Python ECDDataFile.load Examples

Example #1

def getTrainingTimeCourseDataDict(training_data_dict, data_dir):
    trainingTimeCourseDataDict = {}

    for FullPN, ECDFileName in training_data_dict.items():
        aTimeCouse = ECDDataFile()
        aTimeCouse.load(os.sep.join((data_dir.rstrip(os.sep), ECDFileName)))
        trainingTimeCourseDataDict[FullPN] = dict(ECDFileName=ECDFileName,
                                                  ECDData=aTimeCouse)

    return trainingTimeCourseDataDict

Example #2

# --------------------------------------------------------
# (4) run
# --------------------------------------------------------
run( DULATION + INTERVAL )

# --------------------------------------------------------
# (5) read training time-course
# --------------------------------------------------------
aTrainingTimeCourseList = []

for i in range( len(TRAINING_DATA_FILE_LIST) ):

	aTimeCouse = ECDDataFile()
	aTimeCouse.load( _DATA_ + os.sep + TRAINING_DATA_FILE_LIST[i] )
	aTrainingTimeCourseList.append( aTimeCouse )

# --------------------------------------------------------
# (6) save predicted time-course
# --------------------------------------------------------
aPredictedTimeCouseList = []

for i in range( len(aLoggerList) ):
	
	aTimeCouse = ECDDataFile( aLoggerList[i].getData(START_TIME, \
							 DULATION + INTERVAL, \
							 INTERVAL) )
	aTimeCouse.setDataName( aLoggerList[i].getName() )
	aTimeCouse.setNote( 'Predicted %s' %VARIABLE_LIST_FOR_LOGGER[i] )
	aTimeCouse.save( PREFIX_OF_PREDICTED_TIMECOURSE + \

Example #3

# J_r  残差のヤコビアン（m×n行列、全要素ゼロで初期化）
J_r      = np.zeros(( len( theFullPNs['f'] ), len( theFullPNs['b'] )))
J_r_next = copy.deepcopy( J_r )

# βの現在値のリスト
p = []
for b in theFullPNs['b']:
    p.append( PARAMETERS[ b ] )

# トレーニングデータを格納した辞書
target_data_dict = {}

for FullPN, ECDFileName in CURVE_DATA_DICT.items():
    aTimeCouse = ECDDataFile()
    aTimeCouse.load( os.sep.join(( CURVE_DATA_DIR.rstrip( os.sep ), ECDFileName )) )
    target_data_dict[ FullPN ] = getTargetDataPoints( aTimeCouse.getData(), T_START, T_END, T_INTERVAL )

"""
for FullPN, tc in target_data_dict.items():
    print "\n" + FullPN
    for dp in tc:
        print "{} : {}".format( dp[0], dp[1] )
"""

# --------------------------------------------------------
# (3) 反復計算
# --------------------------------------------------------

beta_prev = copy.deepcopy( beta_dict )

Example #4

# --------------------------------------------------------
# (1) load eml file
# --------------------------------------------------------
setModel( EM, 'simple.em' )


# --------------------------------------------------------
# (2) read training time-course
# --------------------------------------------------------
TRAINING_TIME_COURSE_DATA_DICT = {}

for FullPN, ECDFileName in TRAINING_DATA_DICT.items():
    aTimeCouse = ECDDataFile()
    aTimeCouse.load( os.sep.join(( TRAINING_DATA_DIR.rstrip( os.sep ), ECDFileName )) )
    TRAINING_TIME_COURSE_DATA_DICT[ FullPN ] = dict( ECDFileName = ECDFileName, ECDData = aTimeCouse )


# --------------------------------------------------------
# (3) set parameter
# --------------------------------------------------------
EntityStubDict = {}
for FullPN, value in PARAMETERS.items():
    PN = FullPN.split(':')[ -1 ]
    FullID = FullPN[ : len( FullPN ) - len( PN ) - 1 ]
    if FullID not in EntityStubDict:
        EntityStubDict[ FullID ] = createEntityStub( FullID )
    EntityStubDict[ FullID ].setProperty( PN, value )

# --------------------------------------------------------