Examples

Overview

Practical examples demonstrating MD Utils’ most powerful features for interactive visualization and statistical analysis.

⭐ Featured Examples

HTML Grid Dashboards

Create multi-figure HTML dashboards with grid and tabbed layouts. Perfect for comprehensive analysis reports and sharing interactive visualizations.

Key functions: create_plotly_grid_html, create_tabbed_plotly_grid_html

Add statistical significance indicators and model fits to plots: - Cluster-based permutation tests for time series - Automatic box plot significance indicators - Regression fits with confidence intervals

Key functions: add_cluster_permut_sig_to_plotly, add_box_significance_indicator, add_statsmodel_fit

Multi-line Plots & Metadata

Create publication-ready multi-line plots with: - Individual traces + mean ± CI/SD - Automatic significance testing - Metadata annotations for reproducibility

Key functions: multiline_plot, add_meta_info

MNE Plotting

Interactive EEG/MEG visualization with topographic maps and evoked responses: - Spatial distribution visualization with smooth interpolation - Event-related potential plots with confidence intervals - Time-locked topoplots showing activity at specific time points - Automatic channel positioning from MNE info - Customizable colorscales and styling

Key functions: plot_evoked, create_plotly_topoplot

MNE to DataFrame Conversion

Convert MNE Raw and Epochs objects to Polars DataFrames for flexible data analysis: - Transform continuous EEG/MEG recordings to long-format DataFrames - Automatic metadata integration from epochs - Analyze neural data with modern DataFrame operations - Export to CSV, Parquet, or use with other analysis tools

Key functions: mne_raw_to_polars, mne_epochs_to_polars

Additional Examples

Time Series Plotting

Learn how to create interactive time series visualizations with support for large datasets.

Statistical Analysis

Examples of statistical plotting and significance testing.

Example from Repository

The examples/ folder contains runnable Python scripts:

resampler_example.py - Demonstrates plotly-resampler integration

Running Examples

Clone the repository and run examples:

git clone https://github.com/matthiasdold/mdu.git
cd mdu
pip install -e ".[all]"
python examples/resampler_example.py

Jupyter Notebooks

You can also run examples in Jupyter:

pip install jupyter
jupyter notebook

Then create a new notebook and import:

import mdu
from mdu.plotly import html_grids, stats, multiline, shared

--- title: "Examples" --- ## Overview Practical examples demonstrating MD Utils' most powerful features for interactive visualization and statistical analysis. ## ⭐ Featured Examples ### [HTML Grid Dashboards](html_grids.qmd) Create multi-figure HTML dashboards with grid and tabbed layouts. Perfect for comprehensive analysis reports and sharing interactive visualizations. **Key functions**: `create_plotly_grid_html`, `create_tabbed_plotly_grid_html` ### [Advanced Statistical Testing](advanced_statistics.qmd) Add statistical significance indicators and model fits to plots: - Cluster-based permutation tests for time series - Automatic box plot significance indicators - Regression fits with confidence intervals **Key functions**: `add_cluster_permut_sig_to_plotly`, `add_box_significance_indicator`, `add_statsmodel_fit` ### [Multi-line Plots & Metadata](multiline_enhanced.qmd) Create publication-ready multi-line plots with: - Individual traces + mean ± CI/SD - Automatic significance testing - Metadata annotations for reproducibility **Key functions**: `multiline_plot`, `add_meta_info` ### [MNE Plotting](mne_plotting.qmd) Interactive EEG/MEG visualization with topographic maps and evoked responses: - Spatial distribution visualization with smooth interpolation - Event-related potential plots with confidence intervals - Time-locked topoplots showing activity at specific time points - Automatic channel positioning from MNE info - Customizable colorscales and styling **Key functions**: `plot_evoked`, `create_plotly_topoplot` ### [MNE to DataFrame Conversion](mne_dataframe.qmd) Convert MNE Raw and Epochs objects to Polars DataFrames for flexible data analysis: - Transform continuous EEG/MEG recordings to long-format DataFrames - Automatic metadata integration from epochs - Analyze neural data with modern DataFrame operations - Export to CSV, Parquet, or use with other analysis tools **Key functions**: `mne_raw_to_polars`, `mne_epochs_to_polars` ## Additional Examples ### [Time Series Plotting](time_series.qmd) Learn how to create interactive time series visualizations with support for large datasets. ### [Statistical Analysis](statistical.qmd) Examples of statistical plotting and significance testing. ## Example from Repository The `examples/` folder contains runnable Python scripts: - `resampler_example.py` - Demonstrates plotly-resampler integration ## Running Examples Clone the repository and run examples: ```bash git clone https://github.com/matthiasdold/mdu.git cd mdu pip install -e ".[all]" python examples/resampler_example.py ``` ## Jupyter Notebooks You can also run examples in Jupyter: ```bash pip install jupyter jupyter notebook ``` Then create a new notebook and import: ```python import mdu from mdu.plotly import html_grids, stats, multiline, shared ```