haniwers.postprocess

haniwers.postprocess#

Data Visualization and Analysis Plots for Cosmic Ray Data.

This module creates interactive and static visualizations of cosmic ray event data, environmental measurements, and analysis results. It helps researchers understand patterns and trends in the detector measurements.

What Does This Module Do?

The postprocessing module:

  1. Generates plots of event rates over time

  2. Shows environmental conditions (temperature, pressure, humidity)

  3. Creates overlaid visualizations for multi-variable analysis

  4. Produces S-curves for threshold analysis

  5. Generates statistical summaries and reports

Visualization Types

  • Event Rate Plots: Shows cosmic ray detection frequency vs time

  • Environmental Plots: Temperature, pressure, humidity trends

  • Overlay Plots: Multiple variables on shared or separate axes

  • S-Curves: Threshold scan analysis with error functions

  • Statistical Summary: Histograms, distributions, and statistics

Key Functions

event_rate() : Create event rate vs time visualization environmental_data() : Plot temperature, pressure, humidity overlay_plots() : Combine multiple datasets on one chart threshold_curve() : Visualize S-curve fitting results

Libraries Used

This module uses Altair for interactive visualizations. Charts can be:

  • Displayed in Jupyter notebooks

  • Saved to HTML files

  • Exported as images (PNG, SVG)

Example Usage

import pandas as pd
from haniwers.postprocess import event_rate

data = pd.read_csv("processed_data.csv")
chart = event_rate(data)
chart.show()  # Display in browser or notebook
chart.save("event_rate.html")  # Save as HTML

Note

This module is under active development. More visualization types and analysis tools will be added in future versions.

Module Contents#

Functions#

event_rate

API#

haniwers.postprocess.event_rate(data: pandas.DataFrame)#
目次