Python csv2arr Examples

Example #1

File: main.py Project: mathandy/svg-dendro_analysistool

############################################################
if opt.DEBUG_MODE_ON:
    from testingtools import gen_new_fake_data
    opt.RAINFALLDATA_FN = 'dummy_rainfalldata.csv'
    opt.SAMPLEDATA_FN = 'dummy_sampledata.csv'
    opt.RAIN_DATA_HAS_HEADERS = False
    opt.SAMPLE_DATA_HAS_HEADERS = False

    if opt.GENERATE_NEW_FAKE_DATA:
        args = (opt.N_RAIN, opt.N_SAMPLES, opt.REL_NOISE, opt.MEAN_SLOPE)
        gen_new_fake_data(*args)

############################################################
# Data Pre-Processing
############################################################
assert 0 <= opt.MIN_OVERLAP <= len(csv2arr(opt.RAINFALLDATA_FN))

# format and normalize rainfall data
rain = csv2arr(opt.RAINFALLDATA_FN, hasheaders=opt.RAIN_DATA_HAS_HEADERS)
rain = list(np.array(rain).T[0])  # convert Nx1 array to list

rain = [float(x) for x in rain]

# read and format sample data and take the transpose
# (so now each sample is a row)
sampledata = csv2arr(opt.SAMPLEDATA_FN, hasheaders=opt.SAMPLE_DATA_HAS_HEADERS)

# take the transpose (so now each sample is a row)
sampledata = transpose(sampledata)

# convert any strings to floats

Example #2

File: summaryparser.py Project: mathandy/svgtree_analysistool

# if None, defaults to 'summary_data.csv' (in the folder containing this
# script)
outf = None

#####################################################
# set defaults
if not rows2grab:
    rows2grab = [2, 3]
if not trans2grab:
    trans2grab = range(10)
if not summary_dir:
    summary_dir = os.path.join(os.getcwd(), 'summaries')
if not outf:
    outf = 'summary_data.csv'

# do stuff
data = []
data_guide = []
for fn in os.listdir(summary_dir):
    path2summary = os.path.join(summary_dir, fn)
    summary = csv2arr(path2summary)[4:] # throw out first 4 rows
    for m in trans2grab:
        for k in rows2grab:
            data.append(summary[11*m + k][3:])
            x = 10*m + k + 4  # in original csv (not counting blank rows)
            data_guide.append(fn[:-4] + '_({}-{}-{}))'.format(m, k, x))

data = transpose(data)
data.insert(0, data_guide)
arr2csv(data, filename=outf)

Example #3

# if None, defaults to 'summary_data.csv' (in the folder containing this
# script)
outf = None

#####################################################
# set defaults
if not rows2grab:
    rows2grab = [2, 3]
if not trans2grab:
    trans2grab = range(10)
if not summary_dir:
    summary_dir = os.path.join(os.getcwd(), 'summaries')
if not outf:
    outf = 'summary_data.csv'

# do stuff
data = []
data_guide = []
for fn in os.listdir(summary_dir):
    path2summary = os.path.join(summary_dir, fn)
    summary = csv2arr(path2summary)[4:]  # throw out first 4 rows
    for m in trans2grab:
        for k in rows2grab:
            data.append(summary[11 * m + k][3:])
            x = 10 * m + k + 4  # in original csv (not counting blank rows)
            data_guide.append(fn[:-4] + '_({}-{}-{}))'.format(m, k, x))

data = transpose(data)
data.insert(0, data_guide)
arr2csv(data, filename=outf)

Example #4

File: main.py Project: mathandy/svgtree_analysistool

if opt.DEBUG_MODE_ON:
    from testingtools import gen_new_fake_data
    opt.RAINFALLDATA_FN = 'dummy_rainfalldata.csv'
    opt.SAMPLEDATA_FN = 'dummy_sampledata.csv'
    opt.RAIN_DATA_HAS_HEADERS = False
    opt.SAMPLE_DATA_HAS_HEADERS = False

    if opt.GENERATE_NEW_FAKE_DATA:
        args = (opt.N_RAIN, opt.N_SAMPLES, opt.REL_NOISE, opt.MEAN_SLOPE)
        gen_new_fake_data(*args)


############################################################
# Data Pre-Processing
############################################################
assert 0 <= opt.MIN_OVERLAP <= len(csv2arr(opt.RAINFALLDATA_FN))

# format and normalize rainfall data
rain = csv2arr(opt.RAINFALLDATA_FN, hasheaders=opt.RAIN_DATA_HAS_HEADERS)
rain = list(np.array(rain).T[0])  # convert Nx1 array to list


rain = [float(x) for x in rain]

# read and format sample data and take the transpose
# (so now each sample is a row)
sampledata = csv2arr(opt.SAMPLEDATA_FN, hasheaders=opt.SAMPLE_DATA_HAS_HEADERS)

# take the transpose (so now each sample is a row)
sampledata = transpose(sampledata)

Example #5

File: testingtools.py Project: mathandy/svgtree_analysistool

def get_fake_data_params():
    shifts, slopes, constants = csv2arr('dummy_params.csv', dtype=float)
    shifts = [int(x) for x in shifts]
    return shifts, slopes, constants

Example #6

File: testingtools.py Project: mathandy/svg-dendro_analysistool

def get_fake_data_params():
    shifts, slopes, constants = csv2arr('dummy_params.csv', dtype=float)
    shifts = [int(x) for x in shifts]
    return shifts, slopes, constants