> ## Documentation Index
> Fetch the complete documentation index at: https://docs.quadrillion.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Matplotlib Settings

> Configure default plot appearance, colors, and export options.

Fine-grained control over how plots look. Changes apply to all new plots in your notebooks.

These are only the defaults for matplotlib. These can be overridden by simply passing arguments into matplotlib plotting calls.

## Display settings

| Setting         | Description                      |
| --------------- | -------------------------------- |
| **Display DPI** | Resolution for inline plots      |
| **Figure size** | Width and height in inches       |
| **Font family** | Typeface for labels and titles   |
| **Font size**   | Base size for plot text          |
| **Line width**  | Default thickness for plot lines |
| **Show grid**   | Display gridlines on plots       |

## Color settings

| Setting                 | Description                                 |
| ----------------------- | ------------------------------------------- |
| **Default color cycle** | Colors used for multiple data series        |
| **Default colormap**    | Gradient for heatmaps and continuous scales |

Qualia includes several built-in color cycles including its own palette. You can also create custom color schemes.

### Creating custom color cycles

1. Go to **Settings > Matplotlib**
2. Click **Create Custom** under color cycles
3. Add colors using hex codes or a color picker
4. Name and save your palette

Custom palettes appear in the dropdown alongside built-in options.

## Export settings

| Setting         | Description                     |
| --------------- | ------------------------------- |
| **Save DPI**    | Resolution for exported figures |
| **Save format** | PNG, PDF, SVG, or JPG           |

These affect figures saved with `plt.savefig()` or the export button on plot outputs.

## Applying changes

Settings take effect for new plots. Existing plots in your notebook retain their original styling until you re-run the cells.

To apply new settings to existing plots:

1. Update your Matplotlib settings
2. Re-run the cells that generate plots