def loadfile_rso(filename):
# initialize lists for reading
ltime = []
lT = []
lH = []
lM = []
lM_noAbs = []
lMerr = []
# reading data
with open(filename, "r", newline='') as f:
reader = csv.reader(f)
for row in reader:
if (len(row) > 1) and (
row[1] == ""
): # a valid data line only if the comment entry is ""
try:
ltime.append(float(row[0]))
except ValueError:
ltime.append(np.nan)
try:
lT.append(float(row[3]))
except ValueError:
lT.append(np.nan)
try:
lH.append(float(row[2]))
except ValueError:
lH.append(np.nan)
try:
lM.append(float(row[4]))
except ValueError:
lM.append(np.nan)
try:
lMerr.append(float(row[5]))
except ValueError:
lMerr.append(np.nan)
try:
lM_noAbs.append(float(row[18]))
except ValueError:
lM_noAbs.append(np.nan)
# Convert lists to datasets (dicts of 1D numpy arrays)
data = datasets.DataSet([
("time", np.array(ltime, dtype=np.float_, copy=True)),
("T", np.array(lT, dtype=np.float_, copy=True)),
("H", np.array(lH, dtype=np.float_, copy=True)),
("M", np.array(lM, dtype=np.float_, copy=True)),
("err_M", np.array(lMerr, dtype=np.float_, copy=True)),
("M_noAbs", np.array(lM_noAbs, dtype=np.float_, copy=True))
])
return data
def loadfile(filename):
with open(filename, mode="r") as f:
reader = csv.reader(f)
next(reader)
datalist = []
for var in VAR_ORDER:
datalist.append([])
for row in reader:
for i in range(0, len(row)):
datalist[i].append(float(row[i]))
# For backward compatibility #
for i in range(len(row), len(VAR_ORDER)):
datalist[i].append(float('nan'))
datadict = {}
for i in range(0, len(VAR_ORDER)):
datadict[VAR_ORDER[i]] = np.array(datalist[i], dtype=np.float_)
return datasets.DataSet(datadict)
def import_dc(filename):
# initialize lists for reading
ltime = []
lT = []
lH = []
lch1R = []
lch1err = []
lch2R = []
lch2err = []
lch3R = []
lch3err = []
# reading data
with open(filename, "r", newline='') as f:
reader = csv.reader(f)
for row in reader:
if row[0] == "": # a valid data line only if the comment entry is ""
try:
ltime.append(float(row[1]))
except ValueError:
ltime.append(np.nan)
try:
lT.append(float(row[3]))
except ValueError:
lT.append(np.nan)
try:
lH.append(float(row[4]))
except ValueError:
lH.append(np.nan)
try:
lch1R.append(float(row[19]))
except ValueError:
lch1R.append(np.nan)
try:
lch2R.append(float(row[20]))
except ValueError:
lch2R.append(np.nan)
try:
lch3R.append(float(row[21]))
except ValueError:
lch3R.append(np.nan)
# Calculating the standard errors assuming the stupid default resistivity calculation made by PPMS
try:
lch1err.append(float(row[14]) * 1.e3 / float(row[18])**0.5)
except ValueError:
lch1err.append(np.nan)
try:
lch2err.append(float(row[15]) * 1.e3 / float(row[18])**0.5)
except ValueError:
lch2err.append(np.nan)
try:
lch3err.append(float(row[16]) * 1.e3 / float(row[18])**0.5)
except ValueError:
lch3err.append(np.nan)
# Convert lists to datasets (dicts of 1D numpy arrays)
ch1 = datasets.DataSet([
("time", np.array(ltime, dtype=np.float_, copy=True)),
("T", np.array(lT, dtype=np.float_, copy=True)),
("H", np.array(lH, dtype=np.float_, copy=True)),
("R", np.array(lch1R, dtype=np.float_, copy=True)),
("err_R", np.array(lch1err, dtype=np.float_, copy=True))
])
ch2 = datasets.DataSet([
("time", np.array(ltime, dtype=np.float_, copy=True)),
("T", np.array(lT, dtype=np.float_, copy=True)),
("H", np.array(lH, dtype=np.float_, copy=True)),
("R", np.array(lch2R, dtype=np.float_, copy=True)),
("err_R", np.array(lch2err, dtype=np.float_, copy=True))
])
ch3 = datasets.DataSet([
("time", np.array(ltime, dtype=np.float_, copy=True)),
("T", np.array(lT, dtype=np.float_, copy=True)),
("H", np.array(lH, dtype=np.float_, copy=True)),
("R", np.array(lch3R, dtype=np.float_, copy=True)),
("err_R", np.array(lch3err, dtype=np.float_, copy=True))
])
return (ch1, ch2, ch3)