lowfield_mri_programs/spectrometer_service/SpectometerDecodeLib.py

import json
import base64
import numpy as np

class DataDecoder:
    def __init__(self, filename):
        self.data = ''
        with open(filename, 'r') as file:
            self.data = file.read()
        self.structed_data = json.loads(self.data)

    def getRawData(self, averaging_num=0, data_num=0, channel_num=0):
        for items in self.structed_data:
            if(items['averaging_num'] == averaging_num and items['data_num'] == data_num):
                for channel_data in items['channel_data']:
                    if(channel_data['channel_num'] == channel_num):
                        return channel_data['channel_data']
        return None

    def getDataDecoded(self, averaging_num=0, data_num=0, channel_num=0, points=10):
        rawData = self.getRawData(averaging_num, data_num, channel_num)
        edata = base64.b64decode(rawData.encode('utf-8'))
        arr = np.frombuffer(edata, dtype=np.int16, count=points, offset=0)
        return arr

    def getDataScaled(self, averaging_num=0, data_num=0, channel_num=0, points=10, range=5.0):
        decodedData = self.getDataDecoded(averaging_num, data_num, channel_num, points)
        return range * decodedData / 32768


#dec = DataDecoder('saved229.json')
# print(dec.getRawData(0, 0, 1)) # ::getRawData(averagingIndex, dataTriggerIndex, channelIndex)

# a = dec.getDataDecoded(0, 0, 0, 500)
# print(a[0:100]) # ::getDataDecoded(averagingIndex, dataTriggerIndex, channelIndex, count)

#a = dec.getDataScaled(0, 1, 1, 500, 5.0)
#print(a[0:100])