added Oleg Petrov's *write_to_tecmag* result function
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@ -13,12 +13,18 @@ from Errorable import Errorable
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from Drawable import Drawable
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from Drawable import Drawable
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from DamarisFFT import DamarisFFT
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from DamarisFFT import DamarisFFT
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from Signalpath import Signalpath
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from Signalpath import Signalpath
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#from DataPool import DataPool
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import sys
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import sys
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import threading
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import threading
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import types
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import types
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import tables
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import tables
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import numpy
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import numpy
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import datetime
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import datetime # added by Oleg Petrov
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import ctypes # added by Oleg Petrov
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import struct # added by Oleg Petrov
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import os # added by Oleg Petrov
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class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
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class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
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def __init__(self, x = None, y = None, y_2 = None, n = None, index = None, sampl_freq = None, error = False):
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def __init__(self, x = None, y = None, y_2 = None, n = None, index = None, sampl_freq = None, error = False):
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@ -35,6 +41,7 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
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self.common_descriptions=None
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self.common_descriptions=None
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self.time_period=[]
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self.time_period=[]
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self.job_id = None # added by Oleg Petrov
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self.use_error = error
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self.use_error = error
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@ -192,7 +199,8 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
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return max(tmp_max)
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return max(tmp_max)
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def get_job_id(self):
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def get_job_id(self):
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return None
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# return None
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return self.job_id # modified by Oleg Petrov
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def write_to_csv(self, destination=sys.stdout, delimiter=" "):
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def write_to_csv(self, destination=sys.stdout, delimiter=" "):
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"""
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"""
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@ -236,7 +244,8 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
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finally:
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finally:
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self.lock.release()
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self.lock.release()
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def write_to_simpson(self, destination=sys.stdout, delimiter=" "):
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# ------------- added by Oleg Petrov, 14 Feb 2012 ----------------------
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def write_to_simpson(self, destination=sys.stdout, delimiter=" ", frequency=100e6):
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"""
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"""
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writes the data to a text file or sys.stdout in Simpson format,
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writes the data to a text file or sys.stdout in Simpson format,
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for further processing with the NMRnotebook software;
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for further processing with the NMRnotebook software;
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@ -253,6 +262,7 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
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the_destination.write("SIMP\n")
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the_destination.write("SIMP\n")
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the_destination.write("%s%i%s"%("NP=", len(xdata), "\n"))
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the_destination.write("%s%i%s"%("NP=", len(xdata), "\n"))
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the_destination.write("%s%i%s"%("SW=", self.get_sampling_rate(), "\n"))
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the_destination.write("%s%i%s"%("SW=", self.get_sampling_rate(), "\n"))
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the_destination.write("%s%i%s"%("REF=", frequency, "\n"))
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the_destination.write("TYPE=FID\n")
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the_destination.write("TYPE=FID\n")
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the_destination.write("DATA\n")
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the_destination.write("DATA\n")
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ch_no=self.get_number_of_channels()
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ch_no=self.get_number_of_channels()
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@ -267,6 +277,127 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
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finally:
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finally:
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self.lock.release()
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self.lock.release()
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# ------------- added by Oleg Petrov, 10 Sep 2013 -----------------------
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def write_to_tecmag(self, destination=sys.stdout, nrecords=1,\
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frequency=100e6,\
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last_delay = 1.,\
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receiver_phase=0.,\
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nucleus='1H'):
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"""
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writes the data to a binary file in TecMag format;
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destination can be a file object or a filename;
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nrecords determines the 2nd dimension of data;
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"""
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if self.job_id == None or self.n == 0:
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raise ValueError("write_to_tecmag: cannot get a record number")
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else:
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record = self.job_id/self.n + 1
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the_destination=destination
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if type(destination) in types.StringTypes:
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if record == 1 and os.path.exists(destination):
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os.rename(destination, os.path.dirname(destination)+'/~'+os.path.basename(destination))
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the_destination=file(destination, "ab")
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self.lock.acquire()
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try:
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npts = [len(self), nrecords, 1, 1]
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dwell = 1./self.get_sampling_rate()
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sw = 0.5/dwell
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base_freq = [frequency, 100., 0., 0.]
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offset_freq = [0., 0., 0., 0.]
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ob_freq = [sum(x) for x in zip(base_freq, offset_freq)]
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date = self.time_period[0].strftime("%Y/%m/%d %H:%M:%S")
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if record == 1:
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buff = ctypes.create_string_buffer(1056)
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struct.pack_into('8s', buff, 0, 'TNT1.005') # 'TNT1.000' version ID
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struct.pack_into('4s', buff, 8, 'TMAG') # 'TMAG' tag
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struct.pack_into('?', buff, 12, True) # BOOLean value
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struct.pack_into('i', buff, 16, 1024) # length of Tecmag struct
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#Initialize TECMAG structure:
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struct.pack_into('4i', buff, 20, *npts) # npts[4]
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struct.pack_into('4i', buff, 36, *npts) # actual_npts[4]
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struct.pack_into('i', buff, 52, npts[0]) # acq_points
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struct.pack_into('4i', buff, 56, 1, 1, 1, 1) # npts_start[4]
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struct.pack_into('i', buff, 72, self.n) # scans
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struct.pack_into('i', buff, 76, self.n) # actual_scans
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struct.pack_into('i', buff, 88, 1) # sadimension
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struct.pack_into('4d', buff, 104, *ob_freq) # ob_freq[4]
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struct.pack_into('4d', buff, 136, *base_freq) # base_freq[4]
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struct.pack_into('4d', buff, 168, *offset_freq) # offset_freq[4]
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struct.pack_into('d', buff, 200, 0.0) # ref_freq
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struct.pack_into('h', buff, 216, 1) # obs_channel
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struct.pack_into('42s', buff, 218, 42*'2') # space2[42]
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struct.pack_into('4d', buff, 260, sw, 0., 0., 0.) # sw[4], sw = 0.5/dwell
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struct.pack_into('4d', buff, 292, dwell, 0., 0., 0.) # dwell[4]
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struct.pack_into('d', buff, 324, sw) # filter, = 0.5/dwell
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struct.pack_into('d', buff, 340, (npts[0]*dwell)) # acq_time
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struct.pack_into('d', buff, 348, 1.) # last_delay (5*T1 minus sequence length)
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struct.pack_into('h', buff, 356, 1) # spectrum_direction
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struct.pack_into('16s', buff, 372, 16*'2') # space3[16]
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struct.pack_into('d', buff, 396, receiver_phase) # receiver_phase
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struct.pack_into('4s', buff, 404, 4*'2') # space4[4]
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struct.pack_into('16s', buff, 444, 16*'2') # space5[16]
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struct.pack_into('264s', buff, 608, 264*'2') # space6[264]
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struct.pack_into('32s', buff, 884, date) # date[32]
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struct.pack_into('16s', buff, 916, nucleus) # nucleus[16]
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# TECMAG Structure total => 1024
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struct.pack_into('4s', buff, 1044, 'DATA') # 'DATA' tag
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struct.pack_into('?', buff, 1048, True) # BOOLean
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struct.pack_into('i', buff, 1052, 2*4*npts[0]*npts[1]) # length of data (2 = [Re, Im]; 4 = len(c_float))
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the_destination.write(buff)
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# append data to the file as they appear in an experiment (RIRIRIRI blocks in linear order):
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ch_no=self.get_number_of_channels()
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ydata = map(self.get_ydata, xrange(ch_no))
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if ch_no == 1:
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ydata = [ydata, numpy.zeros(len(ydata))]
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data = numpy.append([ydata[0]], [ydata[1]], axis=0)
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data = data.T
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data = data.flatten()
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buff = ctypes.create_string_buffer(4*len(data))
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struct.pack_into('%sf' % len(data), buff, 0, *data)
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the_destination.write(buff)
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if record == nrecords:
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buff = ctypes.create_string_buffer(2068)
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struct.pack_into('4s', buff, 0, 'TMG2') # 'TMG2' tag
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struct.pack_into('?', buff, 4, True) # BOOLean
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struct.pack_into('i', buff, 8, 2048) # length of Tecmag2 struct
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# Leave TECMAG2 structure empty:
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struct.pack_into('52s', buff, 372, 52*'2') # space[52]
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struct.pack_into('866s', buff, 1194, 866*'2') # space[610]+names+strings
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# TECMAG2 Structure total => 2048
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struct.pack_into('4s', buff, 2060, 'PSEQ') # 'PSEQ' tag 658476
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struct.pack_into('?', buff, 2064, False) # BOOLean 658480
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the_destination.write(buff)
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the_destination = None
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ydata=None
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finally:
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self.lock.release()
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# -----------------------------------------------------------------------
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def write_to_hdf(self, hdffile, where, name, title, complib=None, complevel=None):
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def write_to_hdf(self, hdffile, where, name, title, complib=None, complevel=None):
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accu_group=hdffile.createGroup(where=where,name=name,title=title)
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accu_group=hdffile.createGroup(where=where,name=name,title=title)
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accu_group._v_attrs.damaris_type="Accumulation"
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accu_group._v_attrs.damaris_type="Accumulation"
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@ -458,6 +589,7 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
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else:
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else:
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r = Accumulation(x = numpy.array(other.x, dtype="Float64"), y = tmp_y, index = other.index, sampl_freq = other.sampling_rate, n = 1, error = False)
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r = Accumulation(x = numpy.array(other.x, dtype="Float64"), y = tmp_y, index = other.index, sampl_freq = other.sampling_rate, n = 1, error = False)
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r.time_period=[other.job_date,other.job_date]
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r.time_period=[other.job_date,other.job_date]
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r.job_id = other.job_id # added by Oleg Petrov
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r.common_descriptions=other.description.copy()
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r.common_descriptions=other.description.copy()
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self.lock.release()
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self.lock.release()
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return r
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return r
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@ -485,6 +617,7 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
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r = Accumulation(x = numpy.array(self.x, dtype="Float64"), y = tmp_y, n = self.n + 1, index = self.index, sampl_freq = self.sampling_rate, error = False)
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r = Accumulation(x = numpy.array(self.x, dtype="Float64"), y = tmp_y, n = self.n + 1, index = self.index, sampl_freq = self.sampling_rate, error = False)
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r.time_period=[min(self.time_period[0],other.job_date),
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r.time_period=[min(self.time_period[0],other.job_date),
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max(self.time_period[1],other.job_date)]
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max(self.time_period[1],other.job_date)]
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r.job_id = other.job_id # added by Oleg Petrov
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if self.common_descriptions is not None:
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if self.common_descriptions is not None:
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r.common_descriptions={}
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r.common_descriptions={}
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for key in self.common_descriptions.keys():
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for key in self.common_descriptions.keys():
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@ -516,6 +649,7 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
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tmp_y.append(other.y[i])
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tmp_y.append(other.y[i])
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tmp_ysquare.append(other.y_square[i])
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tmp_ysquare.append(other.y_square[i])
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r.time_period=other.time_period[:]
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r.time_period=other.time_period[:]
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r.job_id = other.job_id # added by Oleg Petrov
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if other.common_descriptions is not None:
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if other.common_descriptions is not None:
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r.common_descriptions=othter.common_descriptions.copy()
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r.common_descriptions=othter.common_descriptions.copy()
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else:
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else:
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@ -549,6 +683,7 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
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r.time_period=[min(self.time_period[0],other.time_period[0]),
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r.time_period=[min(self.time_period[0],other.time_period[0]),
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max(self.time_period[1],other.time_period[1])]
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max(self.time_period[1],other.time_period[1])]
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r.job_id = other.job_id # added by Oleg Petrov
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r.common_descriptions={}
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r.common_descriptions={}
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if self.common_descriptions is not None and other.common_descriptions is not None:
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if self.common_descriptions is not None and other.common_descriptions is not None:
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for key in self.common_descriptions.keys():
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for key in self.common_descriptions.keys():
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@ -614,6 +749,7 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
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self.lock.release()
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self.lock.release()
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self.time_period=[other.job_date,other.job_date]
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self.time_period=[other.job_date,other.job_date]
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self.job_id = other.job_id # added by Oleg Petrov
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self.common_descriptions=other.description.copy()
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self.common_descriptions=other.description.copy()
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return self
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return self
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@ -636,6 +772,7 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
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self.n += 1
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self.n += 1
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self.time_period=[min(self.time_period[0],other.job_date),
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self.time_period=[min(self.time_period[0],other.job_date),
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max(self.time_period[1],other.job_date)]
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max(self.time_period[1],other.job_date)]
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self.job_id = other.job_id # added by Oleg Petrov
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if self.common_descriptions is not None:
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if self.common_descriptions is not None:
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for key in self.common_descriptions.keys():
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for key in self.common_descriptions.keys():
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if not (key in other.description and self.common_descriptions[key]==other.description[key]):
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if not (key in other.description and self.common_descriptions[key]==other.description[key]):
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@ -670,6 +807,7 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
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self.set_title(self.__title_pattern % self.n)
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self.set_title(self.__title_pattern % self.n)
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self.common_descriptions=other.common_desriptions.copy()
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self.common_descriptions=other.common_desriptions.copy()
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self.time_period=other.time_period[:]
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self.time_period=other.time_period[:]
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self.job_id = other.job_id # added by Oleg Petrov
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self.lock.release()
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self.lock.release()
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return self
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return self
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@ -691,6 +829,7 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
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self.n += other.n
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self.n += other.n
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self.time_period=[min(self.time_period[0],other.time_period[0]),
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self.time_period=[min(self.time_period[0],other.time_period[0]),
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max(self.time_period[1],other.time_period[1])]
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max(self.time_period[1],other.time_period[1])]
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self.job_id = other.job_id # added by Oleg Petrov
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if self.common_descriptions is not None and other.common_descriptions is not None:
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if self.common_descriptions is not None and other.common_descriptions is not None:
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for key in self.common_descriptions.keys():
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for key in self.common_descriptions.keys():
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if not (key in other.description and
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if not (key in other.description and
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