Merge pull request #169 from deepskies/114-document-run-sims-thoroughly

Cleaned up top-level directory, document run_sims

.github/workflows/paper.yml

@@ -0,0 +1,23 @@
+on: [push]
+
+jobs:
+  paper:
+    runs-on: ubuntu-latest
+    name: Paper Draft
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v3
+      - name: Build draft PDF
+        uses: openjournals/openjournals-draft-action@master
+        with:
+          journal: joss
+          # This should be the path to the paper within your repo.
+          paper-path: paper/paper.md
+      - name: Upload
+        uses: actions/upload-artifact@v1
+        with:
+          name: paper
+          # This is the output path where Pandoc will write the compiled
+          # PDF. Note, this should be the same directory as the input
+          # paper.md
+          path: paper/paper.pdf

.github/workflows/run_tests.yml

@@ -22,6 +22,7 @@ jobs:
       run: |
         conda env update --file environment.yml --name base
         python -m pip install colossus pixell camb
+        python -m pip install .
     - name: Test with pytest
       run: |
         conda install pytest

notebooks/outfiles/params_230920173614790725_150_233437.yaml

@@ -0,0 +1,23 @@
+COSMOLOGY:
+  Battaglia2012:
+    flat: True 
+    H0: 70
+    Omega_m0: 0.25
+    Omega_b0: 0.043
+    sigma8: 0.8
+    ns: 0.96
+    cosmo_h: 0.7
+    t_cmb: 2.725 #K
+
+SURVEYS:
+  ACTDR5:
+    150: #Observation frequency [GHz]
+      beam_size: 1.3 #From published survey properties
+      noise_level: 30 #From published survey properties
+
+IMAGES:
+  image_size: 41
+  pix_size: 0.5
+
+
+

paper/paper.md

@@ -0,0 +1,59 @@
+---
+title: 'DeepSZSim: A Python code for fast, tunable Sunyaev–Zeldovich effect submap simulations'
+tags:
+  - Python
+  - cosmology
+  - cosmic microwave background
+  - galaxy clusters
+  - astronomy
+authors:
+  - name: Author 1
+    orcid: 0000-0000-0000-0000
+    equal-contrib: true
+    affiliation: "1, 2" # (Multiple affiliations must be quoted)
+
+affiliations:
+ - name: Affil 1
+   index: 1
+ - name: Affil 2
+   index: 2
+ - name: Affil 3
+   index: 3
+date: 13 August 2023
+bibliography: paper.bib
+
+
+---
+
+based on: https://joss.theoj.org/papers/10.21105/joss.00388
+
+# Summary
+
+< 10 sentences
+
+Broad context of the field. State of the art simulations for SZ effect. Need for and current lack of fast, accessible simulations for ML. Dual purpose of student training. Tunability of sims and near-term goals for ML use with Deep Skies.
+
+# Statement of need
+
+< 20 sentences
+
+Field need for well-tuned sims and ML methods. Niche our sims fill with Deep Skies, student training, and future science plans.
+
+# Features
+
+Descriptions of functions included in DeepSZSim. Figure 1: code schematic. Figure 2: Submaps, 4x4, including 1D pressure profile, 2D Compton-y map, 2D all-noise map, and 2D all+noise map.
+
+# Citations
+
+
+For a quick reference, the following citation commands can be used:
+- `@author:2001`  ->  "Author et al. (2001)"
+- `[@author:2001]` -> "(Author et al., 2001)"
+- `[@author1:2001; @author2:2001]` -> "(Author1 et al., 2001; Author2 et al., 2002)"
+
+
+# Acknowledgements
+
+We acknowledge the Deep Skies Lab as a community of multi-domain experts and collaborators who’ve facilitated an environment of open discussion, idea-generation, and collaboration. This community was important for the development of this project.
+
+# References

pyproject.toml

@@ -0,0 +1,24 @@
+[tool.poetry]
+name = "simsz"
+version = "0.1.0"
+description = "code for fast simulations of galaxy clusters"
+authors = ["Eve Vavagiakis"]
+license = "LICENSE.txt"
+
+[tool.poetry.dependencies]
+python = "^3.9"
+camb = "^1.4.0"
+h5py = "^3.8.0"
+numpy = "^1.24.3"
+
+[tool.poetry.dev-dependencies]
+pytest = "^7.3.1"
+pytest-cov = "^4.0.0"
+
+pymaster = { version = "^1.5", optional = true }
+[tool.poetry.extras]
+pymaster = ["pymaster"]
+
+[build-system]
+requires = ["poetry-core>=1.0.0"]
+build-backend = "poetry.core.masonry.api"

simsz/__init__.py

@@ -0,0 +1,8 @@
+
+import simsz.make_sz_cluster as make_sz_cluster
+
+try:
+    from simsz.filters import get_tSZ_signal_aperture_photometry
+    from simsz.utils import Mpc_to_arcmin
+except ModuleNotFoundError:
+    pass

simsz/load_vars.py

@@ -2,26 +2,38 @@
 from astropy.cosmology import FlatLambdaCDM
 import simsz.read_yaml as read_yaml
 from typing import Union
+import os
 
 class load_vars(object):
 
-    def __init__(self, file_path= Union[None, str]):
-        self.file_path = file_path
+    def __init__(self, 
+                 file_path=os.path.join(os.path.dirname(__file__), "Settings", "inputdata.yaml")):
         self.data = []
+        self.file_path = file_path
 
     def make_dict_and_flatLCDM(self):
+        d = {}
         ref=read_yaml.YAMLOperator(self.file_path).parse_yaml()
-        survey=[key for key in ref['SURVEYS'].keys()][0]
-        survey_freq=[key for key in ref['SURVEYS'][survey].keys()][0]
-        beam_size=ref['SURVEYS'][survey][survey_freq]['beam_size']
-        noise_level=ref['SURVEYS'][survey][survey_freq]['noise_level']
-        image_size = ref['IMAGES']['image_size']
-        pix_size = ref['IMAGES']['pix_size']
+        survey = [key for key in ref['SURVEYS'].keys()][0]
+        survey_freq = [key for key in ref['SURVEYS'][survey].keys()][0]
+        beam_size_arcmin = ref['SURVEYS'][survey][survey_freq]['beam_size']
+        noise_level = ref['SURVEYS'][survey][survey_freq]['noise_level']
+        image_size_arcmin = ref['IMAGES']['image_size']
+        pix_size_arcmin = ref['IMAGES']['pix_size']
+        d["survey"] = survey
+        d["survey_freq"] = survey_freq
+        d["beam_size_arcmin"] = beam_size_arcmin
+        d["noise_level"] = noise_level
+        d["image_size_arcmin"] = image_size_arcmin
+        d["pix_size_arcmin"] = pix_size_arcmin
         for key in ref['COSMOLOGY'].keys():
             cosmo_dict=ref['COSMOLOGY'][key] #Read in cosmological parameters
 
         sigma8=cosmo_dict['sigma8']
         ns=cosmo_dict['ns']
 
         cosmo=FlatLambdaCDM(cosmo_dict['H0'], cosmo_dict['Omega_m0'], Tcmb0=cosmo_dict['t_cmb'], Ob0=cosmo_dict['Omega_b0'])
-        return(survey,survey_freq,beam_size,noise_level,image_size,pix_size,cosmo,sigma8,ns)
+        d["sigma8"] = sigma8
+        d["ns"] = ns
+        d["cosmo"] = cosmo
+        return d

make_sz_cluster.py → simsz/make_sz_cluster.py

@@ -190,7 +190,7 @@ def Pth_Battaglia2012(radius_mpc,R200_mpc,gamma,alpha,beta,xc,P0):
 
     Returns:
     --------
-    Pth: float
+    Pth: array of floats
         the thermal pressure profile normalized over P200, units of 
         keV/cm**3
     '''
@@ -208,7 +208,7 @@ def epp_to_y(profile, radii_mpc, P200_kevcm3, R200_mpc, **kwargs):
 
     Parameters:
     -----------
-    profile:
+    profile: method
         Method to get thermal pressure profile in Kev/cm^3, accepts radius, 
         R200 and **kwargs
     radii_mpc: array
@@ -389,23 +389,21 @@ def simulate_submap(M200_dist, z_dist, id_dist=None,
 
     """
     #Make a dictionary and cosmology from the .yaml
-    (survey,freq_GHz,beam_size_fwhp_arcmin,noise_level,
-     image_size,pix_size_arcmin,cosmo,sigma8,ns)=load_vars.load_vars(
-        settings_yaml).make_dict_and_flatLCDM() 
+    d=load_vars.load_vars().make_dict_and_flatLCDM() 
 
     M200_dist = np.asarray(M200_dist)
     z_dist = np.asarray(z_dist)
     if add_cmb:
         # To make sure to only calculate this once if its a dist
-        ps = simtools.get_cls(ns=ns, cosmo=cosmo) 
+        ps = simtools.get_cls(ns=d['ns'], cosmo=d['cosmo']) 
 
     if not os.path.exists(savedir):
             print(f"making local directory `{savedir}`")
             os.mkdir(savedir)
 
     # Generate a run_id based on time of running and freq
     rand_num = np.random.randint(10**6)
-    run_id = dt.now().strftime('%y%m%d%H%M%S%f_')+str(freq_GHz)+'_'+str(
+    run_id = dt.now().strftime('%y%m%d%H%M%S%f_')+str(d['survey_freq'])+'_'+str(
         rand_num).zfill(6) 
 
     f = h5py.File(os.path.join(savedir, f'sz_sim_{run_id}.h5'), 'a')
@@ -415,20 +413,20 @@ def simulate_submap(M200_dist, z_dist, id_dist=None,
     for index, M200 in np.ndenumerate(M200_dist):
         z = z_dist[index]
         if R200_dist is None:
-            (M200,R200,_c200)= get_r200_and_c200(cosmo,sigma8,
-                                                                ns,M200,z)
+            (M200,R200,_c200)= get_r200_and_c200(d['cosmo'],d['sigma8'],
+                                                                d['ns'],M200,z)
         else:
             R200 = R200_dist[index]
 
 
-        y_map = generate_y_submap(z, M200, R200, cosmo, 
-                                                  image_size, pix_size_arcmin)
+        y_map = generate_y_submap(z, M200, R200, d['cosmo'], 
+                                                  d['image_size_arcmin'], d['pix_size_arcmin'])
         #get f_SZ for observation frequency
-        fSZ = simtools.f_sz(freq_GHz,cosmo.Tcmb0) 
-        dT_map = (y_map * cosmo.Tcmb0 * fSZ).to(u.uK)
+        fSZ = simtools.f_sz(d['survey_freq'],d['cosmo'].Tcmb0) 
+        dT_map = (y_map * d['cosmo'].Tcmb0 * fSZ).to(u.uK)
 
         cluster = {'M200': M200, 'R200': R200, 'redshift_z': z, 
-                   'y_central': y_map[image_size//2][image_size//2]}
+                   'y_central': y_map[d['image_size_arcmin']//2][d['image_size_arcmin']//2]}
 
         if id_dist is not None:
             cluster['ID'] = id_dist[index]
@@ -440,17 +438,17 @@ def simulate_submap(M200_dist, z_dist, id_dist=None,
         if add_cmb:
             conv_map, cmb_map = simtools.add_cmb_map_and_convolve(dT_map, 
                                                                   ps, 
-                                                                  pix_size_arcmin, 
-                                                                  beam_size_fwhp_arcmin)
+                                                                  d['pix_size_arcmin'], 
+                                                                  d['beam_size_arcmin'])
             cluster['CMB_map'] = cmb_map
 
         else:
             conv_map = simtools.convolve_map_with_gaussian_beam(
-                pix_size_arcmin, beam_size_fwhp_arcmin, dT_map)
+                d['pix_size_arcmin'], d['beam_size_fwhp_arcmin'], dT_map)
 
-        if not noise_level == 0:
-            noise_map=noise.generate_noise_map(image_size, 
-                                               noise_level, pix_size_arcmin)
+        if not d['noise_level'] == 0:
+            noise_map=noise.generate_noise_map(d['image_size_arcmin'], 
+                                               d['noise_level'], d['pix_size_arcmin'])
             final_map = conv_map + noise_map
 
             cluster['noise_map'] = noise_map
@@ -460,7 +458,7 @@ def simulate_submap(M200_dist, z_dist, id_dist=None,
         utils.save_sim_to_h5(f, f"sim_{cluster['ID']}", cluster)
 
     f.close()
-    shutil.copyfile(settings_yaml, os.path.join(savedir, f'params_{run_id}.yaml'))
+    shutil.copyfile(os.path.join(os.path.dirname(__file__), "Settings", "inputdata.yaml"), os.path.join(savedir, f'params_{run_id}.yaml'))
 
     return clusters
 

simsz/read_yaml.py

@@ -4,7 +4,7 @@
 
 class YAMLOperator(object):
 
-    def __init__(self, file_path= Union[None, str]):
+    def __init__(self, file_path=os.path.join(os.path.dirname(__file__), "Settings", "inputdata.yaml")):
 
         self.file_path = file_path
 

simsz/utils.py

@@ -122,4 +122,4 @@ def save_sim_to_h5(file, name, data, attributes={}, overwrite=False):
     if name not in file:
         file.create_group(name)
     for aname, attr in attributes.items():
-        file[name].attrs[aname] = attr
+        file[name].attrs[aname] = attr

tests/test_simtools.py

@@ -7,6 +7,8 @@
 from astropy import units as u
 from pixell import enmap
 import camb
+from astropy.cosmology import FlatLambdaCDM
+
 
 def get_mock_cosmology():
     '''
@@ -21,9 +23,9 @@ def get_mock_cosmology():
 
 class TestSimTools():
     def test_f_sz(self):
-        freq = 100
+        freq = 1
+        (cosmo,sigma8,ns) = get_mock_cosmology()
         T_CMB = cosmo.Tcmb0
         fsz = simtools.f_sz(freq,T_CMB)
-        fsz_expected = 12.509
-        assert u.isclose(fsz,fsz_expected), 
-        f"Expected {fsz_expected}, but got {fsz}"
+        fsz_expected = -1.999948
+        assert u.isclose(fsz,fsz_expected),f"Expected {fsz_expected}, but got {fsz}"