def plotMiniscan0p1a(obspaths, fileLevel):
hdf5Files, hdf5Filenames, _ = makeFileList(obspaths,
fileLevel,
silent=True)
#from plot_animations_v01 import animateLines
plt.figure()
#for fileIndex, (hdf5_file, hdf5_filename) in enumerate(zip(hdf5Files, hdf5Filenames)):
for fileIndex, (hdf5_file, hdf5_filename) in enumerate(
zip(hdf5Files[3:4], hdf5Filenames[3:4])):
detectorData = hdf5_file["Science/Y"][...]
aotfFrequency = hdf5_file["Channel/AOTFFrequency"][...]
# exponent = hdf5_file["Channel/Exponent"][...]
detectorDataMean = np.mean(detectorData[:, 12:13], axis=1)
# a = animateLines([detectorDataMean])
# plotIndices = [0,1,2,3,256,257]
# cmap = plt.get_cmap('jet')
# colours = [cmap(i) for i in aotfFrequency[np.asarray(plotIndices)]]
# for plotIndex in plotIndices:
## plt.plot(detectorDataMean[plotIndex,:], label=aotfFrequency[plotIndex])
plt.plot(aotfFrequency,
detectorDataMean[:, 100] / np.mean(detectorDataMean, axis=1))
plt.plot(aotfFrequency,
detectorDataMean[:, 200] / np.mean(detectorDataMean, axis=1))
def searchForMiniscans(regex, fileLevel):
hdf5Files, hdf5Filenames, titles = makeFileList(regex,
fileLevel,
open_files=False,
silent=True)
for hdf5_filename in hdf5Filenames:
hdf5_filename_split = hdf5_filename.split("_")
if len(hdf5_filename_split) == 6:
if hdf5_filename_split[-1] == "S":
name, hdf5_file = getFile(hdf5_filename,
fileLevel,
0,
silent=True)
detectorData = hdf5_file["Science/Y"][...]
nSpectra = detectorData.shape[0]
alts = hdf5_file["Geometry/Point0/TangentAltAreoid"][:, 0]
if alts[0] > 250.0 and alts[-1] > 250.0:
print("Warning: merged occultation")
print("nSpectra=%i, hdf5_filename=%s, orders=" %
(nSpectra, hdf5_filename))
print(
list(set(list(
hdf5_file["Channel/DiffractionOrder"][...]))))
from fit_absorption_band_v01 import fit_gaussian_absorption
from hdf5_functions_v04 import BASE_DIRECTORY, DATA_DIRECTORY, LOCAL_DIRECTORY, FIG_X, FIG_Y, makeFileList
from plot_solar_line_simulations_lno import smoothHighRes #, nu_mp, t_p0
SMOOTHING_LEVEL = 600 #must be even number
MAKE_CALIBRATION_TABLE = True
#MAKE_CALIBRATION_TABLE = False
regex = re.compile(
"(20161121_233000_0p1a_LNO_1|20180702_112352_0p1a_LNO_1|20181101_213226_0p1a_LNO_1|20190314_021825_0p1a_LNO_1|20190609_011514_0p1a_LNO_1|20191207_051654_0p1a_LNO_1)"
)
fileLevel = "hdf5_level_0p1a"
hdf5Files, hdf5Filenames, titles = makeFileList(regex, fileLevel)
#new values from order 118 solar line
#Q0=-10.159
#Q1=-0.8688
#new values from mean gradient/offset of best orders: 142, 151, 156, 162, 166, 167, 178, 189, 194
Q0 = -10.13785778
Q1 = -0.829174444
#old values
#Q0=-6.267734
#Q1=-7.299039e-1
Q2 = 0.0
def t_p0(t, Q0=Q0, Q1=Q1, Q2=Q2):
"""instrument temperature to pixel0 shift"""
detectorData = hdf5_file["Science/Y"][...]
nSpectra = detectorData.shape[0]
alts = hdf5_file["Geometry/Point0/TangentAltAreoid"][:, 0]
if alts[0] > 250.0 and alts[-1] > 250.0:
print("Warning: merged occultation")
print("nSpectra=%i, hdf5_filename=%s, orders=" %
(nSpectra, hdf5_filename))
print(
list(set(list(
hdf5_file["Channel/DiffractionOrder"][...]))))
"""search for specific miniscans in dataset"""
#searchForMiniscans(regex, fileLevel)
"""plot miniscans"""
hdf5Files, hdf5Filenames, _ = makeFileList(regex, fileLevel, silent=True)
hdf5_file = hdf5Files[0]
hdf5_filename = hdf5Filenames[0]
plt.figure(figsize=(FIG_X, FIG_Y))
alts = hdf5_file["Geometry/Point0/TangentAltAreoid"][:, 0]
if alts[0] > 250.0 and alts[-1] > 250.0:
isMerged = True
halfLength = int(len(alts) / 2)
if isMerged:
alts = alts[0:halfLength]
detectorData = hdf5_file["Science/Y"][0:halfLength, 50:]