def __init__(self, filename,
dataset_type='fits',
auxiliary_files=[],
nprocs=None,
storage_filename=None,
nan_mask=None,
suppress_astropy_warnings=True,
parameters=None,
units_override=None,
unit_system="cgs"):
if parameters is None:
parameters = {}
parameters["nprocs"] = nprocs
self.specified_parameters = parameters
if suppress_astropy_warnings:
warnings.filterwarnings('ignore', module="astropy", append=True)
auxiliary_files = ensure_list(auxiliary_files)
self.filenames = [filename] + auxiliary_files
self.num_files = len(self.filenames)
self.fluid_types += ("fits",)
if nan_mask is None:
self.nan_mask = {}
elif isinstance(nan_mask, float):
self.nan_mask = {"all":nan_mask}
elif isinstance(nan_mask, dict):
self.nan_mask = nan_mask
self._handle = FITSFileHandler(self.filenames[0])
if (isinstance(self.filenames[0], _astropy.pyfits.hdu.image._ImageBaseHDU) or
isinstance(self.filenames[0], _astropy.pyfits.HDUList)):
fn = "InMemoryFITSFile_%s" % uuid.uuid4().hex
else:
fn = self.filenames[0]
self._handle._fits_files.append(self._handle)
if self.num_files > 1:
for fits_file in auxiliary_files:
if isinstance(fits_file, _astropy.pyfits.hdu.image._ImageBaseHDU):
f = _astropy.pyfits.HDUList([fits_file])
elif isinstance(fits_file, _astropy.pyfits.HDUList):
f = fits_file
else:
if os.path.exists(fits_file):
fn = fits_file
else:
fn = os.path.join(ytcfg.get("yt","test_data_dir"),fits_file)
f = _astropy.pyfits.open(fn, memmap=True,
do_not_scale_image_data=True,
ignore_blank=True)
self._handle._fits_files.append(f)
self.refine_by = 2
Dataset.__init__(self, fn, dataset_type, units_override=units_override,
unit_system=unit_system)
self.storage_filename = storage_filename
def __init__(self,
filename,
dataset_type='fits',
auxiliary_files=[],
nprocs=None,
storage_filename=None,
nan_mask=None,
spectral_factor=1.0,
z_axis_decomp=False,
suppress_astropy_warnings=True,
parameters=None,
units_override=None,
unit_system="cgs"):
if parameters is None:
parameters = {}
parameters["nprocs"] = nprocs
self.specified_parameters = parameters
self.z_axis_decomp = z_axis_decomp
self.spectral_factor = spectral_factor
if suppress_astropy_warnings:
warnings.filterwarnings('ignore', module="astropy", append=True)
auxiliary_files = ensure_list(auxiliary_files)
self.filenames = [filename] + auxiliary_files
self.num_files = len(self.filenames)
self.fluid_types += ("fits", )
if nan_mask is None:
self.nan_mask = {}
elif isinstance(nan_mask, float):
self.nan_mask = {"all": nan_mask}
elif isinstance(nan_mask, dict):
self.nan_mask = nan_mask
self._handle = FITSFileHandler(self.filenames[0])
if (isinstance(self.filenames[0],
_astropy.pyfits.hdu.image._ImageBaseHDU)
or isinstance(self.filenames[0], _astropy.pyfits.HDUList)):
fn = "InMemoryFITSFile_%s" % uuid.uuid4().hex
else:
fn = self.filenames[0]
self._handle._fits_files.append(self._handle)
if self.num_files > 1:
for fits_file in auxiliary_files:
if isinstance(fits_file,
_astropy.pyfits.hdu.image._ImageBaseHDU):
f = _astropy.pyfits.HDUList([fits_file])
elif isinstance(fits_file, _astropy.pyfits.HDUList):
f = fits_file
else:
if os.path.exists(fits_file):
fn = fits_file
else:
fn = os.path.join(ytcfg.get("yt", "test_data_dir"),
fits_file)
f = _astropy.pyfits.open(fn,
memmap=True,
do_not_scale_image_data=True,
ignore_blank=True)
self._handle._fits_files.append(f)
if len(self._handle) > 1 and self._handle[1].name == "EVENTS":
self.events_data = True
self.first_image = 1
self.primary_header = self._handle[self.first_image].header
self.naxis = 2
self.wcs = _astropy.pywcs.WCS(naxis=2)
self.events_info = {}
for k, v in self.primary_header.items():
if k.startswith("TTYP"):
if v.lower() in ["x", "y"]:
num = k.strip("TTYPE")
self.events_info[v.lower()] = (
self.primary_header["TLMIN" + num],
self.primary_header["TLMAX" + num],
self.primary_header["TCTYP" + num],
self.primary_header["TCRVL" + num],
self.primary_header["TCDLT" + num],
self.primary_header["TCRPX" + num])
elif v.lower() in ["energy", "time"]:
num = k.strip("TTYPE")
unit = self.primary_header["TUNIT" + num].lower()
if unit.endswith("ev"): unit = unit.replace("ev", "eV")
self.events_info[v.lower()] = unit
self.axis_names = [self.events_info[ax][2] for ax in ["x", "y"]]
self.reblock = 1
if "reblock" in self.specified_parameters:
self.reblock = self.specified_parameters["reblock"]
self.wcs.wcs.cdelt = [
self.events_info["x"][4] * self.reblock,
self.events_info["y"][4] * self.reblock
]
self.wcs.wcs.crpix = [
(self.events_info["x"][5] - 0.5) / self.reblock + 0.5,
(self.events_info["y"][5] - 0.5) / self.reblock + 0.5
]
self.wcs.wcs.ctype = [
self.events_info["x"][2], self.events_info["y"][2]
]
self.wcs.wcs.cunit = ["deg", "deg"]
self.wcs.wcs.crval = [
self.events_info["x"][3], self.events_info["y"][3]
]
self.dims = [
(self.events_info["x"][1] - self.events_info["x"][0]) /
self.reblock,
(self.events_info["y"][1] - self.events_info["y"][0]) /
self.reblock
]
else:
self.events_data = False
# Sometimes the primary hdu doesn't have an image
if len(self._handle) > 1 and self._handle[0].header["naxis"] == 0:
self.first_image = 1
else:
self.first_image = 0
self.primary_header = self._handle[self.first_image].header
self.naxis = self.primary_header["naxis"]
self.axis_names = [
self.primary_header.get("ctype%d" % (i + 1), "LINEAR")
for i in range(self.naxis)
]
self.dims = [
self.primary_header["naxis%d" % (i + 1)]
for i in range(self.naxis)
]
wcs = _astropy.pywcs.WCS(header=self.primary_header)
if self.naxis == 4:
self.wcs = _astropy.pywcs.WCS(naxis=3)
self.wcs.wcs.crpix = wcs.wcs.crpix[:3]
self.wcs.wcs.cdelt = wcs.wcs.cdelt[:3]
self.wcs.wcs.crval = wcs.wcs.crval[:3]
self.wcs.wcs.cunit = [str(unit) for unit in wcs.wcs.cunit][:3]
self.wcs.wcs.ctype = [type for type in wcs.wcs.ctype][:3]
else:
self.wcs = wcs
self.refine_by = 2
Dataset.__init__(self,
fn,
dataset_type,
units_override=units_override,
unit_system=unit_system)
self.storage_filename = storage_filename