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[DOCS-1930] Fix incorrect detail about line plot primary lines #2317

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mdlinville merged 2 commits into from
Mar 19, 2026
Merged

[DOCS-1930] Fix incorrect detail about line plot primary lines #2317

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[DOCS-1930] Fix incorrect detail about line plot primary lines
mdlinville Mar 18, 2026
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Merge branch 'main' into DOCS-1930
mdlinville Mar 19, 2026
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2 changes: 1 addition & 1 deletion models/app/features/panels/line-plot/sampling.mdx
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Expand Up @@ -8,7 +8,7 @@ Use point aggregation methods within your line plots for improved data visualiza

## Full fidelity

When you use full fidelity mode, W&B breaks the x-axis into dynamic buckets. The number of points per line adapts to chart size and the number of runs. It calculates the minimum and maximum values within each bucket (used for optional shading) and uses the last value in each bucket to draw the line.
When you use full fidelity mode, W&B breaks the x-axis into dynamic buckets. The number of points per line adapts to chart size and the number of runs. It calculates the minimum and maximum values within each bucket (used for optional shading) and uses the last value in each bucket (not the average) to draw the primary line.

There are three main advantages to using full fidelity mode for point aggregation:

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2 changes: 1 addition & 1 deletion release-notes/server-releases-archived.mdx
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Expand Up @@ -148,7 +148,7 @@ Due to a release versioning issue, 0.56.0 is the next major release after 0.54.0

## Features

* The new Full Fidelity line plot in W&B Experiments enhances the visibility of training metrics by aggregating all data along the x-axis, displaying the minimum, maximum, and average values within each bucket, allowing users to easily spot outliers and zoom into high-fidelity details without downsampling loss. [Learn more in our documentation](https://docs.wandb.ai/models/app/features/panels/line-plot/sampling).
* The new Full Fidelity line plot in W&B Experiments enhances the visibility of training metrics by aggregating all data along the x-axis, displaying the minimum, maximum, and last value within each bucket (the last value draws the primary line), allowing users to easily spot outliers and zoom into high-fidelity details without downsampling loss. [Learn more in our documentation](https://docs.wandb.ai/models/app/features/panels/line-plot/sampling).
* You can now use [cross-cloud storage buckets for team-level BYOB (secure storage connector)](https://docs.wandb.ai/platform/hosting/data-security/secure-storage-connector#cross-cloud-or-s3-compatible-storage-for-team-level-byob) in Dedicated Cloud and Self-Managed instances. For example, in a W&B instance on AWS, you can now configure Azure Blob Storage or Google Cloud Storage for team-level BYOB, and so on for each cross-cloud combination.
* In the same vein, you can now use [S3-compatible storage buckets like MinIO for team-level BYOB (secure storage connector)](https://docs.wandb.ai/platform/hosting/data-security/secure-storage-connector#cross-cloud-or-s3-compatible-storage-for-team-level-byob) in Dedicated Cloud and Self-Managed instances. For example, in a W&B instance on Google Cloud, you can configure a MinIO bucket hosted in cloud or on-prem for team-level BYOB.
* Admins can now automate full deletion of users in their Dedicated Cloud or Self-Managed instances using the [SCIM API's DELETE User endpoint](https://docs.wandb.ai/platform/hosting/iam/scim#delete-user). The user deactivation operation has been reimplemented using the [PATCH User endpoint](https://docs.wandb.ai/platform/hosting/iam/scim#deactivate-user), along with the introduction of [user reactivation operation](https://docs.wandb.ai/platform/hosting/iam/scim#reactivate-user).
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