better instrument generation

maria/atmosphere/__init__.py

@@ -116,7 +116,7 @@ def _simulate_atmospheric_emission(self, units="K_RJ"):
             )
 
             for band in bands:
-                band_index = self.instrument.dets(band=band.name).uid
+                band_index = self.instrument.dets(band=band.name).index
 
                 if self.verbose:
                     bands.set_description(f"Computing atm. emission ({band.name})")
@@ -167,7 +167,7 @@ def _simulate_atmospheric_emission(self, units="K_RJ"):
             )
 
             for band in bands:
-                band_index = self.instrument.dets(band=band.name).uid
+                band_index = self.instrument.dets(band=band.name).index
 
                 if self.verbose:
                     bands.set_description(f"Computing atm. transmission ({band.name})")

maria/atmosphere/turbulent_layer.py

@@ -4,7 +4,7 @@
 from .. import utils
 from ..coords import Coordinates, get_center_phi_theta
 from ..instrument import Instrument
-from ..instrument.beam import construct_beam_filter, separably_filter
+from ..instrument.beams import construct_beam_filter, separably_filter
 from .weather import Weather
 
 MIN_SAMPLES_PER_RIBBON = 2
@@ -309,7 +309,7 @@ def sample(self):
         for band in self.instrument.bands:
             # we assume the atmosphere looks the same for every nu in the band
 
-            band_index = self.instrument.dets(band=band.name).uid
+            band_index = self.instrument.dets(band=band.name).index
             band_angular_fwhm = self.instrument.angular_fwhm(z=self.depth)[
                 band_index
             ].mean()

maria/instrument/__init__.py

@@ -1,5 +1,4 @@
 import os
-from collections.abc import Mapping
 from dataclasses import dataclass, fields
 from operator import attrgetter
 
@@ -11,9 +10,9 @@
 from matplotlib.patches import Patch
 
 from .. import utils
-from .band import Band, BandList, generate_bands  # noqa F401
-from .beam import compute_angular_fwhm, construct_beam_filter  # noqa F401
-from .dets import Detectors, generate_detectors  # noqa F401
+from .bands import BandList  # noqa F401
+from .beams import compute_angular_fwhm, construct_beam_filter  # noqa F401
+from .dets import Detectors  # noqa F401
 
 HEX_CODE_LIST = [
     mpl.colors.to_hex(mpl.colormaps.get_cmap("Paired")(t))
@@ -30,25 +29,11 @@
 INSTRUMENT_CONFIGS = utils.io.read_yaml(f"{here}/instruments.yml")
 
 INSTRUMENT_DISPLAY_COLUMNS = [
-    "instrument_description",
-    "field_of_view",
-    "primary_size",
-    "bands",
+    "description",
+    # "field_of_view",
+    # "primary_size",
+    # "bands",
 ]
-instrument_data = pd.DataFrame(INSTRUMENT_CONFIGS).reindex(INSTRUMENT_DISPLAY_COLUMNS).T
-
-for instrument_name, config in INSTRUMENT_CONFIGS.items():
-    instrument_data.at[instrument_name, "bands"] = list(config["bands"].keys())
-
-all_instruments = list(instrument_data.index)
-
-
-class InvalidInstrumentError(Exception):
-    def __init__(self, invalid_instrument):
-        super().__init__(
-            f"The instrument '{invalid_instrument}' is not supported."
-            f"Supported instruments are:\n\n{instrument_data.__repr__()}"
-        )
 
 
 def get_instrument_config(instrument_name=None, **kwargs):
@@ -62,6 +47,9 @@ def get_instrument(instrument_name="default", **kwargs):
     """
     Get an instrument from a pre-defined config.
     """
+    for key, config in INSTRUMENT_CONFIGS.items():
+        if instrument_name in config.get("aliases", []):
+            instrument_name = key
     if instrument_name not in INSTRUMENT_CONFIGS.keys():
         raise InvalidInstrumentError(instrument_name)
     instrument_config = INSTRUMENT_CONFIGS[instrument_name].copy()
@@ -89,16 +77,11 @@ class Instrument:
 
     @classmethod
     def from_config(cls, config):
-        if isinstance(config.get("bands"), Mapping):
-            dets = Detectors.generate(
-                bands_config=config.pop("bands"),
-                field_of_view=config.get("field_of_view", 1),
-                geometry=config.get("geometry", "hex"),
-                baseline=config.get("baseline", 0),
-            )
+        dets = Detectors.from_config(config=config)
 
-        else:
-            raise ValueError("'bands' must be a dictionary of bands.")
+        for key in ["dets", "aliases"]:
+            if key in config:
+                config.pop(key)
 
         return cls(bands=dets.bands, dets=dets, **config)
 
@@ -142,7 +125,7 @@ def baseline_y(self):
 
     @property
     def baselines(self):
-        return np.c_[self.baseline_x, self.baseline_y]
+        return np.c_[self.baseline_x, self.baseline_y, self.baseline_z]
 
     @staticmethod
     def beam_profile(r, fwhm):
@@ -204,11 +187,11 @@ def plot_dets(self, units="deg"):
 
             band_color = HEX_CODE_LIST[iub]
 
-            # nom_freq = self.dets.band_center[band_mask].mean()
+            # band_center = self.dets.band_center[band_mask].mean()
             # band_res_arcmins = 2 * self.fwhm
 
             # 60 * np.degrees(
-            #     1.22 * 2.998e8 / (1e9 * nom_freq * self.primary_size)
+            #     1.22 * 2.998e8 / (1e9 * band_center * self.primary_size)
             # )
 
             # offsets_arcmins = 60 * np.degrees(self.offsets[band_mask])
@@ -240,3 +223,22 @@ def plot_dets(self, units="deg"):
         ax.set_xlabel(rf"$\theta_x$ offset ({units})")
         ax.set_ylabel(rf"$\theta_y$ offset ({units})")
         ax.legend(handles=legend_handles)
+
+
+instrument_data = pd.DataFrame(INSTRUMENT_CONFIGS).reindex(INSTRUMENT_DISPLAY_COLUMNS).T
+
+for instrument_name, config in INSTRUMENT_CONFIGS.items():
+    instrument = get_instrument(instrument_name)
+    f_list = sorted(np.unique([band.center for band in instrument.dets.bands]))
+    instrument_data.at[instrument_name, "f [GHz]"] = "/".join([str(f) for f in f_list])
+    instrument_data.at[instrument_name, "n"] = instrument.dets.n
+
+all_instruments = list(instrument_data.index)
+
+
+class InvalidInstrumentError(Exception):
+    def __init__(self, invalid_instrument):
+        super().__init__(
+            f"The instrument '{invalid_instrument}' is not supported. "
+            f"Supported instruments are:\n\n{instrument_data.__repr__()}"
+        )

maria/instrument/band.py → maria/instrument/bands.py

@@ -1,54 +1,46 @@
+import glob
 import os
 from dataclasses import dataclass
 from typing import Sequence
 
 import numpy as np
 import pandas as pd
 
+from .. import utils
+from ..utils.io import flatten_config, read_yaml
+
 BAND_FIELD_TYPES = {
     "center": "float",
     "width": "float",
-    "type": "str",
+    "passband_shape": "str",
 }
 
 here, this_filename = os.path.split(__file__)
 
+all_bands = {}
+for path in glob.glob(f"{here}/bands/*.yml"):
+    tag = os.path.split(path)[1].split(".")[0]
+    all_bands[tag] = read_yaml(path)
 
-def generate_bands(bands_config):
-    bands = []
-
-    for band_key, band_config in bands_config.items():
-        band_name = band_config.get("band_name", band_key)
-        band_file = band_config.get("file")
+all_bands = flatten_config(all_bands)
 
-        if band_file is not None:
-            if os.path.exists(band_file):
-                band_df = pd.read_csv(band_file)
-            elif os.path.exists(f"{here}/{band_file}"):
-                band_df = pd.read_csv(f"{here}/{band_file}")
-            else:
-                raise FileNotFoundError(band_file)
 
-            band = Band.from_passband(
-                name=band_name, nu=band_df.nu_GHz.values, pb=band_df.pb.values
-            )
-
-        else:
-            band = Band(
-                name=band_name,
-                center=band_config["band_center"],
-                width=band_config["band_width"],
-                white_noise=band_config.get("white_noise", 0),
-                pink_noise=band_config.get("pink_noise", 0),
-                tau=band_config.get("tau", 0),
-            )
+class BandList(Sequence):
+    @classmethod
+    def from_config(cls, config):
+        bands = []
 
-        bands.append(band)
+        if isinstance(config, str):
+            config = utils.io.read_yaml(f"{here}/{config}")
 
-    return BandList(bands)
+        for name in config.keys():
+            band_config = config[name]
+            if "file" in band_config.keys():
+                band_config = utils.io.read_yaml(f'{here}/{band_config["file"]}')
 
+            bands.append(Band(name=name, **band_config))
+        return cls(bands=bands)
 
-class BandList(Sequence):
     def __init__(self, bands: list = []):
         self.bands = bands
 
@@ -73,8 +65,10 @@ def __len__(self):
         return len(self.bands)
 
     def __repr__(self):
-        # return f"BandList([{', '.join(self.names)}])"
-        return self.bands.__repr__()
+        return self.summary.__repr__()
+
+    def __repr_html__(self):
+        return self.summary.__repr_html__()
 
     def __short_repr__(self):
         return f"BandList([{', '.join(self.names)}])"
@@ -100,10 +94,11 @@ class Band:
     name: str
     center: float
     width: float
-    type: str = "flat"
-    tau: float = 0
-    white_noise: float = 0
-    pink_noise: float = 0
+    tau: float = 0.0
+    white_noise: float = 0.0
+    pink_noise: float = 0.0
+    passband_shape: str = "gaussian"
+    efficiency: float = 1.0
 
     @classmethod
     def from_passband(cls, name, nu, pb, pb_err=None):
@@ -112,7 +107,7 @@ def from_passband(cls, name, nu, pb, pb_err=None):
             nu[pb > pb.max() / np.e**2].ptp(), 3
         )  # width is the two-sigma interval
 
-        band = cls(name=name, center=center, width=width, type="custom")
+        band = cls(name=name, center=center, width=width, passband_shape="custom")
 
         band._nu = nu
         band._pb = pb
@@ -121,20 +116,20 @@ def from_passband(cls, name, nu, pb, pb_err=None):
 
     @property
     def nu_min(self) -> float:
-        if self.type == "flat":
+        if self.passband_shape == "flat":
             return self.center - 0.5 * self.width
-        if self.type == "gaussian":
+        if self.passband_shape == "gaussian":
             return self.center - self.width
-        if self.type == "custom":
+        if self.passband_shape == "custom":
             return self._nu[self._pb > 1e-2 * self._pb.max()].min()
 
     @property
     def nu_max(self) -> float:
-        if self.type == "flat":
+        if self.passband_shape == "flat":
             return self.center + 0.5 * self.width
-        if self.type == "gaussian":
+        if self.passband_shape == "gaussian":
             return self.center + self.width
-        if self.type == "custom":
+        if self.passband_shape == "custom":
             return self._nu[self._pb > 1e-2 * self._pb.max()].max()
 
     def passband(self, nu):
@@ -144,13 +139,13 @@ def passband(self, nu):
 
         _nu = np.atleast_1d(nu)
 
-        if self.type == "gaussian":
+        if self.passband_shape == "gaussian":
             band_sigma = self.width / 4
 
             return np.exp(-0.5 * np.square((_nu - self.center) / band_sigma))
 
-        if self.type == "flat":
+        if self.passband_shape == "flat":
             return np.where((_nu > self.nu_min) & (_nu < self.nu_max), 1.0, 0.0)
 
-        elif self.type == "custom":
+        elif self.passband_shape == "custom":
             return np.interp(_nu, self._nu, self._pb)

maria/instrument/bands/act.yml

@@ -0,0 +1,65 @@
+pa4:
+  f150:
+    center: 150
+    width: 30
+    passband_shape: gaussian
+    tau: 0
+    white_noise: 266.e-6
+    pink_noise: 1.e-1
+    efficiency: 0.5
+  f220:
+    center: 220
+    width: 30
+    passband_shape: gaussian
+    tau: 0
+    white_noise: 266.e-6
+    pink_noise: 1.e-1
+    efficiency: 0.5
+pa5:
+  f090:
+    center: 90
+    width: 30
+    passband_shape: gaussian
+    tau: 0
+    white_noise: 266.e-6
+    pink_noise: 1.e-1
+    efficiency: 0.5
+  f150:
+    center: 150
+    width: 30
+    passband_shape: gaussian
+    tau: 0
+    white_noise: 266.e-6
+    pink_noise: 1.e-1
+    efficiency: 0.5
+pa6:
+  f090:
+    center: 90
+    width: 30
+    passband_shape: gaussian
+    tau: 0
+    white_noise: 266.e-6
+    pink_noise: 1.e-1
+    efficiency: 0.5
+  f150:
+    center: 150
+    width: 30
+    passband_shape: gaussian
+    tau: 0
+    white_noise: 266.e-6
+    pink_noise: 1.e-1
+    efficiency: 0.5
+
+  f093:
+    n_dets: 217
+    field_of_view: 0.07
+    detector_geometry: hex
+
+    bands: [mustang2/f093]
+
+    # file: data/mustang2/passbands/f093.csv
+    center: 90
+    width: 30
+    efficiency: 0.5
+    white_noise: 266.e-6 # in K_RJ s^-1/2
+    pink_noise: 1.e-1 # in K_RJ s^-1/2