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Data Explorer

The Data Explorer is an interactive tool for browsing, filtering, and analyzing experiment outputs. It supports MCMC chains, survey catalogs, anomaly tables, and any tabular data your experiments produce.

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Features

Sortable Tables

Click any column header to sort. Shift-click for multi-column sort. Filter rows by value ranges or text search.

Column Statistics

Select a column to see mean, median, std, min, max, and a histogram. Useful for quick parameter checks.

Equation Calculators

Built-in calculators for common derived quantities: Hubble tension, sigma distances, Bayes factors, and more.

Node Tree

Visualize experiment dependencies and data flow as an interactive node graph.

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Supported Data Formats

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Embedding Datasets

When an experiment completes, its output datasets are automatically available in the Data Explorer. You can also embed datasets manually:

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Column Offset Warning

MCMC chain files with a # header row have a column offset of +1. The header row starts with # which shifts indices. For example, H0 at header position 22 is at data position 21. The Data Explorer handles this automatically.

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Equation Calculators

The Data Explorer includes six built-in calculators:
  1. Hubble Tension, Compute sigma tension between two H0 measurements
  2. Bayes Factor, Compare model evidence from MCMC chains
  3. Convergence (R-hat), Gelman-Rubin diagnostic from multiple chains
  4. Effective Samples, Compute N_eff from autocorrelation
  5. Sigma Distance, How many sigma between a measurement and prediction
  6. Delta Chi-Squared, Model comparison via chi-squared difference
Filters apply in real time and update the column statistics panel.

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Export

Export filtered data in multiple formats:

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API

Returns JSON with rows, column metadata, and summary statistics.

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Visualization

The Data Explorer includes basic plotting capabilities:
  • Scatter plots, Select two columns for x/y axes
  • Histograms, Single-column distribution
  • Corner plots, Multi-parameter posterior visualization (for MCMC data)
  • Time series, For data with timestamp columns
For publication-quality figures, use the Figure generation tools in the paper pipeline instead.