One-shot D_ell cross-check: so_gaussian_fg vs PySM Gaussian foregrounds

so_gaussian_fg_crosscheck.executed.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "16017263",
   "metadata": {},
   "source": [
    "# One-shot cross-check: `so_gaussian_fg` vs PySM Gaussian foregrounds\n",
    "\n",
    "This notebook performs a one-shot `D_ell` comparison of the **original**\n",
    "[`1cosmologist/so_gaussian_fg`](https://github.com/1cosmologist/so_gaussian_fg)\n",
    "implementation and the PySM Gaussian foreground implementation.\n",
    "\n",
    "Scope:\n",
    "- Compare EE/BB `D_ell` at pivot frequencies.\n",
    "- Original code has no TT model, so TT is not compared.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "da0b6b2a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-12T23:28:32.557819Z",
     "iopub.status.busy": "2026-02-12T23:28:32.557541Z",
     "iopub.status.idle": "2026-02-12T23:28:34.128664Z",
     "shell.execute_reply": "2026-02-12T23:28:34.128091Z"
    }
   },
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "import json\n",
    "import importlib.util\n",
    "import sys\n",
    "import types\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pysm3\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "17d882eb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-12T23:28:34.130764Z",
     "iopub.status.busy": "2026-02-12T23:28:34.130528Z",
     "iopub.status.idle": "2026-02-12T23:28:34.134806Z",
     "shell.execute_reply": "2026-02-12T23:28:34.134301Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PosixPath('/tmp/so_gaussian_fg_ref')"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Clone original repo if needed\n",
    "orig_repo = Path('/tmp/so_gaussian_fg_ref')\n",
    "if not orig_repo.exists():\n",
    "    import subprocess\n",
    "    subprocess.run(\n",
    "        ['git', 'clone', '--depth', '1', 'https://github.com/1cosmologist/so_gaussian_fg', str(orig_repo)],\n",
    "        check=True,\n",
    "    )\n",
    "orig_repo\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "522cf223",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-12T23:28:34.136384Z",
     "iopub.status.busy": "2026-02-12T23:28:34.136272Z",
     "iopub.status.idle": "2026-02-12T23:28:34.156139Z",
     "shell.execute_reply": "2026-02-12T23:28:34.155386Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "so_gaussian_fg_generate.GaussianForegroundSimulator"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Provide a minimal `skytools` stub so the original module can import.\n",
    "skytools_stub = types.ModuleType('skytools')\n",
    "skytools_stub.KCMB_to_MJysr = lambda freq: 1.0\n",
    "skytools_stub.MJysr_to_Kb = lambda freq: 1.0\n",
    "skytools_stub.greybody = lambda f, fp, beta, td: (f / fp) ** beta\n",
    "skytools_stub.powerlaw = lambda f, fp, beta: (f / fp) ** beta\n",
    "sys.modules['skytools'] = skytools_stub\n",
    "\n",
    "mod_path = orig_repo / 'generate_gaussian_fg.py'\n",
    "spec = importlib.util.spec_from_file_location('so_gaussian_fg_generate', mod_path)\n",
    "mod = importlib.util.module_from_spec(spec)\n",
    "spec.loader.exec_module(mod)\n",
    "OrigSim = mod.GaussianForegroundSimulator\n",
    "OrigSim\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1a46806e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-12T23:28:34.158250Z",
     "iopub.status.busy": "2026-02-12T23:28:34.158011Z",
     "iopub.status.idle": "2026-02-12T23:28:34.430624Z",
     "shell.execute_reply": "2026-02-12T23:28:34.429777Z"
    }
   },
   "outputs": [],
   "source": [
    "# Compute D_ell arrays from both implementations\n",
    "nside = 64\n",
    "lmax = 3 * nside - 1\n",
    "ells = np.arange(lmax + 1)\n",
    "dell_factor = ells * (ells + 1) / (2 * np.pi)\n",
    "\n",
    "orig = OrigSim(instr_params={'freqs': [93.0], 'beams': [30.0], 'nsides': [nside]})\n",
    "\n",
    "orig_dell_dust_ee = np.zeros_like(ells, dtype=np.float64)\n",
    "orig_dell_dust_bb = np.zeros_like(ells, dtype=np.float64)\n",
    "orig_dell_sync_ee = np.zeros_like(ells, dtype=np.float64)\n",
    "orig_dell_sync_bb = np.zeros_like(ells, dtype=np.float64)\n",
    "orig_dell_dust_ee[2:] = orig.cl_dust_EE[2:] * dell_factor[2:]\n",
    "orig_dell_dust_bb[2:] = orig.cl_dust_BB[2:] * dell_factor[2:]\n",
    "orig_dell_sync_ee[2:] = orig.cl_sync_EE[2:] * dell_factor[2:]\n",
    "orig_dell_sync_bb[2:] = orig.cl_sync_BB[2:] * dell_factor[2:]\n",
    "\n",
    "pysm_dust = pysm3.GaussianDust(nside=nside, seed=112359)\n",
    "pysm_sync = pysm3.GaussianSynchrotron(nside=nside, seed=112360)\n",
    "\n",
    "pysm_dell_dust_ee = np.zeros_like(ells, dtype=np.float64)\n",
    "pysm_dell_dust_bb = np.zeros_like(ells, dtype=np.float64)\n",
    "pysm_dell_sync_ee = np.zeros_like(ells, dtype=np.float64)\n",
    "pysm_dell_sync_bb = np.zeros_like(ells, dtype=np.float64)\n",
    "pysm_dell_dust_ee[2:] = pysm_dust.cl_ee[2:] * dell_factor[2:]\n",
    "pysm_dell_dust_bb[2:] = pysm_dust.cl_bb[2:] * dell_factor[2:]\n",
    "pysm_dell_sync_ee[2:] = pysm_sync.cl_ee[2:] * dell_factor[2:]\n",
    "pysm_dell_sync_bb[2:] = pysm_sync.cl_bb[2:] * dell_factor[2:]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8f0fda71",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-12T23:28:34.432344Z",
     "iopub.status.busy": "2026-02-12T23:28:34.432205Z",
     "iopub.status.idle": "2026-02-12T23:28:34.436218Z",
     "shell.execute_reply": "2026-02-12T23:28:34.435713Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"comparison\": {\n",
      "    \"dust_EE\": {\n",
      "      \"max_abs_diff\": 0.0,\n",
      "      \"max_rel_diff\": 0.0,\n",
      "      \"ell80_original\": 56.0,\n",
      "      \"ell80_pysm\": 56.0\n",
      "    },\n",
      "    \"dust_BB\": {\n",
      "      \"max_abs_diff\": 0.0,\n",
      "      \"max_rel_diff\": 0.0,\n",
      "      \"ell80_original\": 28.0,\n",
      "      \"ell80_pysm\": 28.0\n",
      "    },\n",
      "    \"sync_EE\": {\n",
      "      \"max_abs_diff\": 0.0,\n",
      "      \"max_rel_diff\": 0.0,\n",
      "      \"ell80_original\": 9.0,\n",
      "      \"ell80_pysm\": 9.0\n",
      "    },\n",
      "    \"sync_BB\": {\n",
      "      \"max_abs_diff\": 0.0,\n",
      "      \"max_rel_diff\": 0.0,\n",
      "      \"ell80_original\": 1.6,\n",
      "      \"ell80_pysm\": 1.6\n",
      "    }\n",
      "  },\n",
      "  \"notes\": [\n",
      "    \"Compares D_ell at pivot frequencies for EE/BB.\",\n",
      "    \"Original so_gaussian_fg has no TT model.\",\n",
      "    \"Uses original GaussianForegroundSimulator.dust_cl/sync_cl code path.\"\n",
      "  ]\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "def summarize(a, b):\n",
    "    diff = np.abs(a - b)\n",
    "    rel = np.zeros_like(diff)\n",
    "    valid = np.abs(a) > 0\n",
    "    rel[valid] = diff[valid] / np.abs(a[valid])\n",
    "    return {\n",
    "        'max_abs_diff': float(np.max(diff[2:])),\n",
    "        'max_rel_diff': float(np.max(rel[2:])),\n",
    "        'ell80_original': float(a[80]),\n",
    "        'ell80_pysm': float(b[80]),\n",
    "    }\n",
    "\n",
    "report = {\n",
    "    'comparison': {\n",
    "        'dust_EE': summarize(orig_dell_dust_ee, pysm_dell_dust_ee),\n",
    "        'dust_BB': summarize(orig_dell_dust_bb, pysm_dell_dust_bb),\n",
    "        'sync_EE': summarize(orig_dell_sync_ee, pysm_dell_sync_ee),\n",
    "        'sync_BB': summarize(orig_dell_sync_bb, pysm_dell_sync_bb),\n",
    "    },\n",
    "    'notes': [\n",
    "        'Compares D_ell at pivot frequencies for EE/BB.',\n",
    "        'Original so_gaussian_fg has no TT model.',\n",
    "        'Uses original GaussianForegroundSimulator.dust_cl/sync_cl code path.'\n",
    "    ]\n",
    "}\n",
    "\n",
    "print(json.dumps(report, indent=2))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b01374d9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-12T23:28:34.438216Z",
     "iopub.status.busy": "2026-02-12T23:28:34.437997Z",
     "iopub.status.idle": "2026-02-12T23:28:34.980885Z",
     "shell.execute_reply": "2026-02-12T23:28:34.980387Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot comparisons\n",
    "ell = np.arange(2, lmax + 1)\n",
    "\n",
    "fig, axes = plt.subplots(1, 2, figsize=(12, 5), constrained_layout=True)\n",
    "\n",
    "# Dust\n",
    "axes[0].loglog(ell, orig_dell_dust_ee[2:], label='Original Dust EE', lw=2)\n",
    "axes[0].loglog(ell, pysm_dell_dust_ee[2:], '--', label='PySM Dust EE', lw=2)\n",
    "axes[0].loglog(ell, orig_dell_dust_bb[2:], label='Original Dust BB', lw=2)\n",
    "axes[0].loglog(ell, pysm_dell_dust_bb[2:], '--', label='PySM Dust BB', lw=2)\n",
    "axes[0].set_title('Dust D_ell at pivot')\n",
    "axes[0].set_xlabel('ell')\n",
    "axes[0].set_ylabel('D_ell [uK_CMB^2]')\n",
    "axes[0].legend()\n",
    "axes[0].grid(True, alpha=0.3)\n",
    "\n",
    "# Sync\n",
    "axes[1].loglog(ell, orig_dell_sync_ee[2:], label='Original Sync EE', lw=2)\n",
    "axes[1].loglog(ell, pysm_dell_sync_ee[2:], '--', label='PySM Sync EE', lw=2)\n",
    "axes[1].loglog(ell, orig_dell_sync_bb[2:], label='Original Sync BB', lw=2)\n",
    "axes[1].loglog(ell, pysm_dell_sync_bb[2:], '--', label='PySM Sync BB', lw=2)\n",
    "axes[1].set_title('Synchrotron D_ell at pivot')\n",
    "axes[1].set_xlabel('ell')\n",
    "axes[1].set_ylabel('D_ell [uK_CMB^2]')\n",
    "axes[1].legend()\n",
    "axes[1].grid(True, alpha=0.3)\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e6dbc7ed",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-12T23:28:34.982000Z",
     "iopub.status.busy": "2026-02-12T23:28:34.981828Z",
     "iopub.status.idle": "2026-02-12T23:28:35.136267Z",
     "shell.execute_reply": "2026-02-12T23:28:35.135534Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Residual plots (PySM - Original)\n",
    "fig, axes = plt.subplots(1, 2, figsize=(12, 4), constrained_layout=True)\n",
    "\n",
    "axes[0].plot(ell, pysm_dell_dust_ee[2:] - orig_dell_dust_ee[2:], label='Dust EE residual')\n",
    "axes[0].plot(ell, pysm_dell_dust_bb[2:] - orig_dell_dust_bb[2:], label='Dust BB residual')\n",
    "axes[0].set_title('Dust residuals')\n",
    "axes[0].set_xlabel('ell')\n",
    "axes[0].set_ylabel('PySM - Original')\n",
    "axes[0].legend()\n",
    "axes[0].grid(True, alpha=0.3)\n",
    "\n",
    "axes[1].plot(ell, pysm_dell_sync_ee[2:] - orig_dell_sync_ee[2:], label='Sync EE residual')\n",
    "axes[1].plot(ell, pysm_dell_sync_bb[2:] - orig_dell_sync_bb[2:], label='Sync BB residual')\n",
    "axes[1].set_title('Synch residuals')\n",
    "axes[1].set_xlabel('ell')\n",
    "axes[1].set_ylabel('PySM - Original')\n",
    "axes[1].legend()\n",
    "axes[1].grid(True, alpha=0.3)\n",
    "\n",
    "plt.show()\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}

so_gaussian_fg_crosscheck_README.md

One-shot cross-check: so_gaussian_fg vs PySM Gaussian foregrounds

This gist contains a one-shot executed notebook comparing the original 1cosmologist/so_gaussian_fg power spectrum implementation against the PySM Gaussian foreground implementation.

Scope:

• D_ell comparison at pivot frequencies for EE/BB.
• Original code has no TT model, so TT is not compared.

Result summary:

• dust_EE max abs/rel diff: 0 / 0
• dust_BB max abs/rel diff: 0 / 0
• sync_EE max abs/rel diff: 0 / 0
• sync_BB max abs/rel diff: 0 / 0

See so_gaussian_fg_crosscheck.executed.ipynb for embedded plots and full details.

so_gaussian_fg_crosscheck_summary.json

{
  "comparison": {
    "dust_EE": {
      "max_abs_diff": 0.0,
      "max_rel_diff": 0.0,
      "ell80_original": 56.0,
      "ell80_pysm": 56.0
    },
    "dust_BB": {
      "max_abs_diff": 0.0,
      "max_rel_diff": 0.0,
      "ell80_original": 28.0,
      "ell80_pysm": 28.0
    },
    "sync_EE": {
      "max_abs_diff": 0.0,
      "max_rel_diff": 0.0,
      "ell80_original": 9.0,
      "ell80_pysm": 9.0
    },
    "sync_BB": {
      "max_abs_diff": 0.0,
      "max_rel_diff": 0.0,
      "ell80_original": 1.6,
      "ell80_pysm": 1.6
    }
  },
  "notes": [
    "Compares D_ell at pivot frequencies for EE/BB.",
    "Original so_gaussian_fg has no TT model.",
    "Uses original GaussianForegroundSimulator.dust_cl/sync_cl code path."
  ]
}