2. Preparation of calibration data

%matplotlib inline

from meas_data_preprocessing import *
from hydrophone_data_preprocessing import *

Read calibration data for selected measurement scenario

infos, hyd_data = read_calib_data(meas_scenario=13, do_plot=False)

Checking if file ../datasets/pD7_MH44.DAT is already present or download it from https://raw.githubusercontent.com/Ma-Weber/Tutorial-Deconvolution/master/MeasuredSignals/pD-Mode%207%20MHz/pD7_MH44.DAT otherwise:
Replace is False and data exists, so doing nothing. Use replace=True to re-download the data.
Checking if file ../datasets/pD7_MH44r.DAT is already present or download it from https://raw.githubusercontent.com/Ma-Weber/Tutorial-Deconvolution/master/MeasuredSignals/pD-Mode%207%20MHz/pD7_MH44r.DAT otherwise:
Replace is False and data exists, so doing nothing. Use replace=True to re-download the data.
Checking if file ../datasets/MW_MH44ReIm.csv is already present or download it from https://raw.githubusercontent.com/Ma-Weber/Tutorial-Deconvolution/master/HydrophoneCalibrationData/MW_MH44ReIm.csv otherwise:
Replace is False and data exists, so doing nothing. Use replace=True to re-download the data.

# metadata for chosen measurement scenario
for key in infos.keys():
    print("%20s: %s" % (key, infos[key]))

                   i: 13
       hydrophonname: GAMPT MH44
     measurementtype: Pulse-Doppler-Mode 7 MHz
     measurementfile: ../datasets/pD7_MH44.DAT
           noisefile: ../datasets/pD7_MH44r.DAT
         hydfilename: ../datasets/MW_MH44ReIm.csv

# available measurement data
for key in hyd_data.keys():
    print("%10s: %s" % (key, type(hyd_data[key])))

      name: <class 'str'>
 frequency: <class 'numpy.ndarray'>
      real: <class 'numpy.ndarray'>
      imag: <class 'numpy.ndarray'>
   varreal: <class 'numpy.ndarray'>
   varimag: <class 'numpy.ndarray'>
       cov: <class 'numpy.ndarray'>

Reduce frequency range

hyd_data = reduce_freq_range(hyd_data, fmin=1e6, fmax=100e6)

Plot amplitude and phase data

figure(figsize=(16, 8))
plot(
    hyd_data["frequency"] / 1e6, np.sqrt(hyd_data["real"] ** 2 + hyd_data["imag"] ** 2)
)
xlabel("Frequency f / MHz")
ylabel("Sensitivity M / V/Pa")
title("Filename: {}".format(hyd_data["name"]))
show()

figure(figsize=(16, 8))
plot(hyd_data["frequency"] / 1e6, np.arctan2(hyd_data["imag"], hyd_data["real"]))
xlabel("Frequency f / MHz")
ylabel(r"Phase $\varphi$ / rad")
title("Filename: {}".format(hyd_data["name"]))
show()