# the FOV
cvmag_lim = 6.1
catalog_star_table = sdt[sdt.vmag < cvmag_lim]
catalog_stars = stars[sdt.vmag < cvmag_lim]
# Define telescope frame
location = EarthLocation.from_geodetic(lon=14.974609,
lat=37.693267,
height=1750)
obstime = Time("2019-05-09T01:37:54.728026")
altaz_frame = AltAz(location=location, obstime=obstime)
# Get pixel coordinates from TargetCalib
from target_calib import CameraConfiguration
camera_config = CameraConfiguration("1.1.0")
mapping = camera_config.GetMapping()
xpix = np.array(mapping.GetXPixVector()) # * u.m
ypix = np.array(mapping.GetYPixVector()) # * u.m
pos = np.array(
[np.array(mapping.GetXPixVector()),
np.array(mapping.GetYPixVector())])
size = mapping.GetSize() * u.m
area = size**2
pix_area = np.full(xpix.size, area) * area.unit
focal_length = u.Quantity(2.15191, u.m)
from ssm.pointing.astrometry import (
rotang,
rot_matrix,
generate_hotspots,
StarPatternMatch,
matchpattern,
class SimtelReader(WaveformReader):
def __init__(self, path, max_events=None):
"""
Reads simtelarray files utilising the SimTelEventSource from ctapipe
Parameters
----------
path : str
Path to the simtel file
max_events : int
Maximum number of events to read from the file
"""
super().__init__(path, max_events)
try:
from ctapipe.io import SimTelEventSource, EventSeeker
from ctapipe.coordinates import EngineeringCameraFrame
except ModuleNotFoundError:
msg = "Cannot find ctapipe installation"
raise ModuleNotFoundError(msg)
try:
from target_calib import CameraConfiguration
except ModuleNotFoundError:
msg = ("Cannot find TARGET libraries, please follow installation "
"instructions from https://forge.in2p3.fr/projects/gct/"
"wiki/Installing_CHEC_Software")
raise ModuleNotFoundError(msg)
self.path = path
reader = SimTelEventSource(input_url=path,
max_events=max_events,
back_seekable=True)
self.seeker = EventSeeker(reader)
first_event = self.seeker[0]
tels = list(first_event.r0.tels_with_data)
self.tel = tels[0]
shape = first_event.r0.tel[self.tel].waveform.shape
_, self.n_pixels, self.n_samples = shape
self.n_modules = self.n_pixels // 64
self.index = 0
n_modules = 32
camera_version = "1.1.0"
self._camera_config = CameraConfiguration(camera_version)
tc_mapping = self._camera_config.GetMapping(n_modules == 1)
self.mapping = get_clp_mapping_from_tc_mapping(tc_mapping)
n_rows = self.mapping.metadata['n_rows']
n_columns = self.mapping.metadata['n_columns']
camera_geom = first_event.inst.subarray.tel[tels[0]].camera
engineering_frame = EngineeringCameraFrame(n_mirrors=2)
engineering_geom = camera_geom.transform_to(engineering_frame)
pix_x = engineering_geom.pix_x.value
pix_y = engineering_geom.pix_y.value
row, col = get_row_column(pix_x, pix_y)
camera_2d = np.zeros((n_rows, n_columns), dtype=np.int)
camera_2d[row, col] = np.arange(self.n_pixels, dtype=np.int)
self.pixel_order = camera_2d[self.mapping['row'], self.mapping['col']]
self.reference_pulse_path = self._camera_config.GetReferencePulsePath()
self.camera_version = self._camera_config.GetVersion()
self.gps_time = None
self.mc_true = None
self.mc = None
self.pointing = None
self.mcheader = None
def _get_event(self, iev):
event = self.seeker[iev]
self._fill_event_containers(event)
waveforms = event.r1.tel[self.tel].waveform[0]
waveforms = waveforms[self.pixel_order]
return waveforms
@staticmethod
def is_compatible(path):
# read the first 4 bytes
with open(path, 'rb') as f:
marker_bytes = f.read(4)
# if file is gzip, read the first 4 bytes with gzip again
if marker_bytes[0] == 0x1f and marker_bytes[1] == 0x8b:
with gzip.open(path, 'rb') as f:
marker_bytes = f.read(4)
# check for the simtel magic marker
int_marker, = struct.unpack('I', marker_bytes)
return int_marker == 3558836791 or int_marker == 931798996
def __iter__(self):
for event in self.seeker:
self._fill_event_containers(event)
waveforms = event.r1.tel[self.tel].waveform[0]
waveforms = waveforms[self.pixel_order]
yield waveforms
def _fill_event_containers(self, event):
self.index = event.count
self.run_id = event.r0.obs_id
self.gps_time = event.trig.gps_time
self.mc_true = event.mc.tel[self.tel].photo_electron_image
self.mc_true = self.mc_true[self.pixel_order]
self.mc = dict(iev=self.index,
t_cpu=self.t_cpu,
energy=event.mc.energy.value,
alt=event.mc.alt.value,
az=event.mc.az.value,
core_x=event.mc.core_x.value,
core_y=event.mc.core_y.value,
h_first_int=event.mc.h_first_int.value,
x_max=event.mc.x_max.value,
shower_primary_id=event.mc.shower_primary_id)
self.pointing = dict(
iev=self.index,
t_cpu=self.t_cpu,
azimuth_raw=event.mc.tel[self.tel].azimuth_raw,
altitude_raw=event.mc.tel[self.tel].altitude_raw,
azimuth_cor=event.mc.tel[self.tel].azimuth_cor,
altitude_cor=event.mc.tel[self.tel].altitude_cor,
)
if self.mcheader is None:
mch = event.mcheader
self.mcheader = dict(
corsika_version=mch.corsika_version,
simtel_version=mch.simtel_version,
energy_range_min=mch.energy_range_min.value,
energy_range_max=mch.energy_range_max.value,
prod_site_B_total=mch.prod_site_B_total.value,
prod_site_B_declination=mch.prod_site_B_declination.value,
prod_site_B_inclination=mch.prod_site_B_inclination.value,
prod_site_alt=mch.prod_site_alt.value,
spectral_index=mch.spectral_index,
shower_prog_start=mch.shower_prog_start,
shower_prog_id=mch.shower_prog_id,
detector_prog_start=mch.detector_prog_start,
detector_prog_id=mch.detector_prog_id,
num_showers=mch.num_showers,
shower_reuse=mch.shower_reuse,
max_alt=mch.max_alt.value,
min_alt=mch.min_alt.value,
max_az=mch.max_az.value,
min_az=mch.min_az.value,
diffuse=mch.diffuse,
max_viewcone_radius=mch.max_viewcone_radius.value,
min_viewcone_radius=mch.min_viewcone_radius.value,
max_scatter_range=mch.max_scatter_range.value,
min_scatter_range=mch.min_scatter_range.value,
core_pos_mode=mch.core_pos_mode,
injection_height=mch.injection_height.value,
atmosphere=mch.atmosphere,
corsika_iact_options=mch.corsika_iact_options,
corsika_low_E_model=mch.corsika_low_E_model,
corsika_high_E_model=mch.corsika_high_E_model,
corsika_bunchsize=mch.corsika_bunchsize,
corsika_wlen_min=mch.corsika_wlen_min.value,
corsika_wlen_max=mch.corsika_wlen_max.value,
corsika_low_E_detail=mch.corsika_low_E_detail,
corsika_high_E_detail=mch.corsika_high_E_detail,
)
@property
def n_events(self):
return len(self.seeker)
@property
def t_cpu(self):
return pd.to_datetime(self.gps_time.value, unit='s')
def tc_mapping(self):
from target_calib import CameraConfiguration
version = self.mapping.metadata.version
camera_config = CameraConfiguration(version)
return camera_config.GetMapping(self.n_modules == 1)
class TIOReader:
"""
Reader for the R0 and R1 tio files
"""
def __init__(self, path, max_events=None):
try:
from target_io import WaveformArrayReader
from target_calib import CameraConfiguration
except ModuleNotFoundError:
msg = ("Cannot find TARGET libraries, please follow installation "
"instructions from https://forge.in2p3.fr/projects/gct/"
"wiki/Installing_CHEC_Software")
raise ModuleNotFoundError(msg)
if not os.path.exists(path):
raise FileNotFoundError("File does not exist: {}".format(path))
self.path = path
self._reader = WaveformArrayReader(self.path, 2, 1)
self.is_r1 = self._reader.fR1
self.n_events = self._reader.fNEvents
self.run_id = self._reader.fRunID
self.n_pixels = self._reader.fNPixels
self.n_modules = self._reader.fNModules
self.n_tmpix = self.n_pixels // self.n_modules
self.n_samples = self._reader.fNSamples
self._camera_config = CameraConfiguration(self._reader.fCameraVersion)
self.tc_mapping = self._camera_config.GetMapping(self.n_modules == 1)
self._pixel = self._PixelWaveforms(self)
self.n_cells = self._camera_config.GetNCells()
self.camera_version = self._camera_config.GetVersion()
self.reference_pulse_path = self._camera_config.GetReferencePulsePath()
self.current_tack = None
self.current_cpu_ns = None
self.current_cpu_s = None
self.first_cell_ids = np.zeros(self.n_pixels, dtype=np.uint16)
if self.is_r1:
self.samples = np.zeros((self.n_pixels, self.n_samples),
dtype=np.float32)
self.get_tio_event = self._reader.GetR1Event
else:
self.samples = np.zeros((self.n_pixels, self.n_samples),
dtype=np.uint16)
self.get_tio_event = self._reader.GetR0Event
if max_events and max_events < self.n_events:
self.n_events = max_events
def _get_event(self, iev):
self.index = iev
self.get_tio_event(iev, self.samples, self.first_cell_ids)
self.current_tack = self._reader.fCurrentTimeTack
self.current_cpu_ns = self._reader.fCurrentTimeNs
self.current_cpu_s = self._reader.fCurrentTimeSec
return self.samples
def __iter__(self):
for iev in range(self.n_events):
yield self._get_event(iev)
def __getitem__(self, iev):
return np.copy(self._get_event(iev))
class _PixelWaveforms:
def __init__(self, tio_reader):
self.reader = tio_reader
def __getitem__(self, p):
if not isinstance(p, list) and not isinstance(p, np.ndarray):
p = [p]
n_events = self.reader.n_events
n_pixels = len(p)
n_samples = self.reader.n_samples
waveforms = np.zeros((n_events, n_pixels, n_samples))
for iev, wf in enumerate(self.reader):
waveforms[iev] = wf[p]
return waveforms
@property
def pixel(self):
return self._pixel
@property
def mapping(self):
return get_clp_mapping_from_tc_mapping(self.tc_mapping)
def get_sn(self, tm):
if tm >= self.n_modules:
raise IndexError("Requested TM out of range: {}".format(tm))
return self._reader.GetSN(tm)
@staticmethod
def is_compatible(filepath):
try:
h = fits.getheader(filepath, 0)
if 'EVENT_HEADER_VERSION' not in h:
return False
except IOError:
return False
return True
class TIOReader(WaveformReader):
def __init__(self, path, max_events=None,
skip_events=2, skip_end_events=1):
"""
Utilies TargetIO to read R0 and R1 tio files. Enables easy access to
the waveforms for anaylsis.
Waveforms can be read from the file by either indexing this reader or
iterating over it:
>>> path = "/path/to/file_r0.tio"
>>> reader = TIOReader(path)
>>> wf = reader[3] # Obtain the waveforms for the third event
>>> path = "/path/to/file_r0.tio"
>>> reader = TIOReader(path)
>>> wfs = reader[:10] # Obtain the waveforms for the first 10 events
>>> path = "/path/to/file_r0.tio"
>>> reader = TIOReader(path)
>>> for wf in reader: # Iterate over all events in the file
>>> print(wf)
Parameters
----------
path : str
Path to the _r0.tio or _r1.tio file
max_events : int
Maximum number of events to read from the file
"""
super().__init__(path, max_events)
try:
from target_io import WaveformArrayReader
from target_calib import CameraConfiguration
except ModuleNotFoundError:
msg = ("Cannot find TARGET libraries, please follow installation "
"instructions from https://forge.in2p3.fr/projects/gct/"
"wiki/Installing_CHEC_Software")
raise ModuleNotFoundError(msg)
self._reader = WaveformArrayReader(
self.path, skip_events, skip_end_events
)
self.is_r1 = self._reader.fR1
self._n_events = self._reader.fNEvents
self.run_id = self._reader.fRunID
self.n_pixels = self._reader.fNPixels
self.n_superpixels_per_module = self._reader.fNSuperpixelsPerModule
self.n_modules = self._reader.fNModules
self.n_tmpix = self.n_pixels // self.n_modules
self.n_samples = self._reader.fNSamples
self._camera_config = CameraConfiguration(self._reader.fCameraVersion)
self.tc_mapping = self._camera_config.GetMapping(self.n_modules == 1)
self.n_cells = self._camera_config.GetNCells()
self.camera_version = self._camera_config.GetVersion()
self.reference_pulse_path = self._camera_config.GetReferencePulsePath()
if self.is_r1:
self.dtype = np.float32
self.get_tio_event = self._reader.GetR1Event
else:
self.dtype = np.uint16
self.get_tio_event = self._reader.GetR0Event
if max_events and max_events < self._n_events:
self._n_events = max_events
def _get_event(self, iev):
samples = np.zeros((self.n_pixels, self.n_samples), self.dtype)
(first_cell_id, stale, missing_packets,
t_tack, t_cpu_s, t_cpu_ns) = self.get_tio_event(iev, samples)
waveform = Waveform(
input_array=samples,
iev=iev,
is_r1=self.is_r1,
first_cell_id=first_cell_id,
missing_packets=missing_packets,
stale=stale,
t_tack=t_tack,
t_cpu_container=(t_cpu_s, t_cpu_ns),
)
return waveform
@staticmethod
def is_compatible(path):
with open(path, 'rb') as f:
marker_bytes = f.read(1024)
# if file is gzip, read the first 4 bytes with gzip again
if marker_bytes[0] == 0x1f and marker_bytes[1] == 0x8b:
with gzip.open(path, 'rb') as f:
marker_bytes = f.read(1024)
if b'FITS' not in marker_bytes:
return False
try:
h = fits.getheader(path, 0)
if 'EVENT_HEADER_VERSION' not in h:
return False
except IOError:
return False
return True
@property
def n_events(self):
return self._n_events
@property
def mapping(self):
return get_clp_mapping_from_tc_mapping(self.tc_mapping)
def get_sn(self, tm):
"""
Get the SN of the TARGET module in a slot
Parameters
----------
tm : int
Slot number for the TARGET module
Returns
-------
int
Serial number of the TM
"""
if tm >= self.n_modules:
raise IndexError("Requested TM out of range: {}".format(tm))
return self._reader.GetSN(tm)
def get_sipm_temp(self, tm):
if tm >= self.n_modules:
raise IndexError("Requested TM out of range: {}".format(tm))
return self._reader.GetSiPMTemp(tm)
def get_primary_temp(self, tm):
if tm >= self.n_modules:
raise IndexError("Requested TM out of range: {}".format(tm))
return self._reader.GetPrimaryTemp(tm)
def get_sp_dac(self, tm, sp):
if tm >= self.n_modules:
raise IndexError("Requested TM out of range: {}".format(tm))
if sp >= self.n_superpixels_per_module:
raise IndexError("Requested SP out of range: {}".format(sp))
return self._reader.GetSPDAC(tm, sp)
def get_sp_hvon(self, tm, sp):
if tm >= self.n_modules:
raise IndexError("Requested TM out of range: {}".format(tm))
if sp >= self.n_superpixels_per_module:
raise IndexError("Requested SP out of range: {}".format(sp))
return self._reader.GetSPHVON(tm, sp)
def main():
file_dir = os.path.dirname(os.path.abspath(__file__))
output_dir = os.path.join(file_dir, "outputs")
output_path = os.path.join(output_dir, "checs_pixel_mapping.dat")
config = CameraConfiguration("1.1.0")
mapping = config.GetMapping()
mappingsp = mapping.GetMappingSP()
qe_arr = np.load(os.path.join(file_dir, 'outputs/checs_qe_variation.npy'))
gain_arr = np.load(os.path.join(file_dir, 'outputs/checs_gain_variation.npy'))
with open(output_path, 'w') as f:
pixtype = """# PixType format:
# Par. 1: pixel type (here always 1)
# 2: PMT type (must be 0)
# 3: cathode shape type
# 4: visible cathode diameter [cm]
# 5: funnel shape type (see above)
# 6: funnel diameter (flat-to-flat for hex.) [cm]
# 7: depth of funnel [cm]
# 8: a) funnel efficiency "filename", b) funnel plate transparency
# 9: a) optional wavelength "filename", b) funnel wall reflectivity
# In case a) in column 8, columns 3+7 are not used. If in case a) the
# optional file name for the wavelength dependence is provided, the
# overall scale in the file provided as parameter 8 is ignored because
# it is rescaled such that the average over all mirrors is equal to
# the given wavelength dependent value.
#
# Shape types: 0: circ., 1: hex(flat x), 2: sq., 3: hex(flat y)
#
#Angular Dep currently all set to one for checks
# Note that pixel size is scale from the actual 6.125 mm at the focal length
# planned with GATE telescopes (228.3 cm) to the focal length of ASTRI (215 cm).
# Similarly scaled are the pixel positions.
PixType 1 0 2 0.623 2 0.623 0.0 "transmission_pmma_vs_theta_20150422.dat" "transmission_pmma_vs_lambda_meas0deg_coat_82raws.dat"
# Pixel format:
# Par. 1: pixel number (starting at 0)
# 2: pixel type (must be 1)
# 3: x position [cm]
# 4: y position [cm]
# 5: drawer/module number
# 6: board number in module
# 7: channel number n board
# 8: board Id number ('0x....')
# 9: pixel on (is on if parameter is missing)
# 10: relative QE or PDE (1 if unused)
# 11: relative gain (1 if unused)
"""
f.write(pixtype)
for i in range(mapping.GetNPixels()):
ipix = mapping.GetPixel(i)
xpix = mapping.GetXPix(i) * 10**2
ypix = mapping.GetYPix(i) * 10**2
imod = mapping.GetSlot(i)
ichan = mapping.GetTMPixel(i)
qe = 1#qe_arr[i]
gain = 1#gain_arr[i]
l = "Pixel\t{}\t1\t{:.5f}\t{:.5f}\t{}\t0\t{}\t0x00\t1\t{:.5f}\t{:.5f}\n"
lf = l.format(ipix, xpix, ypix, imod, ichan, qe, gain)
f.write(lf)
f.write('\n')
for i in range(mappingsp.GetNSuperPixels()):
nei = mappingsp.GetNeighbours(i, True)
f.write("MajorityTrigger * of ")
for isp in [i, *nei]:
con = list(mappingsp.GetContainedPixels(isp))
rows = [mapping.GetRow(j) for j in con]
cols = [mapping.GetColumn(j) for j in con]
min_r = np.min(rows)
min_c = np.min(cols)
con_bl = con[np.where((rows == min_r) & (cols == min_c))[0][0]]
con.remove(con_bl)
f.write('{}[{},{},{}] '.format(con_bl, *con))
f.write('\n')