bmb-compute — Numeric Computation
Math, statistics, random numbers, and vector operations compiled from BMB.
Installation
pip install bmb-compute
Quick Start
import bmb_compute
# Math
bmb_compute.sqrt(144) # 12
bmb_compute.factorial(10) # 3628800
bmb_compute.ipow(2, 20) # 1048576
bmb_compute.clamp(15, 1, 10) # 10
# Statistics
bmb_compute.sum([10, 20, 30]) # 60
bmb_compute.mean_scaled([10, 20, 30]) # 20000 (= 20.000)
bmb_compute.min_val([5, 3, 8, 1]) # 1
bmb_compute.range_val([10, 50]) # 40
# Vector
bmb_compute.dot_product([1, 2, 3], [4, 5, 6]) # 32
bmb_compute.dist_squared([0, 0], [3, 4]) # 25
# Utility
bmb_compute.is_power_of_two(8) # True
bmb_compute.next_power_of_two(5) # 8
Full API (33 functions)
Math
| Function | Description |
|---|---|
abs(x) |
Absolute value |
min(a, b) / max(a, b) |
Minimum / maximum |
clamp(x, lo, hi) |
Clamp to range |
sign(x) |
Sign (-1, 0, 1) |
ipow(base, exp) |
Integer power |
sqrt(n) |
Integer square root |
factorial(n) |
Factorial (up to 20!) |
Statistics
| Function | Description |
|---|---|
sum(arr) |
Sum of elements |
mean_scaled(arr) |
Mean x 1000 |
min_val(arr) / max_val(arr) |
Min/max of array |
range_val(arr) |
Range (max - min) |
variance_scaled(arr) |
Variance x 1000000 |
median_scaled(arr) |
Median x 1000 (sorted input) |
cumsum(arr) |
Cumulative sum |
moving_avg_scaled(arr, k) |
Moving average x 1000 |
Random (XorShift64*)
| Function | Description |
|---|---|
rand_seed(seed) |
Initialize PRNG |
rand_next(state) |
Next state |
rand_pos(state) |
Positive random value |
rand_range(state, max) |
Random in [0, max) |
Vector
| Function | Description |
|---|---|
dot_product(a, b) |
Dot product |
dist_squared(a, b) |
Euclidean distance squared |
weighted_sum(values, weights) |
Weighted sum |
lerp_scaled(a, b, t) |
Linear interpolation (t: 0-1000) |
magnitude_squared(arr) |
Sum of squares |
vec_add(a, b) |
Element-wise addition |
vec_sub(a, b) |
Element-wise subtraction |
vec_scale(arr, scalar) |
Scalar multiplication |
map_square(arr) |
Square each element |
Utility
| Function | Description |
|---|---|
is_power_of_two(n) |
Power of two check |
next_power_of_two(n) |
Next power of two >= n |
How?
Written in BMB — compile-time contracts prove correctness, then generate code faster than hand-tuned C.
License
MIT
1 maintainer
Release files for bmb-compute 0.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| bmb_compute-0.2.0-py3-none-win_amd64.whl | Python 3 | none | Windows x86-64 | Details |
| bmb_compute-0.2.0-py3-none-manylinux_2_17_x86_64.whl | Python 3 | none | Linux glibc 2.17+ x86-64 | Details |
| bmb_compute-0.2.0-py3-none-macosx_15_0_universal2.whl | Python 3 | none | macOS 15.0+ universal2 (ARM64, x86-64) | Details |
Total release size: 204.7 kB
Release files / bmb_compute-0.2.0-py3-none-win_amd64.whl
| Download URL | bmb_compute-0.2.0-py3-none-win_amd64.whl |
|---|---|
| Size | 87.9 kB |
| Tags | Python 3 Windows x86-64 |
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Release files / bmb_compute-0.2.0-py3-none-manylinux_2_17_x86_64.whl
| Download URL | bmb_compute-0.2.0-py3-none-manylinux_2_17_x86_64.whl |
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| Size | 68.4 kB |
| Tags | Linux glibc 2.17+ x86-64 Python 3 |
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Release files / bmb_compute-0.2.0-py3-none-macosx_15_0_universal2.whl
| Download URL | bmb_compute-0.2.0-py3-none-macosx_15_0_universal2.whl |
|---|---|
| Size | 48.4 kB |
| Tags | Python 3 macOS 15.0+ universal2 (ARM64, x86-64) |
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