Incorporating CMB Lensing Sources and Statistics into Firecrown for 5…

…x2pt (#123)

* read CMBK

* adding and testing CCL NK and GK

* adding NK & GK

* Update sources.py

* add documentation

* fix lint errors

* few fixes

* Update sources.py

* Update sources.py

* Update sources.py

* Update sources.py

* Add CMBL test

* Update test_cmbl_source.py

* Update test_cmbl_source.py

examples/NK&GK/GK.yaml

@@ -0,0 +1,98 @@
+parameters:
+  Omega_k: 0.0
+  Omega_g: 0.0
+  w0: -1.0
+  wa: 0.0
+  T_CMB: 2.7
+  Neff: 0
+  m_nu: 0.0
+  transfer_function: 'bbks'
+  mass_function: 'tinker'
+
+  Omega_b: 0.045
+  Omega_c: 0.21
+  h: 0.71
+  sigma8: 0.80
+  n_s: 0.964
+
+  bias_lens: 1.0
+
+
+cosmosis: 
+  sampler: emcee
+  debug: False
+  quiet: True
+  mpi: True
+  test: 
+    fatal_erros: True
+  emcee: 
+    walkers: 32
+    samples: 20
+  parameters: 
+    Omega_c: [0.1, 0.21, 0.9]
+    sigma8: [0.4, 0.8, 1.2]
+    n_s: [0.87, 0.964, 1.07]
+    h: [0.55, 0.71, 0.91]
+    Omega_b: [0.03, 0.045, 0.07]
+
+
+priors: 
+  module: firecrown.priors
+
+  Omega_c: 
+    kind: uniform
+    loc: 0.1
+    scale: 0.8
+
+  n_s: 
+    kind: uniform 
+    loc: 0.87
+    scale: 0.2
+
+  sigma8:
+    kind: uniform 
+    loc: 0.40
+    scale: 0.80
+
+  h: 
+    kind: uniform 
+    loc: 0.55
+    scale: 0.36
+
+  Omega_b: 
+    kind: uniform 
+    loc: 0.03
+    scale: 0.04
+
+
+two_point: 
+  module: firecrown.ccl.two_point
+  sacc_data: GK.sacc
+
+  sources: 
+    {% for i in range(5) %}
+    src{{i}}: 
+      kind: CMBLSource
+      sacc_tracer: ck{{i}}
+    {% endfor %}
+
+    {% for i in range(5) %}
+    lens{{i}}: 
+      kind: WLSource
+      sacc_tracer: wl{{i}}
+    {% endfor %}
+
+  statistics: 
+    {% for i in range(5) %}
+    GK{{i}}: 
+      sources: ['lens{{i}}','src{{i}}']
+      sacc_data_type: 'cmbGalaxy_convergenceShear_xi_t'
+    {% endfor %}
+
+  likelihood: 
+    kind: ConstGaussianLogLike 
+    data_vector: 
+    {% for i in range(5) %}
+      - GK{{i}}
+    {% endfor %}
+

examples/NK&GK/NK.yaml

@@ -0,0 +1,106 @@
+parameters:
+  Omega_k: 0.0
+  Omega_g: 0.0
+  w0: -1.0
+  wa: 0.0
+  T_CMB: 2.7
+  Neff: 0
+  m_nu: 0.0
+  transfer_function: 'bbks'
+  mass_function: 'tinker'
+
+  sigma8: 0.80
+
+  Omega_b: 0.045
+  h: 0.71
+  Omega_c: 0.21
+  n_s: 0.964
+
+  {% for i in range(5) %}
+  bias_lens{{i}}: 1.0
+  {% endfor %}
+
+
+cosmosis: 
+  sampler: emcee
+  debug: True
+  quiet: False
+  mpi: False
+  test: 
+    fatal_erros: True
+  emcee: 
+    walkers: 32
+    samples: 60
+  parameters: 
+    Omega_c: [0.1, 0.21, 0.9]
+    n_s: [0.87, 0.964, 1.07]
+    h: [0.55, 0.71, 0.91]
+    Omega_b: [0.03, 0.045, 0.07]
+    {% for i in range(5) %}
+    bias_lens{{i}}: [0.2, 1.0, 4.0]
+    {% endfor %}
+
+
+priors: 
+  module: firecrown.priors
+
+  Omega_c: 
+    kind: uniform
+    loc: 0.1
+    scale: 0.8
+
+  n_s: 
+    kind: uniform 
+    loc: 0.87
+    scale: 0.2
+
+  h: 
+    kind: uniform 
+    loc: 0.55
+    scale: 0.36
+
+  Omega_b: 
+    kind: uniform 
+    loc: 0.03
+    scale: 0.04
+
+  {% for i in range(5) %}
+  bias_lens{{i}}: 
+    kind: uniform 
+    loc: 0.2
+    scale: 3.8
+  {% endfor %}
+
+
+two_point: 
+  module: firecrown.ccl.two_point
+  sacc_data: NK.sacc
+
+  sources: 
+    {% for i in range(5) %}
+    src{{i}}: 
+      kind: CMBLSource
+      sacc_tracer: ck{{i}}
+    {% endfor %}
+
+    {% for i in range(5) %}
+    lens{{i}}: 
+      kind: NumberCountsSource
+      sacc_tracer: gc{{i}}
+      bias: bias_lens{{i}}
+    {% endfor %}
+
+  statistics: 
+    {% for i in range(5) %}
+    NK{{i}}: 
+      sources: ['lens{{i}}','src{{i}}']
+      sacc_data_type: 'cmbGalaxy_convergenceDensity_xi'
+    {% endfor %}
+
+  likelihood: 
+    kind: ConstGaussianLogLike 
+    data_vector: 
+    {% for i in range(5) %}
+      - NK{{i}}
+    {% endfor %}
+

examples/NK&GK/README.md

@@ -0,0 +1,17 @@
+# NK and GK constraints
+
+This is part of 5x2pt analysis. `NK.yaml` constrains cosmology based on galaxy number count x CMB lensing correlation (data stored in `NK.sacc`). `GK.yanml` constrains cosmology based on galaxy weak lensing x CMB lensing correlation (data stored in `GK.sacc`). 
+
+Both constraints use `emcee` as the sampler for MCMC chains. 
+
+To run this example, type
+
+```bash
+$ firecrown run-cosmosis NK.yaml
+```
+
+or for GK, type
+
+```bash
+$ firecrown run-cosmosis GK.yaml
+```

examples/des_y1_3x2pt/plot_des_chain.ipynb

@@ -486,9 +486,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.3"
+   "version": "3.7.4"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }

examples/des_y1_3x2pt/plot_des_data_model.ipynb

@@ -5157,9 +5157,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.7.4"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }

firecrown/ccl/sources/sources.py

@@ -7,7 +7,7 @@
 from ..systematics import IdentityFunctionMOR, TopHatSelectionFunction
 
 
-__all__ = ['WLSource', 'NumberCountsSource', 'ClusterSource']
+__all__ = ['WLSource', 'NumberCountsSource', 'ClusterSource', 'CMBLSource']
 
 
 class WLSource(Source):
@@ -374,3 +374,72 @@ def render(self, cosmo, params, systematics=None):
             systematics[systematic].apply(cosmo, params, self)
 
         self.dndz_interp_ = Akima1DInterpolator(self.z_, self.dndz_)
+
+
+class CMBLSource(Source):
+    """A CCL CMB Lensing Source.
+
+    Parameters
+    ----------
+    sacc_tracer : str
+        The name of the tracer in the SACC file.
+    scale : float, optional
+        The default scale for this source. Usually the default of 1.0 is
+        correct.
+    systematics : list of str, optional
+        A list of the source-level systematics to apply to the source. The
+        default of `None` implies no systematics.
+
+    Attributes
+    ----------
+    scale_ : float
+        The overall scale associated with the source. Set after a call to
+        `render`.
+    tracer_ : `pyccl.CMBLensingTracer`
+        The CCL tracer associated with this source. Set after a call to
+        `render`.
+
+    Methods
+    -------
+    render : apply systematics to this source and build the
+        `pyccl.CMBLSource`
+    """
+    def __init__(self, *, sacc_tracer, scale=1.0, systematics=None):
+        self.sacc_tracer = sacc_tracer
+        self.scale = scale
+        self.systematics = systematics or []
+
+    def read(self, sacc_data):
+        """
+        Read the data for this source from the SACC file.
+
+        Parameters
+        ----------
+        sacc_data : sacc.Sacc
+            The data in the sacc format.
+        """
+        pass
+
+    def render(self, cosmo, params, systematics=None):
+        """
+        Render a source by applying systematics.
+
+        Parameters
+        ----------
+        cosmo : pyccl.Cosmology
+            A pyccl.Cosmology object.
+        params : dict
+            A dictionary mapping parameter names to their current values.
+        systematics : dict
+            A dictionary mapping systematic names to their objects. The
+            default of `None` corresponds to no systematics.
+        """
+        systematics = systematics or {}
+
+        self.scale_ = self.scale
+
+        for systematic in self.systematics:
+            systematics[systematic].apply(cosmo, params, self)
+
+        tracer = ccl.CMBLensingTracer(cosmo, 1100.)
+        self.tracer_ = tracer

firecrown/ccl/sources/tests/test_cmbl_source.py

@@ -0,0 +1,55 @@
+import numpy as np
+import pytest
+
+import sacc
+import pyccl as ccl
+
+from ..sources import CMBLSource
+
+
+@pytest.fixture
+def cmbl_data():
+    sacc_data = sacc.Sacc()
+
+    params = dict(
+        Omega_c=0.27,
+        Omega_b=0.045,
+        Omega_k=0.0,
+        w0=-1.0,
+        wa=0.0,
+        sigma8=0.8,
+        n_s=0.96,
+        h=0.67)
+    cosmo = ccl.Cosmology(**params)
+
+    ell = np.arange(3000)
+
+    sacc_data.add_tracer('Map', 'trc1', quantity='cmb_convergence', spin=0,
+                         ell=ell, beam=None)
+
+    return {
+        'cosmo': cosmo,
+        'sacc_tracer': 'trc1',
+        'sacc_data': sacc_data,
+        'params': params,
+        'systematics': [],
+        'systematics_dict': {},
+        'scale_': 1.05}
+
+
+def test_cmbl_source_nosys(cmbl_data):
+    src = CMBLSource(
+        sacc_tracer=cmbl_data['sacc_tracer'],
+        scale=0.5)
+    src.read(cmbl_data['sacc_data'])
+
+    src.render(
+        cmbl_data['cosmo'],
+        cmbl_data['params'],
+        cmbl_data['systematics_dict'])
+
+    assert np.allclose(src.scale, 0.5)
+    assert np.allclose(src.scale_, 0.5)
+    assert src.systematics == []
+
+    assert isinstance(src.tracer_, ccl.CMBLensingTracer)