SkopeDataReader 1.3.0

Python reader to load data acquired with skope-fm or skope-fx

SkopeDataReader

Python reader to load data acquired with skope-fm or skope-fx

CONSTRUCTOR

scan = DataReader(folder, scanNr)

IN
folder: path of the folder containing the scan data files
scanNr: scan number

OUT
obj scan object holding scan definition

FUNCTIONS

getData(self, datatype, samples=[], channels=[], interleaves=[], dynamics=[])

IN
datatype: string (Type names are defined by the Acq System output file extensions: 'raw', 'phase', 'k', 'kspha', 'kcoco', 'Bfit', 'Gfit')
samples: numpy array of requested samples.
channels: numpy array of requested channels. Relative to acquired channels!
interleaves: numpy array of requested interleaves.
dynamics: numpy array of requested dynamics.

for samples, channels, interleaves, and dynamics: If not present or empty all acquired data is returned

OUT
data: size = [samples, channels, interleaves, dynamics]

getTriggerTimeData(self)

OUT
trigTimes: for versions <= 2022: np array with trigger times
for versions >= 2023: dict with 'triggerTimes' and 'flags'

filterData(self, data, frequencyKHz=50)

Note: this is a preliminary implementation for phase and k data only!

IN
data: data obtained by getData that will be filtered
frequencyKHz: cut off frequency for low pass filtering

OUT
data: filtered data

EXAMPLE USAGE

import SkopeDataReader
import numpy as np
from matplotlib import pyplot as plt

# set scan path & nr
dataPath = 'My\Data\Path'
scanNr   = 1

# Initialize DataReader
scan = SkopeDataReader.DataReader(dataPath, scanNr)

# Load and print trigger times
triggerTime = scan.getTriggerTimeData()
print(triggerTime)

# Load and plot raw data
rawData = scan.getData('raw')
fig, ax = plt.subplots()
ax.plot(abs(rawData[:,:,0,0]))
plt.show()

# Load, filter and plot kspha data
kData = scan.getData('kspha', samples=np.arange(10000))
kData = scan.filterData(kData, frequencyKHz=50)
fig, ax = plt.subplots()
ax.plot(kData[:,:,0,0])
plt.show()

# Load and plot Bfit data
BData = scan.getData('Bfit')
fig, ax = plt.subplots()
ax.plot(BData[0,:,0,:].transpose(), '.-')
plt.show()