Python getMetaData Examples

Example #1

File: prepare_static_frame_data.py Project: rmencis/gaitlearning

def produceFeatureFile(baseDirPath,trial,includeSampleWithProbability,outputDirPath):
    dirPath = os.path.join(baseDirPath,'T' + str(trial).zfill(3))
    metaFilePath = os.path.join(dirPath,'meta-' + str(trial).zfill(3)+".yml")
    dataFilePath = os.path.join(dirPath,'mocap-' + str(trial).zfill(3)+".txt")
    outputFilePath = os.path.join(outputDirPath,'t' + str(trial).zfill(3) + ".csv")

    metaData = data_util.getMetaData(metaFilePath)

    with open(outputFilePath, 'wb') as outputCSVFile:
        csvWriter = csv.writer(outputCSVFile)
        counter = 0
        with open(dataFilePath, 'rb') as f:
            reader = csv.reader(f, delimiter='\t')
            for row in reader:
                features = row[2:143]
                if counter == 0:
                    features.append('Subject')
                    csvWriter.writerow(features)
                else:
                    if random.random() <= includeSampleWithProbability:
                        features.append(metaData.subject.id)
                        csvWriter.writerow(features)
                #print features
                counter += 1
    return

Example #2

File: prepare_static_frame_data.py Project: rmencis/gaitlearning

def produceFeatureFile(baseDirPath, trial, includeSampleWithProbability,
                       outputDirPath):
    dirPath = os.path.join(baseDirPath, 'T' + str(trial).zfill(3))
    metaFilePath = os.path.join(dirPath,
                                'meta-' + str(trial).zfill(3) + ".yml")
    dataFilePath = os.path.join(dirPath,
                                'mocap-' + str(trial).zfill(3) + ".txt")
    outputFilePath = os.path.join(outputDirPath,
                                  't' + str(trial).zfill(3) + ".csv")

    metaData = data_util.getMetaData(metaFilePath)

    with open(outputFilePath, 'wb') as outputCSVFile:
        csvWriter = csv.writer(outputCSVFile)
        counter = 0
        with open(dataFilePath, 'rb') as f:
            reader = csv.reader(f, delimiter='\t')
            for row in reader:
                features = row[2:143]
                if counter == 0:
                    features.append('Subject')
                    csvWriter.writerow(features)
                else:
                    if random.random() <= includeSampleWithProbability:
                        features.append(metaData.subject.id)
                        csvWriter.writerow(features)
                #print features
                counter += 1
    return

Example #3

File: prepare_dynamic_data_1.py Project: rmencis/gaitlearning

def readData(baseDirPath,trial):
    dirPath = os.path.join(baseDirPath,'T' + str(trial).zfill(3))
    metaFilePath = os.path.join(dirPath,'meta-' + str(trial).zfill(3)+".yml")
    dataFilePath = os.path.join(dirPath,'mocap-' + str(trial).zfill(3)+".txt")

    metaData = data_util.getMetaData(metaFilePath)

    rows = []
    with open(dataFilePath, 'rb') as f:
        reader = csv.reader(f, delimiter='\t')
        reader.next() # Skin header
        for row in reader:
            rows.append(row)

    return rows,metaData.subject.id

Example #4

File: prepare_dynamic_data_with_cycles.py Project: rmencis/gaitlearning

def readData(baseDirPath,trial):
    dirPath = os.path.join(baseDirPath,'T' + str(trial).zfill(3))
    metaFilePath = os.path.join(dirPath,'meta-' + str(trial).zfill(3)+".yml")
    dataFilePath = os.path.join(dirPath,'mocap-' + str(trial).zfill(3)+".txt")

    metaData = data_util.getMetaData(metaFilePath)

    rows = []
    with open(dataFilePath, 'rb') as f:
        reader = csv.reader(f, delimiter='\t')
        reader.next() # Skin header
        for row in reader:
            rows.append(row)

    return rows,metaData.subject.id