def gen_shot_pos_bmag_correlation(refPos,
pos,
shot,
filt,
window,
norm='ref',
normalized=True):
""" This function outputs the bmag correlation of shot at pos
and the corresponding time delay."""
normArray = norms.which_norm(norm, refPos, window, filt)
def norm_value(norm, posIndex, shot):
""" Wrapper function to make choosing the norm value easier"""
if norm.lower() == 'ref':
normValue = normArray[shot]
else:
normValue = normArray[posIndex, shot]
return normValue
bmagRef, time = tools.get_windowed_filtered_bmag(pos=refPos,
shot=shot,
window=window,
filt=filt)
bmagPos, _ = tools.get_windowed_filtered_bmag(pos, shot, window, filt)
magCorr, tau = tools.correlation(bmagRef, bmagPos, time)
if normalized:
posIndex = tools.get_pos_index(refPos, pos)
normMagCorr = magCorr / norm_value(norm, posIndex, shot)
else:
normMagCorr = magCorr
return normMagCorr, tau
def gen_bmag_temporal_correlation(refPos, filt, window, norm='ref'):
""" Outputs the spatial correlation array based on the bmag data. """
normArray = norms.which_norm(norm, refPos, window, filt)
def norm_value(norm, posIndex, shot):
""" Wrapper function to make choosing the norm value easier"""
if norm.lower() == 'ref':
normValue = normArray[shot]
else:
normValue = normArray[posIndex, shot]
return normValue
magShotArray = np.asarray([])
for shot in range(0, 25):
Bmag1, time = tools.get_windowed_filtered_bmag(refPos, shot, window,
filt)
corr_MagHold, tau = tools.correlation(Bmag1, Bmag1, time, mode='same')
corr_MagHold = np.abs(corr_MagHold)
normValue = norm_value(norm, 0, shot)
if (shot == 0):
corr_Mag = corr_MagHold / (25 * normValue)
else:
corr_Mag += corr_MagHold / (25 * normValue)
magShotArray = np.append(magShotArray, corr_Mag)
return magShotArray, tau
def gen_shot_pos_unproccessed_bmag_correlation(refPos,
pos,
shot,
norm='ref',
normalized=True):
""" Outputs the two-time correlation and time delay of Bmags from refPos and pos for shot.
This correlation is for the time-of-flight analysis and will not be windowed or filtered.
"""
normArray = norms.which_norm_tof(norm, refPos)
def norm_value(norm, posIndex, shot):
""" Wrapper function to make choosing the norm value easier"""
if norm.lower() == 'ref':
normValue = normArray[shot]
else:
normValue = normArray[posIndex, shot]
return normValue
refBmag, _ = tools.get_bmag(pos=refPos, shot=shot)
bmag, time = tools.get_bmag(pos=pos, shot=shot)
magCorr, tau = tools.correlation(refBmag, bmag, time)
if normalized:
posIndex = tools.get_pos_index(refPos, pos)
normMagCorr = magCorr / norm_value(norm, posIndex, shot)
else:
normMagCorr = magCorr
return normMagCorr, tau
def shot_bmag_refnorm_tof(refPos):
""" Outputs the Bmag normalization per shot based on the reference probe."""
normArray = np.zeros(25)
for shot in range(0, 25):
bmag, time = tools.get_bmag(pos=refPos, shot=shot)
norm_Mag, _ = tools.correlation(bmag, bmag, time, mode='valid')
normArray[shot] = norm_Mag
return normArray
def shot_bmag_refnorm(refPos, window, filt):
""" Outputs the Bmag normalization per shot based on the reference probe."""
normArray = np.zeros(25)
for shot in range(0, 25):
wfBmag, time = tools.get_windowed_filtered_bmag(pos=refPos,
shot=shot,
window=window,
filt=filt)
norm_Mag, _ = tools.correlation(wfBmag, wfBmag, time, mode='valid')
normArray[shot] = norm_Mag
return normArray
def gen_shot_bmag_spatial_correlation(refPos,
shot,
filt=3e4,
window=[75, 150],
norm='ref'):
normArray = norms.which_norm(norm, refPos, window, filt)
def norm_value(norm, posIndex, shot):
""" Wrapper function to make choosing the norm value easier"""
if norm.lower() == 'ref':
normValue = normArray[shot]
else:
normValue = normArray[posIndex, shot]
return normValue
magShotArray = np.asarray([])
for pos2Index, pos2 in enumerate([*range(refPos, 16, 2)]):
Br_1, Bt_1, Bz_1, time = data03.load_data(refPos, shot)
Br_2, Bt_2, Bz_2, time = data03.load_data(pos2, shot)
if (pos2 == refPos):
start_Dex = BMX.finding_Index_Time(time * 1e-6, window[0])
if (window[1] != 190):
end_Dex = BMX.finding_Index_Time(time * 1e-6, window[1])
else:
end_Dex = -1
Bmag1 = np.sqrt(Br_1**2 + Bt_1**2 + Bz_1**2)
Bmag2 = np.sqrt(Br_2**2 + Bt_2**2 + Bz_2**2)
Bmag1 = tools.HPF(Bmag1, filt)
Bmag2 = tools.HPF(Bmag2, filt)
time = time[start_Dex:end_Dex]
Bmag1 = Bmag1[start_Dex:end_Dex]
Bmag2 = Bmag2[start_Dex:end_Dex]
corrMagHold, _ = tools.correlation(Bmag1, Bmag2, time, mode='valid')
# corr_MagHold = np.abs(corr_MagHold)
normValue = norm_value(norm=norm, posIndex=pos2Index, shot=shot)
normCorrMagHold = corrMagHold / normValue
magShotArray = np.append(magShotArray, normCorrMagHold)
return magShotArray
def gen_shot_pos_unfiltered_bmag_correlation(refPos,
pos,
shot,
window=[75, 150],
norm='ref',
normalized=False):
""" Output the correlation and time-delay of windowed Bmag correlations between the specified
probes.
"""
normArray = norms.which_windowed_norm(norm, refPos, window)
def norm_value(norm, posIndex, shot):
""" Wrapper function to make choosing the norm value easier"""
if norm.lower() == 'ref':
normValue = normArray[shot]
else:
normValue = normArray[posIndex, shot]
return normValue
refBmag, _ = tools.get_windowed_bmag(pos=refPos, shot=shot, window=window)
bmag, time = tools.get_windowed_bmag(pos=pos, shot=shot, window=window)
# create new function and delete
#refBmag -= np.mean(refBmag)
#bmag -= np.mean(bmag)
magCorr, tau = tools.correlation(refBmag,
bmag,
time,
normalized=normalized)
if normalized:
posIndex = tools.get_pos_index(refPos, pos)
normMagCorr = magCorr / norm_value(norm, posIndex, shot)
else:
normMagCorr = magCorr
return normMagCorr, tau