Add DarkElf + test notebooks

.github/scripts/install_on_linux.sh

@@ -18,9 +18,12 @@ echo "in that folder is:"
 ls $LD_LIBRARY_PATH ; echo $LD_LIBRARY_PATH
 echo "go back to installation; ls ; pwd "
 
-cd dddm
+
 echo "Doing other conda and pip:"
 # We need the data files from this
 git clone https://github.com/joranangevaare/verne ../verne
 pip install -e ../verne
+git clone https://github.com/JoranAngevaare/DarkELF ../darkelf
+pip install -e ../darkelf
+cd dddm
 echo "done"

.github/workflows/test_package.yml

@@ -57,6 +57,8 @@ jobs:
           pip install git+https://github.com/jorana/wimprates
           git clone https://github.com/jorana/verne
           pip install -e verne
+          git clone https://github.com/JoranAngevaare/DarkELF
+          pip install -e DarkELF
       - name: Install other stuff
         run: |
           pip install -r extra_requirements/requirements-tests.txt
@@ -68,6 +70,7 @@ jobs:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
         run: |
           coverage run --source=dddm -m pytest -vsx --durations 0
+          coverage run --append --source=dddm -m pytest --nbmake -n=auto ./notebooks
           coveralls --service=github
       - name: Test package (linux)
         if: matrix.os == 'ubuntu-latest' && matrix.test == 'pytest'
@@ -77,6 +80,7 @@ jobs:
           export LD_LIBRARY_PATH=/home/runner/work/dddm/dddm/MultiNest/lib
           export RUN_TEST_EXTENDED=1
           coverage run --source=dddm -m pytest -vsx --durations 0
+          coverage run --append --source=dddm -m pytest --nbmake -n=auto ./notebooks
           coveralls --service=github
       - name: Test package - fail fast (linux)
         if: matrix.os == 'ubuntu-latest' && matrix.test == 'fail-fast'
@@ -86,7 +90,6 @@ jobs:
         run: |
           export LD_LIBRARY_PATH=/home/runner/work/dddm/dddm/MultiNest/lib
           coverage run --source=dddm -m pytest -vsx --durations 0
-          coveralls --service=github
       - name: Coveralls
         if: matrix.test == 'coveralls'
         env:
@@ -96,6 +99,7 @@ jobs:
           export LD_LIBRARY_PATH=/home/runner/work/dddm/dddm/MultiNest/lib
           export RUN_TEST_EXTENDED=1
           coverage run --source=dddm setup.py test -v
+          coverage run --append --source=dddm -m pytest --nbmake -n=auto ./notebooks
           coveralls --service=github
       - name: goodbye
         run: echo goodbye

extra_requirements/requirements-tests.txt

@@ -2,23 +2,31 @@ corner==2.2.1
 coveralls==3.3.1
 emcee==3.1.1
 gitpython==3.1.27
+gvar==11.9.7
 hypothesis==6.21.1
 immutabledict==2.2.1
 matplotlib==3.5.1
+matplotlib-label-lines==0.5.1
 multihist==0.6.5
 nestle==0.2.0
-numba==0.55.1
+nbmake==1.3.0 
+numba==0.55.2
 numericalunits==1.25
-numpy==1.21.6
+numpy==1.22.4
 pandas==1.4.2
 psutil==5.9.0
 pytest==7.1.2
 pytest-runner==6.0.0
+pytest-xdist==2.5.0
+PyYAML==6.0
 scipy==1.8.0
 seaborn==0.11.2
 tqdm==4.64.0
+vegas==5.1.1
+
 
 # These two packages require metadata not shipped via pip+git
 git+https://github.com/jorana/wimprates
+# git+https://github.com/JoranAngevaare/DarkELF
 # git+https://github.com/jorana/verne
 

notebooks/summary.ipynb

@@ -2,18 +2,39 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
+   "execution_count": 4,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2022-05-23T15:23:57.392218Z",
+     "start_time": "2022-05-23T15:23:54.106785Z"
+    }
+   },
    "outputs": [],
    "source": [
-    "import DirectDmTargets as dddm"
+    "import dddm"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 5,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2022-05-23T15:23:57.405372Z",
+     "start_time": "2022-05-23T15:23:57.395851Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.3.2'"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "import wimprates as wr\n",
     "wr.__version__"
@@ -214,13 +235,16 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "def get_gal_spec(det):\n",
-    "    spec_class = dddm.GenSpectrum(50, 1e-45, use_SHM, dddm.experiment[det])\n",
-    "    spec_class.set_config(\n",
-    "        dict(E_max = 200,\n",
-    "             n_energy_bins = 200\n",
-    "            ))\n",
-    "    return spec_class.get_data(poisson = False)"
+    "experiments = {'Xe_simple': dddm.examples.XenonSimple,\n",
+    "               'Ge_simple': dddm.examples.GermaniumSimple,\n",
+    "               'Ar_simple': dddm.examples.ArgonSimple,\n",
+    "}\n",
+    "def get_gal_spec(det, mw =50):\n",
+    "    spec_class = dddm.GenSpectrum(\n",
+    "        dark_matter_model=use_SHM,\n",
+    "        experiment=experiments[det](n_energy_bins=200, e_min_kev=0, e_max_kev=200)\n",
+    "    )\n",
+    "    return spec_class.get_data(wimp_mass=mw, cross_section=1e-45, poisson = False)"
    ]
   },
   {
@@ -247,12 +271,11 @@
    "outputs": [],
    "source": [
     "def get_det_spec(det, mw =50):\n",
-    "    spec_class = dddm.DetectorSpectrum(mw, 1e-45, use_SHM, dddm.experiment[det])\n",
-    "    spec_class.set_config(\n",
-    "        dict(E_max = 200,\n",
-    "             n_energy_bins = 200\n",
-    "            ))\n",
-    "    return spec_class.get_data(poisson = False)"
+    "    spec_class = dddm.DetectorSpectrum(\n",
+    "        dark_matter_model=use_SHM,\n",
+    "        experiment=experiments[det](n_energy_bins=200, e_min_kev=0, e_max_kev=200)\n",
+    "    )\n",
+    "    return spec_class.get_data(wimp_mass=mw, cross_section=1e-45, poisson = False)"
    ]
   },
   {
@@ -316,8 +339,19 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fit_class = dddm.NestedSamplerStatModel('Xe_simple')\n",
-    "fit_class.config['sampler'] = 'nestle'\n",
+    "context = dddm.base_context()\n",
+    "fit_class = context.get_sampler_for_detector(\n",
+    "    wimp_mass=50,\n",
+    "    cross_section=1e-45,\n",
+    "    sampler_name='nestle',\n",
+    "    detector_name='Xe_simple',\n",
+    "    prior=\"Pato_2010\",\n",
+    "    halo_name='shm',\n",
+    "    detector_kwargs=None,\n",
+    "    halo_kwargs=None,\n",
+    "    sampler_kwargs=dict(nlive=100, tol=0.1, verbose=1),\n",
+    "    fit_parameters=('log_mass', 'log_cross_section',),\n",
+    ")\n",
     "print(f\"Fitting for parameters:\\n{fit_class.config['fit_parameters']}\")"
    ]
   },
@@ -327,8 +361,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fit_class.run_nestle()\n",
-    "fit_class.get_summary()"
+    "fit_class.run()\n",
+    "results = fit_class.get_summary()\n",
+    "print(results)"
    ]
   },
   {
@@ -346,9 +381,18 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fit_unconstrained = dddm.NestedSamplerStatModel('Xe_simple')\n",
-    "fit_unconstrained.set_fit_parameters(fit_unconstrained.known_parameters)\n",
-    "print(f\"Fitting for parameters:\\n{fit_unconstrained.fit_class.config['fit_parameters']}\")"
+    "fit_unconstrained = context.get_sampler_for_detector(\n",
+    "    wimp_mass=50,\n",
+    "    cross_section=1e-45,\n",
+    "    sampler_name='nestle',\n",
+    "    detector_name='Xe_simple',\n",
+    "    prior=\"Pato_2010\",\n",
+    "    halo_name='shm',\n",
+    "    detector_kwargs=None,\n",
+    "    halo_kwargs=None,\n",
+    "    sampler_kwargs=dict(nlive=100, tol=0.1, verbose=1),\n",
+    "    fit_parameters=dddm.statistics.get_param_list(),\n",
+    ")"
    ]
   },
   {
@@ -357,8 +401,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fit_unconstrained.run_nestle()\n",
-    "fit_unconstrained.get_summary()"
+    "fit_unconstrained.run()\n",
+    "results = fit_unconstrained.get_summary()\n",
+    "print(results)"
    ]
   },
   {
@@ -367,7 +412,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fit_unconstrained.show_corner()"
+    "fit_unconstrained.show_corner()\n"
    ]
   },
   {
@@ -387,7 +432,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -401,9 +446,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.1"
+   "version": "3.10.4"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
-}
+}