test visualization

๐Ÿ“ˆ Waveform Burst Trimmer & Visualizer

This toolkit trims long IDLE regions from waveform data, highlights bursty DATA blocks, and visualizes both original and trimmed signals using a minimal delta threshold model.

Quick Start

# Frame detection and word extraction python waveframe.py --in smi_ray.txt --margin 2 --out-trimmed smi_ray_trimmed.csv # Delta post-processing (threshold, cap, flags) python deltas_tool.py --in smi_ray_trimmed.csv --no-header --threshold 10000 --out smi_ray_deltas.txt --cap

Available Scripts

ScriptPurpose
waveframe.pyFrame detection, idle/payload classification, word extraction
plot_bursty_edges.pyBurst detection, gap analysis, visualization
deltas_tool.pyDelta extraction and post-processing (threshold, cap, flags)
trim_deltas.pyInterval-based waveform trimming
identify_gaps.pyFind values above/below thresholds

๐Ÿงน Trim Waveform File Using Interval Blocks

Use plot_bursty_edges.py to identify unwanted regions and create a CSV report for trim_deltas.py:

# Step 1: Identify burst blocks python plot_bursty_edges.py --input smi_ubs.txt --mode waveform --summary-txt smi_gaps.txt --blocks-output blocks.csv # Step 2: Trim using the blocks CSV python trim_deltas.py smi_ubs.txt --output smi_ubs_trimmed.txt --from-csv blocks.csv

Trimming Options

Trim using CSV (from burstmap or waveform mode):

python trim_deltas.py waveform.txt --from-csv blocks.csv

Invert behavior (remove lines IN the CSV):

python trim_deltas.py waveform.txt --from-csv blocks.csv --invert

Manual trimming (without CSV):

python trim_deltas.py waveform.txt --pairs 1000 2000 5000 5100

This removes lines 1000โ€“2000 and 5000โ€“5100.


๐Ÿ“Š Delta Post-Processing

deltas_tool.py provides flexible delta column extraction:

# Extract deltas with threshold flagging python deltas_tool.py --in annotated.csv --out deltas.txt --threshold 10000 --with-flags # Cap values above threshold python deltas_tool.py --in annotated.csv --out deltas.txt --threshold 10000 --cap # Handle zero-deltas python deltas_tool.py --in annotated.csv --out deltas.txt --drop-zero --zero-report zeros.csv

๐Ÿ” Gap Analysis

Find lines where values exceed thresholds:

python identify_gaps.py waveform.txt --gt 5000 # Values > 5000 python identify_gaps.py waveform.txt --lt 100 # Values < 100 python identify_gaps.py waveform.txt --gt 5000 --lt 100 # Both conditions

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