shivs-per-lib 1.1.1

A personal utility package by Shivsamb Harkare.

shivs_per_lib

A Python utility library developed by Shivsamb Harkare (COEP Technological University) for engineering, embedded systems, digital electronics, signal processing, control systems, AI/ML, and software development applications.

The goal of this library is to provide a collection of commonly used engineering calculations, signal processing utilities, machine learning helpers, and embedded-system tools in a single easy-to-use package.

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Installation

pip install shivs_per_lib

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Modules Overview

The library contains functions from the following domains:

• Digital Electronics
• DSP (Digital Signal Processing)
• Control Systems
• Embedded Systems
• AI & Machine Learning
• EDA (Exploratory Data Analysis)
• Software Development Utilities

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Digital Electronics

q_mc()

Implements the Quine-McCluskey Boolean minimization algorithm.

Purpose

Used to simplify Boolean expressions and minimize logic circuits.

Example

from shivs_per_lib import q_mc

q_mc()

The function asks for:

• Minterms
• Don't-care terms
• Number of variables

and outputs the simplified Boolean expression.

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binary_to_gray()

Converts a binary number into Gray code.

Example

binary_to_gray("1010")

Output:

1111

Applications

• Rotary encoders
• Digital communication
• Error reduction systems

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binary_to_decimal()

Converts binary to decimal.

binary_to_decimal("1010")

Output:

10

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decimal_to_binary()

Converts decimal to binary.

decimal_to_binary(10)

Output:

1010

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DSP Functions

fft_analysis()

Performs Fast Fourier Transform analysis.

Example

freq, magnitude = fft_analysis(signal, 1000)

Returns

• Frequency components
• FFT magnitude spectrum

Applications

• Vibration analysis
• Audio processing
• Biomedical signals
• IMU analysis

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butter_lowpass()

Applies Butterworth low-pass filtering.

Example

filtered = butter_lowpass(
    signal,
    cutoff=20,
    fs=100
)

Applications

• Sensor noise removal
• ECG filtering
• IMU preprocessing

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butter_highpass()

Applies Butterworth high-pass filtering.

Example

filtered = butter_highpass(
    signal,
    cutoff=1,
    fs=100
)

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moving_average()

Smooths signals using moving average filtering.

Example

moving_average(signal, window=5)

---

rms()

Computes Root Mean Square value.

Example

rms(signal)

Applications

• Power calculations
• Vibration analysis
• Signal energy estimation

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Control Systems

pid_control()

Implements PID control calculations.

Example

output, integral, error = pid_control(
    setpoint=100,
    measured=95,
    kp=1.2,
    ki=0.3,
    kd=0.1,
    integral=0,
    prev_error=0,
    dt=0.01
)

Applications

• Temperature control
• Motor speed control
• Process automation

---

first_order_response()

Calculates first-order system response.

first_order_response(
    K=1,
    tau=2,
    time=t
)

---

percent_overshoot()

Calculates percentage overshoot.

percent_overshoot(peak=120, final=100)

Output:

20

---

steady_state_error()

Computes steady-state error.

steady_state_error(
    reference=100,
    output=98
)

Output:

2

---

Embedded Systems

adc_to_voltage()

Converts ADC counts to voltage.

adc_to_voltage(
    adc_value=2048,
    resolution=12,
    vref=3.3
)

---

voltage_divider()

Calculates voltage divider output.

voltage_divider(
    vin=12,
    r1=1000,
    r2=1000
)

Output:

6V

---

ohms_law()

Solves Ohm's Law.

ohms_law(v=12, r=4)

Output:

3A

---

pwm_duty_cycle()

Calculates PWM duty cycle.

pwm_duty_cycle(
    on_time=2,
    period=10
)

Output:

20%

---

timer_frequency()

Calculates timer frequency.

timer_frequency(
    16000000,
    64
)

---

uart_tx_time()

Computes UART transmission time.

uart_tx_time(
    bytes_count=100,
    baudrate=9600
)

---

battery_runtime()

Estimates battery runtime.

battery_runtime(
    2000,
    500
)

Output:

4 Hours

---

crc8()

Computes CRC-8 checksum.

crc8([1,2,3,4])

Applications

• Communication protocols
• Error detection
• Embedded systems

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debounce()

Debounces noisy digital signals.

debounce(samples)

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byte_to_hex()

Converts byte to hexadecimal.

byte_to_hex(255)

Output:

0xff

---

hex_to_binary()

Converts hexadecimal to binary.

hex_to_binary("FF")

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swap_endian_16()

Swaps endianness of a 16-bit value.

swap_endian_16(0x1234)

Output:

0x3412

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AI & Machine Learning

normalize()

Performs Z-score normalization.

normalize(data)

---

minmax_normalize()

Performs Min-Max normalization.

minmax_normalize(data)

---

sliding_window()

Creates overlapping windows.

sliding_window(
    data,
    window_size=128,
    step=64
)

Applications

• Gait analysis
• HAR systems
• Time-series ML

---

quaternion_magnitude()

Computes quaternion magnitude.

quaternion_magnitude(
    w,x,y,z
)

---

train_test_split()

Randomly splits data.

train_test_split(
    data,
    test_size=0.2
)

---

accuracy_score()

Computes classification accuracy.

accuracy_score(
    y_true,
    y_pred
)

---

mae()

Computes Mean Absolute Error.

mae(
    y_true,
    y_pred
)

---

confusion_matrix()

Creates confusion matrix metrics.

confusion_matrix(
    y_true,
    y_pred
)

Returns:

{
    "TP": ...,
    "TN": ...,
    "FP": ...,
    "FN": ...
}

---

missing_percentage()

Computes percentage of missing values.

missing_percentage(data)

---

outliers_iqr()

Detects outliers using IQR.

outliers_iqr(data)

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Exploratory Data Analysis

eda_plot()

Universal plotting function.

Supported Plots

• hist
• box
• scatter
• line
• bar

Example

eda_plot(
    df,
    plot_type="scatter",
    col1="Height",
    col2="Weight"
)

---

data_overview()

Provides a quick dataset summary.

data_overview(df)

Returns:

{
    "rows": ...,
    "columns": ...,
    "missing_values": ...,
    "duplicates": ...
}

---

quick_report()

Prints a quick EDA report.

quick_report(df)

Displays:

• Rows
• Columns
• Missing values
• Duplicates
• Column names

---

Software Development Utilities

password_strength()

Evaluates password strength.

password_strength(
    "MyPassword123!"
)

Returns a score from 0 to 4.

---

validate_email()

Validates email format.

validate_email(
    "[e-mail]"
)

Returns:

True

---

timer()

Function execution timer decorator.

@timer
def my_function():
    pass

Output:

my_function took 0.1234 sec

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Developed By

Shivsamb Harkare B.Tech Instrumentation & Control Engineering COEP Technological University

Focused on:

• Embedded Systems
• Artificial Intelligence & Machine Learning
• Signal Processing
• Control Systems
• Healthcare Technology
• Gait Analysis & Human Activity Recognition

If you find this package useful, feel free to contribute and suggest new engineering utilities.