From 0260eedde20efc6980fc499869638c6f5059c6f8 Mon Sep 17 00:00:00 2001
From: wcroberson <79020086+wcroberson@users.noreply.github.com>
Date: Fri, 1 Mar 2024 10:48:51 -0700
Subject: [PATCH] Add to Modifying Priors tutorial
Added an extra block to the Modifying Priors tutorial notebook, which explains that the system should always be instantiated and modified directly when modifying priors, rather than modifying the sampler or driver object.
---
docs/tutorials/Modifying_Priors.ipynb | 1763 ++++++++++++++++++++++++-
1 file changed, 1720 insertions(+), 43 deletions(-)
diff --git a/docs/tutorials/Modifying_Priors.ipynb b/docs/tutorials/Modifying_Priors.ipynb
index ed8acb3e..e7f8e41a 100644
--- a/docs/tutorials/Modifying_Priors.ipynb
+++ b/docs/tutorials/Modifying_Priors.ipynb
@@ -22,7 +22,7 @@
},
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
@@ -43,22 +43,22 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 21,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- " epoch object quant1 quant1_err ... quant12_corr quant_type instrument\n",
- "-------------- ------ ------ ---------- ... ------------ ---------- ----------\n",
- " 55645.95 1 2479.0 16.0 ... nan seppa defsp\n",
- " 55702.89 1 2483.0 8.0 ... nan seppa defsp\n",
- " 55785.015 1 2481.0 33.0 ... nan seppa defsp\n",
- " 55787.935 1 2448.0 24.0 ... nan seppa defsp\n",
- "55985.19400184 1 2483.0 15.0 ... nan seppa defsp\n",
- "56029.11400323 1 2487.0 8.0 ... nan seppa defsp\n",
- "56072.30200459 1 2499.0 26.0 ... nan seppa defsp\n"
+ " epoch object quant1 quant1_err quant2 quant2_err quant12_corr quant_type instrument\n",
+ "-------------- ------ ------ ---------- ------ ---------- ------------ ---------- ----------\n",
+ " 55645.95 1 2479.0 16.0 327.94 0.39 nan seppa defsp\n",
+ " 55702.89 1 2483.0 8.0 327.45 0.19 nan seppa defsp\n",
+ " 55785.015 1 2481.0 33.0 326.84 0.94 nan seppa defsp\n",
+ " 55787.935 1 2448.0 24.0 325.82 0.66 nan seppa defsp\n",
+ "55985.19400184 1 2483.0 15.0 326.46 0.36 nan seppa defsp\n",
+ "56029.11400323 1 2487.0 8.0 326.54 0.18 nan seppa defsp\n",
+ "56072.30200459 1 2499.0 26.0 326.14 0.61 nan seppa defsp\n"
]
}
],
@@ -79,7 +79,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
@@ -111,7 +111,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 23,
"metadata": {},
"outputs": [
{
@@ -144,7 +144,7 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 24,
"metadata": {},
"outputs": [
{
@@ -177,7 +177,7 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 32,
"metadata": {},
"outputs": [
{
@@ -211,7 +211,7 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 8,
"metadata": {},
"outputs": [
{
@@ -266,7 +266,851 @@
{
"data": {
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",
- "image/svg+xml": "\n\n\n\n",
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n",
+ "\n"
+ ],
"text/plain": [
""
]
@@ -279,7 +1123,849 @@
{
"data": {
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",
- "image/svg+xml": "\n\n\n\n",
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n",
+ "\n"
+ ],
"text/plain": [
""
]
@@ -318,7 +2004,7 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 33,
"metadata": {},
"outputs": [
{
@@ -327,21 +2013,7 @@
"text": [
"Starting Burn in\n",
"\n",
- "Burn in complete. Sampling posterior now.\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "/home/sblunt/Projects/orbitize/orbitize/priors.py:354: RuntimeWarning: invalid value encountered in log\n",
- " lnprob = -np.log((element_array*normalizer))\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
+ "Burn in complete. Sampling posterior now.\n",
"10/10 steps completed\n",
"Run complete\n"
]
@@ -352,21 +2024,18 @@
"Text(0, 0.5, 'number of orbits')"
]
},
- "execution_count": 9,
+ "execution_count": 33,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
- "image/png": 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",
"text/plain": [
- ""
+ ""
]
},
- "metadata": {
- "needs_background": "light"
- },
+ "metadata": {},
"output_type": "display_data"
}
],
@@ -389,6 +2058,13 @@
"plt.hist(accepted_eccentricities)\n",
"plt.xlabel('ecc'); plt.ylabel('number of orbits')"
]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The MCMC sampler will automatically take the priors from the system used to instantiate it. However, updates to the system priors made after the sampler instantiation will not be propogated to the sampler, and thus will not be used when running MCMC. The recommended practice when modifying priors is to first instantiate and modify system priors, then instantiate the sampler. When modifying priors we also recommend instantiating the system and sampler objects individually, rather than instantiating a driver object."
+ ]
}
],
"metadata": {
@@ -396,7 +2072,8 @@
"hash": "e899b22145868d3cd465733d82c36c2ae3ac0d3591d6a0807ec2e5e577a9cf5c"
},
"kernelspec": {
- "display_name": "Python 3.7.5 64-bit ('python3.7': conda)",
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
"name": "python3"
},
"language_info": {
@@ -409,7 +2086,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.7.5"
+ "version": "3.11.5"
}
},
"nbformat": 4,