diff --git a/examples/triaxiality/delta_sigma_test.ipynb b/examples/triaxiality/delta_sigma_test.ipynb
index 8f5b64eaf..508aef896 100644
--- a/examples/triaxiality/delta_sigma_test.ipynb
+++ b/examples/triaxiality/delta_sigma_test.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 136,
+   "execution_count": 1,
    "id": "c176f9f7-534d-427d-b2e9-bf2661319118",
    "metadata": {},
    "outputs": [],
@@ -14,7 +14,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 137,
+   "execution_count": 2,
    "id": "c136f015-0e5d-4ae4-b22f-c0add048d9a0",
    "metadata": {},
    "outputs": [],
@@ -26,7 +26,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 138,
+   "execution_count": 3,
    "id": "6a05969e-2d03-4ff9-ada1-a82fef843623",
    "metadata": {},
    "outputs": [],
@@ -48,7 +48,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 139,
+   "execution_count": 4,
    "id": "01bb66e5-b622-4ad1-97f6-ed82e13355ec",
    "metadata": {},
    "outputs": [],
@@ -65,7 +65,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 140,
+   "execution_count": 5,
    "id": "65695a2d-30ea-42c0-93ea-8de8ba5cf000",
    "metadata": {},
    "outputs": [],
@@ -81,9 +81,6 @@
     "r_bins = np.linspace(0, np.max(r), num_bins+1)\n",
     "r_bins_mid = (r_bins[1:] + r_bins[:-1])/2\n",
     "\n",
-    "# print(np.shape(r_bins))\n",
-    "# print(np.shape(r_bins_mid))\n",
-    "\n",
     "r_inds = np.digitize(r, r_bins, right=True)\n",
     "def delta_sigma(weight_1_ij, weight_2_ij, gamma_1_ij, gamma_2_ij, theta_ij, sigma_crit_ij=sigma_crit):\n",
     "    # TODO: summation over i\n",
@@ -92,7 +89,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 141,
+   "execution_count": 6,
    "id": "bec47489-3f42-41fb-8237-5f403c862686",
    "metadata": {},
    "outputs": [],
@@ -110,12 +107,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 142,
+   "execution_count": 7,
    "id": "2e90dc70-3178-4bd7-92ed-e2da79ee91ca",
    "metadata": {},
    "outputs": [],
    "source": [
     "delta_sigmas = []\n",
+    "delta_sigma_consts = []\n",
+    "delta_sigma_crosses = []\n",
+    "delta_sigma_cross_consts = []\n",
     "for i in range(num_bins):\n",
     "    select = (r_inds-1) == i\n",
     "    theta_i = theta[select]\n",
@@ -124,13 +124,23 @@
     "    weight_i = weight_ij()\n",
     "    weight_1_i = weight_1_ij(theta_i)\n",
     "    weight_2_i = weight_2_ij(theta_i)\n",
+    "    \n",
     "    delta_sigma_i = delta_sigma(weight_1_i, weight_2_i, gamma_1_i, gamma_2_i, theta_i)\n",
-    "    delta_sigmas.append(np.mean(delta_sigma_i))"
+    "    delta_sigmas.append(np.mean(delta_sigma_i))\n",
+    "    \n",
+    "    delta_sigma_const_i = delta_sigma_const(w_ij, gamma_1_i)\n",
+    "    delta_sigma_consts.append(np.mean(delta_sigma_const_i))\n",
+    "    \n",
+    "    delta_sigma_cross_i = delta_sigma_cross(weight_1_i, weight_2_i, gamma_1_i, gamma_2_i, theta_i)\n",
+    "    delta_sigma_crosses.append(np.mean(delta_sigma_cross_i))\n",
+    "    \n",
+    "    delta_sigma_cross_i = delta_sigma_cross_const(w_ij, gamma_2_i)\n",
+    "    delta_sigma_cross_consts.append(np.mean(delta_sigma_cross_i))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 158,
+   "execution_count": 8,
    "id": "47299fb0-eb0d-49bf-9fe7-ba39b5b34d49",
    "metadata": {},
    "outputs": [
@@ -155,27 +165,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 144,
-   "id": "84b44e07-1975-4fe0-be25-88bfb0d6385d",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "delta_sigma_consts = []\n",
-    "for i in range(num_bins):\n",
-    "    select = (r_inds-1) == i\n",
-    "    theta_i = theta[select]\n",
-    "    gamma_1_i = gamma1[select]\n",
-    "    gamma_2_i = gamma2[select]\n",
-    "    weight_i = weight_ij()\n",
-    "    weight_1_i = weight_1_ij(theta_i)\n",
-    "    weight_2_i = weight_2_ij(theta_i)\n",
-    "    delta_sigma_const_i = delta_sigma_const(w_ij, gamma_1_i)\n",
-    "    delta_sigma_consts.append(np.mean(delta_sigma_const_i))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 151,
+   "execution_count": 9,
    "id": "b8b79c06-a93c-4543-9be2-ced9aaf3b43c",
    "metadata": {},
    "outputs": [
@@ -200,27 +190,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 146,
-   "id": "88616920-a344-4045-bf12-78981e5c3e47",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "delta_sigma_crosses = []\n",
-    "for i in range(num_bins):\n",
-    "    select = (r_inds-1) == i\n",
-    "    theta_i = theta[select]\n",
-    "    gamma_1_i = gamma1[select]\n",
-    "    gamma_2_i = gamma2[select]\n",
-    "    weight_i = weight_ij()\n",
-    "    weight_1_i = weight_1_ij(theta_i)\n",
-    "    weight_2_i = weight_2_ij(theta_i)\n",
-    "    delta_sigma_cross_i = delta_sigma_cross(weight_1_i, weight_2_i, gamma_1_i, gamma_2_i, theta_i)\n",
-    "    delta_sigma_crosses.append(np.mean(delta_sigma_cross_i))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 159,
+   "execution_count": 10,
    "id": "c977e706-e6d6-4f74-a3c1-20f9e0f041f5",
    "metadata": {},
    "outputs": [
@@ -245,27 +215,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 148,
-   "id": "2f4e8767-0b94-4caf-a717-b11a07131a27",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "delta_sigma_cross_consts = []\n",
-    "for i in range(num_bins):\n",
-    "    select = (r_inds-1) == i\n",
-    "    theta_i = theta[select]\n",
-    "    gamma_1_i = gamma1[select]\n",
-    "    gamma_2_i = gamma2[select]\n",
-    "    weight_i = weight_ij()\n",
-    "    weight_1_i = weight_1_ij(theta_i)\n",
-    "    weight_2_i = weight_2_ij(theta_i)\n",
-    "    delta_sigma_cross_i = delta_sigma_cross_const(w_ij, gamma_2_i)\n",
-    "    delta_sigma_cross_consts.append(np.mean(delta_sigma_cross_i))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 153,
+   "execution_count": 11,
    "id": "3a66e275-89f5-4b34-853c-50904f31ffb9",
    "metadata": {},
    "outputs": [
@@ -287,14 +237,6 @@
     "plt.title('Excess Surface Density (Cross Const) as a function of Radius')\n",
     "plt.show()"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "36ebf25d-2b80-4b95-b9a7-1693707cacb0",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {