch1_adc_offset = tables.Float64Col()
    slv_ch2_adc_gain = tables.Float64Col()
    slv_ch2_adc_offset = tables.Float64Col()
    slv_ch1_comp_gain = tables.Float64Col()
    slv_ch1_comp_offset = tables.Float64Col()
    slv_ch2_comp_gain = tables.Float64Col()
    slv_ch2_comp_offset = tables.Float64Col()


class HisparcWeather(tables.IsDescription):

tables

Hierarchical datasets for Python

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