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)