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- Flexibility; HDF5 file has indexed structure, that means direct access to any data of any file from your code.
Pythonis a high-level scripting language allows to write transparent and compact code based on well-elaborated standard libraries.- In general, code in
Pythonworks slow comparing to C++, but there are libraries like +NumPywritten on C++, which solve this problem for manipulation with large arrays.
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- from the
timedata recordCode Block time_dataset = file['/Configure:0000/Run:0000/CalibCycle:0002/Acqiris::DataDescV1/XppLas.0:Acqiris.0/time'] index = 0 # this is an index in the dataset time = time_dataset[index] # get the time tuple consisting of seconds and nanoseconds time_sec = time[0] time_nsec = time[1]
Code examples
Example 1:
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Basic operations
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#!/usr/bin/env python
import h5py
import numpy as np
eventNumber = 5
file = h5py.File('/reg/d/psdm/XPP/xppcom10/hdf5/xppcom10-r0546.h5', 'r')
dataset = file['/Configure:0000/Run:0000/CalibCycle:0000/Camera::FrameV1/XppSb4Pim.1:Tm6740.1/image']
arr1ev = dataset[eventNumber]
file.close()
print 'arr1ev.shape =', arr1ev.shape
print 'arr1ev =\n', arr1ev
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Example 2: Extract and print the time variables
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#!/usr/bin/env python
import h5py
import time
#-----------------------------------------------------
def print_time(t_sec, t_nsec):
"""Converts seconds in human-readable time and prints formatted time"""
tloc = time.localtime(t_sec) # converts sec to the tuple struct_time in local
print 'Input time :',t_sec,'sec,', t_nsec,'nsec, '
print 'Local time :', time.strftime('%Y-%m-%d %H:%M:%S',tloc)
#-----------------------------------------------------
file_name = '/reg/d/psdm/xpp/xpp22510/hdf5/xpp22510-r0100.h5'
file = h5py.File(file_name, 'r') # open read-only
print "EXAMPLE: Get time from the group attributes:"
group = file["/Configure:0000"]
t_sec = group.attrs.values()[0]
t_nsec = group.attrs.values()[1]
print_time(t_sec, t_nsec)
print "EXAMPLE: Get time from the data record 'time':"
dataset = file['/Configure:0000/Run:0000/CalibCycle:0002/Acqiris::DataDescV1/XppLas.0:Acqiris.0/time']
index = 0
time = dataset[ind]
t_sec = time[0]
t_nsec = time[1]
print_time(t_sec, t_nsec)
f.close()
#----------------------------------------------------
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#!/usr/bin/env python
import os
import sys
import h5py
import numpy as np
class TwoDatasetSynchronization ( object ) :
"""Matching elements of two datasets using their time stamps"""
def __init__ ( self, file, Xdsname, Ydsname ) :
"""Initialization"""
self.dsX = file[Xdsname]
self.dsY = file[Ydsname]
XTimedsname = get_item_path_to_last_name(Xdsname) + '/time'
YTimedsname = get_item_path_to_last_name(Ydsname) + '/time'
self.dsXT = file[XTimedsname]
self.dsYT = file[YTimedsname]
self.XTarr = 0.000000001 * self.dsXT['nanoseconds'] + self.dsXT['seconds']
self.YTarr = 0.000000001 * self.dsYT['nanoseconds'] + self.dsYT['seconds']
self._nXpoints = self.dsX.shape[0]
self._nYpoints = self.dsY.shape[0]
self._indX = 0
self._indY = 0
self._tmapXlist = []
self._tmapYlist = []
print 'Xdsname =',Xdsname
print 'Ydsname =',Ydsname
print 'XTimedsname =',XTimedsname
print 'YTimedsname =',YTimedsname
print 'Initialization: datasets X and Y have length =', self._nXpoints, self._nYpoints
def twoDatasetSynchronizationIterations( self ) :
"""Iteration over time indexes and appending of syncronized arrays."""
while self._indX < self._nXpoints and self._indY < self._nYpoints :
if self.XTarr[self._indX] == self.YTarr[self._indY] : # Time is the same
self._tmapXlist.append(self.dsX[self._indX])
self._tmapYlist.append(self.dsY[self._indY])
self._indX += 1
self._indY += 1
elif self.XTarr[self._indX] > self.YTarr[self._indY] : # Time X > Time Y
self._indY += 1
self.printMissingSynchronization()
else : # Time X < Time Y
self._indX += 1
self.printMissingSynchronization()
def printMissingSynchronization( self ) :
print 'Missing of syncronization for X,Y indexes ',self._indX,self._indY
def runSynchronization( self ) :
"""Executes synchronization and makes the references for synchronized arrays."""
self.twoDatasetSynchronizationIterations()
self.Xarr = np.array(self._tmapXlist)
self.Yarr = np.array(self._tmapYlist)
print 'Number of synchronized in time X and Y array elements =', self.Xarr.shape, self.Yarr.shape
def get_item_path_to_last_name(dsname):
"""Returns the path to the last part of the item name"""
path,name = os.path.split(str(dsname))
return path
def main() :
"""EXAMPLE: Time synchronization of two datasets.
In this example we open the file, which contains normal dataset (Y)
and the dataset with lost records (X).
We access these arrays and associated time arrays
through the class TwoDatasetSynchronization.
Then we iterate over indexes of these arrays and appends the lists of
syncronized arrays.
syncronized arrays. Program prints the message in case of missing synchronization.
"""
file = h5py.File('/reg/d/psdm/CXI/cxi80410/hdf5/cxi80410-r0730.h5', 'r')
Xdsname = '/Configure:0000/Run:0000/CalibCycle:0000/Bld::BldDataFEEGasDetEnergy/NoDetector.0:NoDevice.2/data'
Ydsname = '/Configure:0000/Run:0000/CalibCycle:0000/Ipimb::DataV1/CxiDg1.0:Ipimb.0/data'
synchro = TwoDatasetSynchronization (file, Xdsname, Ydsname)
synchro.runSynchronization()
#--------------------------------
if __name__ == "__main__" :
main()
sys.exit ( "That's it!" )
#--------------------------------
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