# measurepy

A python module to boost first-step data analysis after measurements.

## Problem and Motivation

It is very complicated and tedious to deal with data in my physics lab course. Hence, I develop such a package to boost the process. After the first-step analysis, you can turn to complicated and advanced tools or just finish the report if the experiment is simple.

## Features

- Directly get the value and error with multi-measurements.
- Simple linear regession (based on scipy now).
- Simple plotting with just a parameter to choose the style.
- Plus, minus, multiply, divide with errors.

## Installation

The package has not been published to `pip`

although I aim to do so. Currently, you can install it by running

```
git clone https://github.com/JasonQSY/measurepy && cd measurepy
pip3 install .
```

## Usage

For the multimeasure feature,

```
import numpy as np
from measurepy.multimeasure import *
A = np.array([1, 2, 3, 4, 5])
mean, delta_a, error = cal_error(A, 0.01)
print(mean)
print(delta_a)
print(error)
```

For linear regression,

```
import numpy as np
from measurepy.regression import *
x = np.array([1, 2, 3, 4, 5])
y = np.array(x**2 + 1)
slope, intercept, slope_err, intercept_err, rsquare = lineareg(x, y)
```