def check_convergence(dSysSettings, dEvalData, dSTOPData, bStop):
# =================================================================
# Get the user setting for minimum distance evaluation
[bEvalOn, dMinDEval] = _check_settings(dSysSettings)
# =================================================================
# =================================================================
# If this evaluation was not on, skip this function
if bEvalOn == 0:
return (bStop, dSysSettings, dSTOPData)
# =================================================================
# =================================================================
# Check if the convergence evaluation for this function is on.
if 'bConvCheck' in dMinDEval:
bConvCheck = dMinDEval['bConvCheck']
else:
bConvCheck = 0
# =================================================================
# =================================================================
# If the convergence evaluation is off, skip this function
if bConvCheck == 0:
return (bStop, dSysSettings, dSTOPData)
# =================================================================
# =================================================================
# Get the needed data
# -----------------------------------------------------------------
# Get the settings for the convergence
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
iEval = dSTOPData['EVAL_MIND'] # Index of the minimum
# distance evaluation
iMinConvMargin = dSTOPData['iMinConvMargin'] # Minimum convergence
# margin
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
iMargin = dMinDEval['iConvMarg'] # Allowed margin
iLastPatt = dMinDEval['iConvLastPatt'] # Size of the last data which
# is checked for convergence
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
dMinDData = dEvalData['dMinDData'] # The dictionary with internal
# data of evaluation functions and
# counters
vMinDErrConv = dMinDData['vMinDErrConv'] # Vector with convergence of
# average minimum distance error
vMinDRConv = dMinDData['vMinDRConv'] # Vector with convergence of the
# ratio of patterns which do not
# violate minimum distance
# requirement
# -----------------------------------------------------------------
# =================================================================
# =================================================================
# Check the convergence
# Measure the convergence:
# [average min dist error]
(bConvOkAE, iConvDistAE) = \
_data_convergence.is_data_converged(vMinDErrConv, iLastPatt,
iMargin, iMinConvMargin)
# [ratio of patterns which do not violate minimum distance requirement]
(bConvOkIP, iConvDistIP) = \
_data_convergence.is_data_converged(vMinDRConv, iLastPatt,
iMargin, iMinConvMargin)
bConvOk = bConvOkAE and bConvOkIP
# bConvOkAE == 0 if there is no convergence
# bConvOkIP == 0 if there is no convergence
# Check the stop condition
(bStop, dSTOPData, inxC, bLocalStop) = \
_data_convergence.check_conv_counter(dSTOPData, bConvOk,
bStop, iEval)
# =================================================================
# =================================================================
# Report to the console (if needed)
# Get the verbose settings
(bInfo, _) = _verbose.get_settings(dSysSettings)
# Print the info
if bInfo == 1:
stdout.write('STOP CHECK: ')
stdout.write('Minimum distance eval convergence: ')
if bConvOkAE == 1:
stdout.write('[average error]: OK ')
else:
strMessage = '[average error]: FAILED (%2.2f) ' % (iConvDistAE)
stdout.write(strMessage)
if bConvOkIP == 1:
stdout.write('[rat. correct patterns]: OK ')
else:
strMessage = '[rat. correct patterns]: FAILED (%2.2f) ' \
% (iConvDistIP)
stdout.write(strMessage)
if bConvOk == 1:
strMessage = 'OK %d TIME' % (inxC)
stdout.write(strMessage)
if bLocalStop == 1:
strMessage = ' (enough) \n' % (inxC)
stdout.write(strMessage)
else:
strMessage = '\n'
stdout.write(strMessage)
else:
strMessage = '\n'
stdout.write(strMessage)
# =================================================================
# =================================================================
return (bStop, dSysSettings, dSTOPData)
def check_convergence(dSysSettings, dEvalData, dSTOPData, bStop):
# =================================================================
# Get the user setting for correct patterns counter
(bCntrOn, dRCPCntr) = _check_settings(dSysSettings)
# =================================================================
# =================================================================
# If this counter was not on, skip this function
if bCntrOn == 0:
return (bStop, dSysSettings, dSTOPData)
# =================================================================
# =================================================================
# Check if the convergence check for this function is on.
if 'bConvCheck' in dRCPCntr:
bConvCheck = dRCPCntr['bConvCheck']
else:
bConvCheck = 0
# =================================================================
# =================================================================
# If the convergence check is off, skip this function
if bConvCheck == 0:
return (bStop, dSysSettings, dSTOPData)
# =================================================================
# =================================================================
# Get the needed data
# -----------------------------------------------------------------
# Get the settings for the convergence
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
iCheck = dSTOPData['EVAL_RCP'] # Index of counter of correct patterns
iMinConvMargin = dSTOPData['iMinConvMargin'] # Minimum convergence
# margin
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
iMargin = dRCPCntr['iConvMarg'] # Allowed margin
iLastPatt = dRCPCntr['iConvLastPatt'] # Size of the last data which
# is checked for convergence
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
dRCPData = dEvalData['dRCPData'] # The dictionary with internal data
# of evaluation functions and counter
vCorrConv = dRCPData['vCorrConv'] # Get the vector with convergence of
# the ratio of correct patterns
# -----------------------------------------------------------------
# =================================================================
# =================================================================
# Check the convergence
# Measure the convergence:
# Vector with convergence of the ratio of correct patterns
(bConvOk, iConvDist) = \
_data_convergence.is_data_converged(vCorrConv, iLastPatt,
iMargin, iMinConvMargin)
# Check the stop condition
[bStop, dSTOPData, inxC, bLocalStop] = \
_data_convergence.check_conv_counter(dSTOPData, bConvOk,
bStop, iCheck)
# =================================================================
# =================================================================
# Report to the console (if needed)
# Get the verbose settings
(bInfo, _) = _verbose.get_settings(dSysSettings)
# Print the info
if bInfo == 1:
stdout.write('STOP CHECK: ')
stdout.write('Correct patterns counter convergence: ')
if bConvOk == 1:
stdout.write('[ratio]: OK ')
stdout.write(' ')
else:
strMessage = '[ratio]: FAILED (%2.2f) ' % (iConvDist)
stdout.write(strMessage)
if bConvOk == 1:
strMessage = 'OK %d TIME' % (inxC)
stdout.write(strMessage)
if bLocalStop == 1:
strMessage = ' (enough) \n' % (inxC)
stdout.write(strMessage)
else:
strMessage = '\n'
stdout.write(strMessage)
else:
strMessage = '\n'
stdout.write(strMessage)
# =================================================================
# =================================================================
return (bStop, dSysSettings, dSTOPData)
def check_convergence(dSysSettings, dEvalData, dSTOPData, bStop):
# =================================================================
# Get the user setting for PDF evaluation
(bEvalOn, dPDFTotEval) = _check_settings(0, dSysSettings, 0)
# =================================================================
# =================================================================
# If this evaluation was not on, skip this function
if bEvalOn == 0:
return (bStop, dSysSettings, dSTOPData)
# =================================================================
# =================================================================
# Check if the convergence check for this function is on.
if 'bConvCheck' in dPDFTotEval:
bConvCheck = dPDFTotEval['bConvCheck']
else:
bConvCheck = 0
# =================================================================
# =================================================================
# If the convergence check is off, skip this function
if bConvCheck == 0:
return (bStop, dSysSettings, dSTOPData)
# =================================================================
# =================================================================
# Get the needed data
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
iEval = dSTOPData['EVAL_PDF'] # Index of the PDF
# evaluation
iMinConvMargin = dSTOPData['iMinConvMargin'] # Minimum convergence
# margin
# -----------------------------------------------------------------
# Get the settings for the convergence
iMargin = dPDFTotEval['iConvMarg'] # Allowed margin
iLastPatt = dPDFTotEval['iConvLastPatt'] # Size of the last data
# which is checked for
# convergence
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
dPDFTotData = dEvalData['dPDFTotData'] # The dictionary with
# internal data of
# of PDF evaluation (for
# all patterns)
vPDFErrTotConv = dPDFTotData['vPDFErrTotConv'] # Vector with convergence
# of PDF error
# -----------------------------------------------------------------
# =================================================================
# =================================================================
# -----------------------------------------------------------------
# Measure the convergence
(bConvOk, iConvDist) = \
_data_convergence.is_data_converged(vPDFErrTotConv, iLastPatt,
iMargin, iMinConvMargin)
# Check the stop condition
(bStop, dSTOPData, inxC, bLocalStop) = \
_data_convergence.check_conv_counter(dSTOPData, bConvOk,
bStop, iEval)
# =================================================================
# =================================================================
# Report to the console (if needed)
# Get the verbose settings
(bInfo, _) = _verbose.get_settings(dSysSettings)
# Print the info
if bInfo == 1:
stdout.write('STOP CHECK: ')
stdout.write('PDF eval convergence: ')
if bConvOk == 1:
stdout.write('[error]: OK ')
stdout.write(' ')
else:
strMessage = '[error]: FAILED (%2.2f) ' % (iConvDist)
stdout.write(strMessage)
if bConvOk == 1:
strMessage = 'OK %d TIME' % (inxC)
stdout.write(strMessage)
if bLocalStop == 1:
strMessage = ' (enough) \n' % (inxC)
stdout.write(strMessage)
else:
strMessage = '\n'
stdout.write(strMessage)
else:
strMessage = '\n'
stdout.write(strMessage)
# =================================================================
# =================================================================
return (bStop, dSysSettings, dSTOPData)
