Vyom Sutra

A wave-based decision engine.

Takes a value and a target. Returns a similarity score.

Install

pip install vyom-sutra

Use

import vyom_sutra as vyom

r = vyom.score(value, target=1.2566, scale=1.0) print(r['score']) # 0 - 100 print(r['verdict']) # "Clean" or "Noise"

Output

score > 95 excellent score > 80 clean score > 50 weak score < 50 noise

Works with FFT

FFT splits a signal into frequencies. Vyom scores each frequency. Keep the clean ones. Drop the noise.

import numpy as np import vyom_sutra as vyom

spectrum = np.fft.fft(signal)

for freq in spectrum: r = vyom.score(freq, target=1.2566) if r['clean']: print("keep", freq)

Example 1: Medicine

Screening a drug compound.

Each compound has a weight (MW) and an oiliness (LogP). These two numbers give a phase angle. That angle is compared with the target protein angle.

import vyom_sutra as vyom

mw = 463.9 logp = 2.8 target = 1.2566

phase = (mw / 500) * 1.1 + (logp / 5) * 0.5 r = vyom.score(phase, target=target)

if r['clean']: print("candidate") else: print("reject")

Use case: filter a million compounds down to a short list for the lab. Save months of time.

Example 2: Cosmology

Testing a universe model against observed data.

For each scale k, the model predicts a value n_s. Compare with the measured value from Planck 2018.

import vyom_sutra as vyom

measured_ns = 0.9649

for k in [5, 8, 12, 16]: model_ns = 1 - 2/60 + 0.0012 * (k - 5) r = vyom.score(model_ns, target=measured_ns, scale=1.0) print("k =", k, "score =", r['score'])

Use case: check how close a model is to real data.

Example 3: Earthquake detection

A seismometer records ground motion. Earthquake waves have a known shape (target).

1. Read the sensor signal.
2. FFT gives the frequencies.
3. Vyom scores each frequency.
4. Frequencies near target = earthquake.

import numpy as np import vyom_sutra as vyom

signal = read_seismometer() spectrum = np.fft.fft(signal)

eq_target = 2.0 hits = 0

for freq in spectrum: r = vyom.score(freq, target=eq_target, scale=1.0) if r['clean']: hits += 1

if hits > 10: print("earthquake detected") else: print("no earthquake")

Use case: separate a real quake from traffic noise, wind, or a passing truck.

Other sectors

The same function works anywhere a decision is needed.

audio denoise (FFT + Vyom) image compression (DCT + Vyom) game NPC (id -> behavior) finance signal (price -> buy or sell) music note (freq -> in tune or not) terrain height (x, y -> noise filter)

Same one function.

Dynamic scale

scale = 0.5 coarse scale = 1.0 normal scale = 5.0 fine scale = 25.0 very fine

Any value works.

Batch

values = [i * 0.001 for i in range(1000000)] results = vyom.score_batch(values, target=1.2566)

License

MIT