Get ACA penalty and planning limits from chandra_models

proseco/catalog.py

@@ -44,6 +44,8 @@ def get_aca_catalog(obsid=0, **kwargs):
     :param man_angle: maneuver angle (deg)
     :param t_ccd_acq: ACA CCD temperature for acquisition (degC)
     :param t_ccd_guide: ACA CCD temperature for guide (degC)
+    :param t_ccd_penalty_limit: ACA CCD penalty limit for planning (degC). If not
+        provided this defaults to value from the ACA xija thermal model.
     :param date: date of acquisition (any DateTime-compatible format)
     :param dither_acq: acq dither size (2-element sequence (y, z), arcsec)
     :param dither_guide: guide dither size (2-element sequence (y, z), arcsec)
@@ -110,11 +112,14 @@ def _get_aca_catalog(**kwargs):
     aca.call_args = kwargs.copy()
     aca.set_attrs_from_kwargs(**kwargs)
 
+    # Remove kwargs that are specific to AcaTable
+    for kwarg in ('t_ccd', 't_ccd_penalty_limit'):
+        if kwarg in kwargs:
+            del kwargs[kwarg]
+
     # Override t_ccd related inputs with effective temperatures for downstream
     # action by AcqTable, GuideTable, FidTable.  See set_attrs_from_kwargs()
     # method for more details.
-    if 't_ccd' in kwargs:
-        del kwargs['t_ccd']
     kwargs['t_ccd_acq'] = aca.t_ccd_eff_acq
     kwargs['t_ccd_guide'] = aca.t_ccd_eff_guide
 
@@ -168,16 +173,22 @@ def _get_aca_catalog(**kwargs):
     return aca
 
 
-def get_effective_t_ccd(t_ccd):
+def get_effective_t_ccd(t_ccd, t_ccd_penalty_limit=None):
     """Return the effective T_ccd used for selection and catalog evaluation.
 
     For details see Dynamic ACA limits in baby steps section in:
     https://occweb.cfa.harvard.edu/twiki/bin/view/Aspect/StarWorkingGroupMeeting2019x02x13
 
-    :param t_ccd:
-    :return:
+    :param t_ccd: float
+        Actual (predicted) CCD temperature
+    :param t_ccd_penalty_limit: float, None
+        ACA penalty limit to use (degC). Default = aca_t_ccd_penalty_limit from
+        proseco.characteristics.
+    :returns: t_ccd_eff
+        Effective CCD temperature (degC) for use in star selection
     """
-    t_limit = ACA.aca_t_ccd_penalty_limit
+    t_limit = (ACA.aca_t_ccd_penalty_limit if t_ccd_penalty_limit is None
+               else t_ccd_penalty_limit)
     if t_ccd > t_limit:
         return t_ccd + 1 + (t_ccd - t_limit)
     else:
@@ -205,6 +216,7 @@ class ACATable(ACACatalogTable):
     # method below).
     t_ccd_eff_acq = MetaAttribute(is_kwarg=False)
     t_ccd_eff_guide = MetaAttribute(is_kwarg=False)
+    t_ccd_penalty_limit = MetaAttribute()
 
     def __copy__(self):
         # Astropy Table now does a light key-only copy of the `meta` dict, so
@@ -252,8 +264,10 @@ def set_attrs_from_kwargs(self, **kwargs):
         """
         super().set_attrs_from_kwargs(**kwargs)
 
-        self.t_ccd_eff_acq = get_effective_t_ccd(self.t_ccd_acq)
-        self.t_ccd_eff_guide = get_effective_t_ccd(self.t_ccd_guide)
+        if self.t_ccd_penalty_limit is None:
+            self.t_ccd_penalty_limit = ACA.aca_t_ccd_penalty_limit
+        self.t_ccd_eff_acq = get_effective_t_ccd(self.t_ccd_acq, self.t_ccd_penalty_limit)
+        self.t_ccd_eff_guide = get_effective_t_ccd(self.t_ccd_guide, self.t_ccd_penalty_limit)
         self.version = VERSION
 
     def get_review_table(self):

proseco/characteristics.py

@@ -28,10 +28,6 @@
 col_spoiler_mag_diff = 4.5
 col_spoiler_pix_sep = 10  # pixels
 
-# ACA T_ccd penalty limit (degC).
-# Above this limit a temperature "penalty" is applied via get_effective_t_ccd()
-aca_t_ccd_penalty_limit = -7.5
-
 # Dark current that corresponds to a 5.0 mag star in a single pixel.  Apply
 # this value to the region specified by bad_pixels.
 bad_pixel_dark_current = 700_000
@@ -49,3 +45,57 @@ def _load_bad_star_set():
 
 
 bad_star_set = LazyDict(_load_bad_star_set)
+
+# Version of chandra_models to use for the ACA xija model from which the
+# planning and penalty limits are extracted. Default of None means use the
+# current flight-approved version. For testing or other rare circumstances this
+# can be overridden prior to calling get_aca_catalog(). This module variable
+# gets set to the actual chandra_models version when the ACA attributes are
+# first accessed.
+chandra_models_version = None
+
+# The next two characteristics are lazily defined to ensure import succeeds.
+
+# aca_t_ccd_penalty_limit : ACA T_ccd penalty limit (degC).
+# Above this limit a temperature "penalty" is applied via get_effective_t_ccd()
+
+# aca_t_ccd_planning_limit : ACA T_ccd planning limit (degC).
+# Predicted ACA CCD temperatures must be below this limit.
+
+
+def __getattr__(name):
+    """Lazily define module attributes for the ACA planning and penalty limits"""
+    if name in ('aca_t_ccd_penalty_limit', 'aca_t_ccd_planning_limit'):
+        _set_aca_limits()
+        return globals()[name]
+    else:
+        raise AttributeError(f"module {__name__} has no attribute {name}")
+
+
+def _set_aca_limits():
+    """Set global variables for ACA thermal planning and penalty limits"""
+    global chandra_models_version
+    from xija.get_model_spec import get_xija_model_spec
+    spec, chandra_models_version = get_xija_model_spec('aca', version=chandra_models_version)
+
+    names = ('aca_t_ccd_penalty_limit', 'aca_t_ccd_planning_limit')
+    spec_names = ('planning.penalty.high', 'planning.warning.high')
+    for name, spec_name in zip(names, spec_names):
+        try:
+            limit = spec['limits']['aacccdpt'][spec_name]
+        except KeyError:
+            raise KeyError(f"unable to find ['limits']['aacccdpt']['{spec_name}'] "
+                           "in the ACA xija model in "
+                           f"chandra_models version {chandra_models_version}.")
+        else:
+            globals()[name] = limit
+
+
+# Make sure module-level `dir()` includes the lazy attributes.
+
+# Grab the module attributes before defining __dir__
+_attrs = dir()
+
+
+def __dir__():
+    return sorted(_attrs + ['aca_t_ccd_penalty_limit', 'aca_t_ccd_planning_limit'])

proseco/tests/test_catalog.py

@@ -33,7 +33,7 @@
 def test_allowed_kwargs():
     """Test #332 where allowed_kwargs class attribute is unique for each subclass"""
     new_kwargs = ACATable.allowed_kwargs - ACACatalogTable.allowed_kwargs
-    assert new_kwargs == {'call_args', 'version'}
+    assert new_kwargs == {'call_args', 'version', 't_ccd_penalty_limit'}
 
     new_kwargs = FidTable.allowed_kwargs - ACACatalogTable.allowed_kwargs
     assert new_kwargs == {'acqs', 'include_ids', 'exclude_ids'}
@@ -404,6 +404,39 @@ def test_t_ccd_effective_acq_guide(t_ccd_case):
 
     kwargs = mod_std_info(stars=stars, t_ccd_acq=t_ccd_acq, t_ccd_guide=t_ccd_guide)
     aca = get_aca_catalog(**kwargs)
+    assert aca.t_ccd_penalty_limit == t_limit
+
+    assert np.isclose(aca.t_ccd_acq, t_ccd_acq)
+    assert np.isclose(aca.t_ccd_guide, t_ccd_guide)
+
+    # t_ccd + 1 + (t_ccd - t_limit) from proseco.catalog.get_effective_t_ccd()
+    assert np.isclose(aca.t_ccd_eff_acq, t_ccd_acq + t_penalty_acq)
+    assert np.isclose(aca.t_ccd_eff_guide, t_ccd_guide + t_penalty_guide)
+
+    assert np.isclose(aca.t_ccd_eff_acq, aca.acqs.t_ccd)
+    assert np.isclose(aca.t_ccd_eff_guide, aca.guides.t_ccd)
+
+
+@pytest.mark.parametrize('t_ccd_case', t_ccd_cases)
+def test_t_ccd_effective_acq_guide_via_kwarg(t_ccd_case):
+    """Test setting of effective T_ccd temperatures for cases above and
+    below a manually specified limit
+    """
+    stars = StarsTable.empty()
+    stars.add_fake_constellation(mag=8.0, n_stars=8)
+
+    t_limit = -np.pi  # some number different from ACA.aca_t_ccd_penalty_limit
+
+    t_offset, t_penalty_acq, t_penalty_guide = t_ccd_case
+    # Set acq and guide temperatures different
+    t_ccd_acq = t_limit + t_offset
+    t_ccd_guide = t_ccd_acq - 0.1
+
+    kwargs = mod_std_info(stars=stars, t_ccd_acq=t_ccd_acq, t_ccd_guide=t_ccd_guide)
+    kwargs['t_ccd_penalty_limit'] = t_limit
+    aca = get_aca_catalog(**kwargs)
+
+    assert aca.t_ccd_penalty_limit == t_limit
 
     assert np.isclose(aca.t_ccd_acq, t_ccd_acq)
     assert np.isclose(aca.t_ccd_guide, t_ccd_guide)