diff --git a/notebooks/mflike_tutorial.ipynb b/notebooks/mflike_tutorial.ipynb
index 0588b74..5e8462c 100644
--- a/notebooks/mflike_tutorial.ipynb
+++ b/notebooks/mflike_tutorial.ipynb
@@ -27,8 +27,8 @@
      "text": [
       "     Numpy : 1.23.1\n",
       "Matplotlib : 3.3.3\n",
-      "      CAMB : 1.4.0\n",
-      "    Cobaya : 3.2.2\n"
+      "      CAMB : 1.5.0\n",
+      "    Cobaya : 3.4.1\n"
      ]
     }
    ],
@@ -96,25 +96,32 @@
     "    \"a_psee\": 0.003,\n",
     "    \"a_pste\": 0.042,\n",
     "    \"xi\": 0.10,\n",
+    "    \"beta_s\": -2.5,    #beta radio\n",
+    "  \"alpha_s\": 1,      #alpha radio\n",
+    "  \"T_effd\": 19.6,    #effective galactic dust temperature\n",
+    "  \"beta_d\": 1.5,     #beta galactic dust\n",
+    "  \"alpha_dT\": -0.6,  #galactic dust ell slope for T\n",
+    "  \"alpha_dE\": -0.4,  #galactic dust ell slope for E\n",
+    "  \"alpha_p\": 1,      #CIB poisson ell slope \n",
     "}\n",
     "\n",
     "nuisance_params = {\n",
     "    \"bandint_shift_LAT_93\": 0,  # only ideal values for now\n",
     "    \"bandint_shift_LAT_145\": 0,\n",
     "    \"bandint_shift_LAT_225\": 0,\n",
-    "    \"calT_LAT_93\": 1,\n",
+    " #   \"calT_LAT_93\": 1,\n",
     "    \"calE_LAT_93\": 1,\n",
-    "    \"calT_LAT_145\": 1,\n",
+    " #   \"calT_LAT_145\": 1,\n",
     "    \"calE_LAT_145\": 1,\n",
-    "    \"calT_LAT_225\": 1,\n",
+    " #   \"calT_LAT_225\": 1,\n",
     "    \"calE_LAT_225\": 1,\n",
     "    \"cal_LAT_93\": 1,\n",
     "    \"cal_LAT_145\": 1,\n",
     "    \"cal_LAT_225\": 1,\n",
-    "    \"calG_all\": 1,\n",
-    "    \"alpha_LAT_93\": 0,\n",
-    "    \"alpha_LAT_145\": 0,\n",
-    "    \"alpha_LAT_225\": 0,\n",
+    "  #  \"calG_all\": 1,\n",
+    "  #  \"alpha_LAT_93\": 0,\n",
+    "  #  \"alpha_LAT_145\": 0,\n",
+    "  #  \"alpha_LAT_225\": 0,\n",
     "}"
    ]
   },
@@ -187,6 +194,16 @@
       "Pass --enable-32bits-pci-domain to configure to support such devices\n",
       "(warning: it would break the library ABI, don't enable unless really needed).\n"
      ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -369,7 +386,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -409,7 +426,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -430,7 +447,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -478,7 +495,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -495,7 +512,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -516,7 +533,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -566,7 +583,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -594,7 +611,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -615,7 +632,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -656,7 +673,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -698,7 +715,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -710,7 +727,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -726,7 +743,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -789,14 +806,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/serenagiardiello/.local/lib/python3.8/site-packages/sacc/sacc.py:370: UserWarning: Empty index selected - maybe you should check the tracer order?\n",
+      "/home/serenagiardiello/anaconda3/envs/mflike/lib/python3.8/site-packages/sacc/sacc.py:378: UserWarning: Empty index selected - maybe you should check the tracer order?\n",
       "  warnings.warn(\"Empty index selected - maybe you \"\n"
      ]
     },
@@ -882,7 +899,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -892,11 +909,17 @@
     "        k: {\n",
     "            \"prior\": {\n",
     "                \"min\": 0.9 * v if v != 0 else -0.5,\n",
-    "                \"max\": 1.1 * v if v != 0 else +0.5,\n",
+    "                \"max\": 1.1 * v if (v != 0 and v > 0) else +0.5,\n",
     "            }\n",
     "        }\n",
     "        for k, v in sampled_params.items()\n",
-    "        if k not in [\"logA\", \"As\"]\n",
+    "        if k not in [\"logA\", \"As\",\"beta_s\",\n",
+    "            \"alpha_s\",\n",
+    "            \"T_effd\",\n",
+    "            \"beta_d\",\n",
+    "            \"alpha_dT\",\n",
+    "            \"alpha_dE\",\n",
+    "            \"alpha_p\" ]\n",
     "    }\n",
     ")\n",
     "\n",
@@ -909,6 +932,65 @@
     "}"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'cosmomc_theta': {'prior': {'min': 0.009368280000000001,\n",
+       "   'max': 0.011450120000000001}},\n",
+       " 'logA': {'prior': {'min': 2.7396000000000003, 'max': 3.3484000000000003},\n",
+       "  'drop': True},\n",
+       " 'As': {'value': 'lambda logA: 1e-10*np.exp(logA)'},\n",
+       " 'ombh2': {'prior': {'min': 0.020133, 'max': 0.024607000000000004}},\n",
+       " 'omch2': {'prior': {'min': 0.108, 'max': 0.132}},\n",
+       " 'ns': {'prior': {'min': 0.86841, 'max': 1.06139}},\n",
+       " 'Alens': {'prior': {'min': 0.9, 'max': 1.1}},\n",
+       " 'tau': {'prior': {'min': 0.04896, 'max': 0.059840000000000004}},\n",
+       " 'a_tSZ': {'prior': {'min': 2.9699999999999998, 'max': 3.63}},\n",
+       " 'a_kSZ': {'prior': {'min': 1.4400000000000002, 'max': 1.7600000000000002}},\n",
+       " 'a_p': {'prior': {'min': 6.210000000000001, 'max': 7.590000000000001}},\n",
+       " 'beta_p': {'prior': {'min': 1.9800000000000002, 'max': 2.4200000000000004}},\n",
+       " 'a_c': {'prior': {'min': 4.41, 'max': 5.390000000000001}},\n",
+       " 'beta_c': {'prior': {'min': 1.9800000000000002, 'max': 2.4200000000000004}},\n",
+       " 'a_s': {'prior': {'min': 2.79, 'max': 3.4100000000000006}},\n",
+       " 'T_d': {'prior': {'min': 8.64, 'max': 10.56}},\n",
+       " 'a_gtt': {'prior': {'min': 2.52, 'max': 3.08}},\n",
+       " 'a_gte': {'prior': {'min': 0.09000000000000001, 'max': 0.11000000000000001}},\n",
+       " 'a_gee': {'prior': {'min': 0.09000000000000001, 'max': 0.11000000000000001}},\n",
+       " 'a_psee': {'prior': {'min': 0.0027, 'max': 0.0033000000000000004}},\n",
+       " 'a_pste': {'prior': {'min': 0.0378, 'max': 0.046200000000000005}},\n",
+       " 'xi': {'prior': {'min': 0.09000000000000001, 'max': 0.11000000000000001}},\n",
+       " 'beta_s': -2.5,\n",
+       " 'alpha_s': 1,\n",
+       " 'T_effd': 19.6,\n",
+       " 'beta_d': 1.5,\n",
+       " 'alpha_dT': -0.6,\n",
+       " 'alpha_dE': -0.4,\n",
+       " 'alpha_p': 1,\n",
+       " 'bandint_shift_LAT_93': {'prior': {'min': -0.5, 'max': 0.5}},\n",
+       " 'bandint_shift_LAT_145': {'prior': {'min': -0.5, 'max': 0.5}},\n",
+       " 'bandint_shift_LAT_225': {'prior': {'min': -0.5, 'max': 0.5}},\n",
+       " 'calE_LAT_93': {'prior': {'min': 0.9, 'max': 1.1}},\n",
+       " 'calE_LAT_145': {'prior': {'min': 0.9, 'max': 1.1}},\n",
+       " 'calE_LAT_225': {'prior': {'min': 0.9, 'max': 1.1}},\n",
+       " 'cal_LAT_93': {'prior': {'min': 0.9, 'max': 1.1}},\n",
+       " 'cal_LAT_145': {'prior': {'min': 0.9, 'max': 1.1}},\n",
+       " 'cal_LAT_225': {'prior': {'min': 0.9, 'max': 1.1}}}"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sampled_params"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -921,7 +1003,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [
     {
@@ -958,7 +1040,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dict_keys(['cosmomc_theta', 'logA', 'ombh2', 'omch2', 'ns', 'Alens', 'tau', 'a_tSZ', 'a_kSZ', 'a_p', 'beta_p', 'a_c', 'beta_c', 'a_s', 'T_d', 'a_gtt', 'a_gte', 'a_gee', 'a_psee', 'a_pste', 'xi', 'bandint_shift_LAT_93', 'bandint_shift_LAT_145', 'bandint_shift_LAT_225', 'calE_LAT_93', 'calE_LAT_145', 'calE_LAT_225', 'cal_LAT_93', 'cal_LAT_145', 'cal_LAT_225'])"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.parameterization.sampled_params().keys()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -977,7 +1079,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1001,7 +1103,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [
     {
@@ -1014,11 +1116,21 @@
    ],
    "source": [
     "deriv = {k: None for k in fisher_params}\n",
+    "fg_fix = {\"beta_s\": -2.5,    #beta radio\n",
+    "  \"alpha_s\": 1,      #alpha radio\n",
+    "  \"T_effd\": 19.6,    #effective galactic dust temperature\n",
+    "  \"beta_d\": 1.5,     #beta galactic dust\n",
+    "  \"alpha_dT\": -0.6,  #galactic dust ell slope for T\n",
+    "  \"alpha_dE\": -0.4,  #galactic dust ell slope for E\n",
+    "  \"alpha_p\": 1,      #CIB poisson ell slope \n",
+    "}\n",
+    "\n",
     "for i, p in enumerate(fisher_params):\n",
     "\n",
     "    def _get_power_spectra(epsilon):\n",
     "        point = defaults.copy()\n",
     "        point.update({p: point[p] * (1 + epsilon) if point[p] != 0 else point[p] + epsilon})\n",
+    "        point.update(fg_fix)\n",
     "        model.logposterior(point)\n",
     "        cl = model.theory[\"camb\"].get_Cl(ell_factor=True)\n",
     "        return mflike._get_power_spectra(cl, **point)\n",
@@ -1058,7 +1170,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [
     {
@@ -1112,32 +1224,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "param: cosmomc_theta, sigma: 1.4053440860980095e-06, Fisher S/N: 7406.869323299701\n",
-      "param: logA, sigma: 0.01855164505777501, Fisher S/N: 164.08248381855805\n",
-      "param: ombh2, sigma: 6.30669212421406e-05, Fisher S/N: 354.70258511767366\n",
-      "param: omch2, sigma: 0.0011026235986169512, Fisher S/N: 108.83133659620476\n",
-      "param: ns, sigma: 0.0031898296323270353, Fisher S/N: 302.4926441905579\n",
-      "param: tau, sigma: 0.010459712037500625, Fisher S/N: 5.20090799870615\n",
-      "param: a_tSZ, sigma: 0.06920457173257455, Fisher S/N: 47.68471095742208\n",
-      "param: a_kSZ, sigma: 0.14426113756334474, Fisher S/N: 11.09099808184615\n",
-      "param: a_p, sigma: 0.04943973006023647, Fisher S/N: 139.56386880739774\n",
-      "param: beta_p, sigma: 0.007950350536488635, Fisher S/N: 276.71735854953334\n",
-      "param: a_c, sigma: 0.12552552490040478, Fisher S/N: 39.035885361863954\n",
-      "param: beta_c, sigma: 0.02338641763845622, Fisher S/N: 94.07169725654596\n",
-      "param: a_s, sigma: 0.01111388203280301, Fisher S/N: 278.9304395035184\n",
-      "param: a_gtt, sigma: 0.21178590795462116, Fisher S/N: 13.220898534004203\n",
-      "param: a_gte, sigma: 0.014857196412751907, Fisher S/N: 6.730744968422856\n",
-      "param: a_gee, sigma: 0.0023950784545167104, Fisher S/N: 41.752285738872985\n",
-      "param: a_psee, sigma: 0.004542298460564408, Fisher S/N: 0.6604585819372231\n",
-      "param: a_pste, sigma: 0.0034694877635880386, Fisher S/N: 12.105533399133503\n",
-      "param: xi, sigma: 0.007469144085455909, Fisher S/N: 13.388414904824547\n"
+      "param: cosmomc_theta, sigma: 1.4053440860980404e-06, Fisher S/N: 7406.869323299538\n",
+      "param: logA, sigma: 0.018551645057774506, Fisher S/N: 164.08248381856248\n",
+      "param: ombh2, sigma: 6.306692124213734e-05, Fisher S/N: 354.7025851176921\n",
+      "param: omch2, sigma: 0.0011026235986169705, Fisher S/N: 108.83133659620286\n",
+      "param: ns, sigma: 0.003189829632327165, Fisher S/N: 302.4926441905456\n",
+      "param: tau, sigma: 0.010459712037500509, Fisher S/N: 5.2009079987062075\n",
+      "param: a_tSZ, sigma: 0.06920457173258697, Fisher S/N: 47.68471095741352\n",
+      "param: a_kSZ, sigma: 0.14426113756336395, Fisher S/N: 11.090998081844672\n",
+      "param: a_p, sigma: 0.049439730060229836, Fisher S/N: 139.56386880741644\n",
+      "param: beta_p, sigma: 0.00795035053648887, Fisher S/N: 276.7173585495251\n",
+      "param: a_c, sigma: 0.12552552490037042, Fisher S/N: 39.03588536187464\n",
+      "param: beta_c, sigma: 0.02338641763845552, Fisher S/N: 94.07169725654877\n",
+      "param: a_s, sigma: 0.011113882032803496, Fisher S/N: 278.9304395035062\n",
+      "param: a_gtt, sigma: 0.2117859079545539, Fisher S/N: 13.2208985340084\n",
+      "param: a_gte, sigma: 0.01485719641275419, Fisher S/N: 6.730744968421822\n",
+      "param: a_gee, sigma: 0.002395078454516678, Fisher S/N: 41.75228573887355\n",
+      "param: a_psee, sigma: 0.004542298460563816, Fisher S/N: 0.660458581937309\n",
+      "param: a_pste, sigma: 0.003469487763588105, Fisher S/N: 12.105533399133272\n",
+      "param: xi, sigma: 0.007469144085457632, Fisher S/N: 13.38841490482146\n"
      ]
     }
    ],
@@ -1156,7 +1268,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [
     {
@@ -1212,7 +1324,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [
     {
@@ -1249,7 +1361,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1281,7 +1393,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [
     {
@@ -1333,13 +1445,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "[mflike] Computing bandpass at first step, no shifts\n",
       "log-likelihood value = -3578.006563536072\n",
       "Χ² value = 3079.648922352865\n"
      ]
@@ -1361,9 +1474,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "mflike",
    "language": "python",
-   "name": "python3"
+   "name": "mflike"
   },
   "language_info": {
    "codemirror_mode": {
@@ -1375,7 +1488,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.8.15"
   },
   "org": null,
   "widgets": {