From 586ddb7b1ecc47de8826033c995c6a9d7199327d Mon Sep 17 00:00:00 2001
From: Yiyu Ni <niyiyu@uw.edu>
Date: Tue, 20 Feb 2024 16:40:36 -0800
Subject: [PATCH] Update noise_configuration.md

---
 tutorials/noise_configuration.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tutorials/noise_configuration.md b/tutorials/noise_configuration.md
index 3c0e3b85..b49126bc 100644
--- a/tutorials/noise_configuration.md
+++ b/tutorials/noise_configuration.md
@@ -18,7 +18,6 @@ We gratefully acknowledge support from the [Packard Foundation](https://www.pack
 
 ## NoisePy Workflow
 
-<img src="./docs_old/figures/data_flow.png">
 The data processing in NoisePy consists of three steps:
 
 1. **(Optional) Step 0 - Download**: The `download()` function or the `noisepy download` CLI command can be used to download data from an FDSN web service. Alternatively, data from an [S3 bucket](https://s3.console.aws.amazon.com/s3/buckets/scedc-pds) can be copied locally using the `aws` CLI, or streamed directly from S3. for users who want to work entirely locally, this step prepares and organize the data in a ``DataStore``.
@@ -34,6 +33,7 @@ NoisePy accesses data through 3 "DataStore" abstract classes: `DataStore`, `Cros
 2. Stacking: Data is aggregated and stacked over all time periods. Stacked data will be stored in ``StackStore``.
 
 Workflow is described in the figure below.
+
 <img src="../docs_old/figures/data_flow.png">
 
 ## Applications