Merge pull request #86 from simonsobs/restructure

Refactor for SoLikeT
simonsobs · Sep 4, 2024 · 37048c1 · 37048c1
2 parents 660e0fa + 37e1022
commit 37048c1
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diff --git a/.github/workflows/testing.yml b/.github/workflows/testing.yml
@@ -26,7 +26,7 @@ jobs:
       if: matrix.os == 'macos-latest'
       run: |
         set -x
-        sudo ln -s /opt/homebrew/bin/gfortran-11 /usr/local/bin/gfortran
+        sudo ln -s /opt/homebrew/bin/gfortran-12 /usr/local/bin/gfortran
         gfortran --version
 
     - name: Install dependencies via pip

diff --git a/docs/source/foreground.rst b/docs/source/foreground.rst
@@ -0,0 +1,21 @@
+``foreground`` – Application of foregrounds with bandpass
+=========================================================
+
+.. automodule:: mflike.foreground
+
+``Foreground`` class content
+-----------------------------
+
+.. autoclass:: mflike.Foreground
+   :exclude-members: initialize
+   :members:
+   :show-inheritance:
+   :private-members:
+   :member-order: bysource
+
+.. autoclass:: mflike.BandpowerForeground
+   :exclude-members: initialize
+   :members:
+   :show-inheritance:
+   :private-members:
+   :member-order: bysource
diff --git a/docs/source/index.rst b/docs/source/index.rst
@@ -17,4 +17,4 @@
    :caption: API
 
    mflike.rst
-   theoryforge.rst
+   foreground.rst
diff --git a/docs/source/notebooks/tutorial_fisher.ipynb b/docs/source/notebooks/tutorial_fisher.ipynb
diff --git a/docs/source/notebooks/tutorial_foregrounds.ipynb b/docs/source/notebooks/tutorial_foregrounds.ipynb
diff --git a/docs/source/notebooks/tutorial_loading.ipynb b/docs/source/notebooks/tutorial_loading.ipynb
@@ -110,7 +110,7 @@
     "mflike_input_file = dict(\n",
     "    input_file=\"LAT_simu_sacc_00044.fits\", cov_Bbl_file=\"data_sacc_w_covar_and_Bbl.fits\"\n",
     ")\n",
-    "mflike_config = {\"mflike.MFLike\": mflike_input_file}"
+    "mflike_config = {\"mflike.TTTEEE\": mflike_input_file}"
    ]
   },
   {
@@ -306,7 +306,8 @@
     "tags": []
    },
    "source": [
-    "We finally put everything into a dictionary to push it into `cobaya` configuration system. Here for the purpose of this tutorial, we use `camb` as Boltzmann solver with minimal settings. Another configuration `high_accuracy_settings` is also provided and you can switch within the `info` object"
+    "We finally put everything into a dictionary to push it into `cobaya` configuration system. Here for the purpose of this tutorial, we use `camb` as Boltzmann solver with minimal settings. Another configuration `high_accuracy_settings` is also provided and you can switch within the `info` object.  \n",
+    "The likelihood also depends on the foreground model, the default model for which can also be obtained from mflike.BandpowerForeground."
    ]
   },
   {
@@ -339,7 +340,8 @@
     "info = {\n",
     "    \"params\": cosmo_params | fg_params | nuisance_params,\n",
     "    \"likelihood\": mflike_config,\n",
-    "    \"theory\": {\"camb\": {\"extra_args\": minimal_settings}},\n",
+    "    \"theory\": {\"camb\": {\"extra_args\": minimal_settings},\n",
+    "               \"mflike.BandpowerForeground\": None},\n",
     "    \"packages_path\": packages_path,\n",
     "}"
    ]
@@ -416,7 +418,7 @@
    },
    "outputs": [],
    "source": [
-    "mflike = model.likelihood[\"mflike.MFLike\"]"
+    "mflike = model.likelihood[\"mflike.TTTEEE\"]"
    ]
   },
   {
@@ -450,7 +452,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.7"
+   "version": "3.11.5"
   },
   "widgets": {
    "application/vnd.jupyter.widget-state+json": {

diff --git a/docs/source/notebooks/tutorial_logp_value.ipynb b/docs/source/notebooks/tutorial_logp_value.ipynb
diff --git a/docs/source/notebooks/tutorial_residuals.ipynb b/docs/source/notebooks/tutorial_residuals.ipynb
@@ -153,7 +153,7 @@
     "tags": []
    },
    "source": [
-    "To take into account the systematics, we call the `mflike.ThFo.get_modified_theory` function. In this function, we need to use the same $\\ell$ range set by the data through the variable `l_bpws`, that is why we generated the theory spectra using the `mflike.l_bpws` ell range. (Notice that `dls` has a multipole range of `2, mflike.l_bpws[-1]`)."
+    "To take into account the systematics, we call the `mflike.get_modified_theory` function. In this function, we need to use the same $\\ell$ range set by the data through the variable `l_bpws`, that is why we generated the theory spectra using the `mflike.l_bpws` ell range. (Notice that `dls` has a multipole range of `2, mflike.l_bpws[-1]`)."
    ]
   },
   {
@@ -171,7 +171,9 @@
    "source": [
     "ell = mflike.l_bpws\n",
     "dls_cmb = {mode: dls[mode][ell] for mode in [\"tt\", \"te\", \"ee\", \"bb\"]}\n",
-    "dl_obs = mflike.ThFo.get_modified_theory(dls_cmb, **fg_params, **nuisance_params)"
+    "foreground_model = model.theory[\"mflike.BandpowerForeground\"]\n",
+    "fg_totals = foreground_model.get_fg_totals()\n",
+    "dl_obs = mflike.get_modified_theory(dls_cmb, fg_totals, **nuisance_params)"
    ]
   },
   {
@@ -201,7 +203,7 @@
    "source": [
     "## Simulated data *vs.* data model\n",
     "\n",
-    "We start by plotting unbinned theory + foreground model with the total power spectrum modified by the systematics for a bunch of simulated files. Let's first start by retrieving the foreground model"
+    "We start by plotting unbinned theory + foreground model with the total power spectrum modified by the systematics for a bunch of simulated files. Let's first start by retrieving the foreground model as a dictionary"
    ]
   },
   {
@@ -217,7 +219,7 @@
    },
    "outputs": [],
    "source": [
-    "fg_models = mflike.ThFo._get_foreground_model(ell=ell, **fg_params)"
+    "fg_models = foreground_model.get_foreground_model(ell=ell, **fg_params)"
    ]
   },
   {
@@ -231,7 +233,7 @@
     "tags": []
    },
    "source": [
-    "To load `MFLike` for different simulated data file, we will use the external way as described in the last part of this [tutorial](tutorial_logp_value.ipynb). Altough the `spec_meta` attribute holds the different spectra, there is no easy way to extract a specific cross and/or mode. Here we will built a dictionnary indexed on spectrum mode and cross experiments to be latter used by the plotting function (the `contextmanager` is just to catch and flush the `logging` messages when initializing `MFLike` likelihood)"
+    "To load `MFLike` for different simulated data file, we will use the external way as described in the last part of this [tutorial](tutorial_logp_value.ipynb). Altough the `spec_meta` attribute holds the different spectra, there is no easy way to extract a specific cross and/or mode. Here we will built a dictionary indexed on spectrum mode and cross experiments to be latter used by the plotting function (the `contextmanager` is just to catch and flush the `logging` messages when initializing `MFLike` likelihood)"
    ]
   },
   {
@@ -265,7 +267,7 @@
     "import logging\n",
     "from contextlib import contextmanager\n",
     "\n",
-    "from mflike import MFLike\n",
+    "from mflike import TTTEEE\n",
     "from tqdm.auto import tqdm\n",
     "\n",
     "\n",
@@ -284,7 +286,7 @@
     "for isim in tqdm(range(nsims)):\n",
     "    input_file = dict(input_file=f\"LAT_simu_sacc_{isim:05d}.fits\")\n",
     "    with disable_logging():\n",
-    "        ext_mflike = MFLike(mflike_input_file | input_file, packages_path=packages_path)\n",
+    "        ext_mflike = TTTEEE(mflike_input_file | input_file, packages_path=packages_path)\n",
     "        for data in ext_mflike.spec_meta:\n",
     "            lb, db = data.get(\"leff\"), data.get(\"cl_data\")\n",
     "            cross = (data.get(\"t1\"), data.get(\"t2\"))\n",
@@ -493,7 +495,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.8"
+   "version": "3.11.5"
   },
   "widgets": {
    "application/vnd.jupyter.widget-state+json": {

diff --git a/docs/source/theoryforge.rst b/docs/source/theoryforge.rst
diff --git a/examples/mflike_example.yaml b/examples/mflike_example.yaml
@@ -7,6 +7,21 @@ likelihood:
     input_file: LAT_simu_sacc_00044.fits
     cov_Bbl_file: data_sacc_w_covar_and_Bbl.fits
 
+theory:
+  camb:
+    stop_at_error: False
+    extra_args:
+      kmax: 10
+      k_per_logint: 130
+      nonlinear: True
+      lens_potential_accuracy: 8
+      lens_margin: 2050
+      AccuracyBoost: 2.0
+      lSampleBoost: 2.0
+      lAccuracyBoost: 2.0
+      DoLateRadTruncation: False
+  mflike.BandpowerForeground:
+
 params:
   # Sampled
   cosmomc_theta:
@@ -66,20 +81,6 @@ params:
     value: 9.60
     latex: T_d
 
-theory:
-  camb:
-    stop_at_error: False
-    extra_args:
-      kmax: 10
-      k_per_logint: 130
-      nonlinear: True
-      lens_potential_accuracy: 8
-      lens_margin: 2050
-      AccuracyBoost: 2.0
-      lSampleBoost: 2.0
-      lAccuracyBoost: 2.0
-      DoLateRadTruncation: False
-
 
 sampler:
   mcmc:

diff --git a/mflike/EE.yaml b/mflike/EE.yaml
@@ -0,0 +1,11 @@
+# Specify default set of spectra and scale cuts
+# to be used
+requested_cls: [ "ee" ]
+defaults:
+  # Which spectra?
+  polarizations: [ EE ]
+  # Scale cuts (in ell) for each spectrum
+  scales:
+    EE: [ 30, 9000 ]
+
+params: !defaults [ mflike_common, calib_E ]
diff --git a/mflike/Foreground.yaml b/mflike/Foreground.yaml
@@ -0,0 +1,63 @@
+requested_cls: [ "tt", "te", "ee" ]
+lmin: 2
+lmax: 6001
+# ells set automatically from above if not set directly
+ells:
+experiments: [ "LAT_93", "LAT_145", "LAT_225" ]
+bandint_freqs: [ 93.0, 145.0, 225.0 ]
+# Parameters to build a top-hat band:
+# - nsteps sets the number of frequencies used in the band integration
+# - bandwidth sets the relative width of the band wrt the central frequency
+#   the central frequency of each band is set from the bands stored in the sacc file
+#     - with nstep: 1, bandwidth must be 0
+#     Dirac delta bandpass, no band integration
+#     useful if you don't want to do band integration
+#     when the bandpasses in the sacc file are multifrequency
+#     the freq used is the effective frequency from the bandpass
+#     - if nstep > 1,  bandwidth must be > 1
+#     bandwidth can be a list if you want a different width for each band
+#     e.g. bandwidth: [0.3,0.2,0.3] for 3 bands
+# when top_hat_band is a null dict: no top-hat band is built and
+# bandpasses read from sacc file. Band integration is performed accordingly
+# (if bandpass in sacc is a single freq, no band integration)
+# the default is to read bandpasses from file, to build top-hat uncomment the
+# parameters of the block!
+# Bandpass has to be divided by nu^2 if measured with respect to a RJ source
+# the nu^2 factor is set back again in the _bandpass_construction function
+top_hat_band:
+#  nsteps: 1
+#  bandwidth: 0
+
+normalisation:
+  nu_0: 150.0
+  ell_0: 3000
+  T_CMB: 2.725
+
+components:
+  tt:
+    - kSZ
+    - tSZ_and_CIB
+    - cibp
+    - dust
+    - radio
+  te:
+    - radio
+    - dust
+  ee:
+    - radio
+    - dust
+
+# parameters that are always used
+params:
+  beta_s: #beta radio
+    value: -2.5
+    latex: \beta_s
+  alpha_s: #alpha radio
+    value: 1.0
+    latex: \alpha_s
+  T_effd: #effective galactic dust temperature
+    value: 19.6
+    latex: T_{\mathrm{dust},\mathrm{eff}}
+  beta_d: #beta galactic dust
+    value: 1.5
+    latex: \beta_\mathrm{dust}