### Install shapesimilarity from source

Source: https://pypi.org/project/shapesimilarity/1.0.0

Install the shapesimilarity package by cloning the source code repository and then installing it locally. This is useful for development or if you need the latest unreleased version.

```bash
$ git clone https://github.com/nelsonwenner/shape-similarity.git

$ python -m pip install .
```

--------------------------------

### Install shapesimilarity with pip

Source: https://pypi.org/project/shapesimilarity/1.0.0

Install the shapesimilarity package using pip. This is the recommended method for most users.

```bash
$ python -m pip install shapesimilarity
```

--------------------------------

### Run shapesimilarity tests

Source: https://pypi.org/project/shapesimilarity/1.0.0

Install pytest and run the package's tests to ensure it is functioning correctly after installation.

```bash
$ python -m pip install pytest

$ python -m pytest
```

--------------------------------

### Calculate Shape Similarity

Source: https://pypi.org/project/shapesimilarity

Calculate the similarity between two shapes using the shapesimilarity package. This example visualizes the shapes and their calculated similarity.

```python
from shapesimilarity import shape_similarity
import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(1, -1, num=200)

y1 = 2*x**2 + 1
y2 = 2*x**2 + 2

shape1 = np.column_stack((x, y1))
shape2 = np.column_stack((x, y2))

similarity = shape_similarity(shape1, shape2)

plt.plot(shape1[:,0], shape1[:,1], linewidth=2.0)
plt.plot(shape2[:,0], shape2[:,1], linewidth=2.0)

plt.title(f'Shape similarity is: {similarity}', fontsize=14, fontweight='bold')
plt.show()

```

--------------------------------

### Customize shape_similarity function

Source: https://pypi.org/project/shapesimilarity

Customize the shape_similarity function by adjusting rotation correction and accuracy. Increasing rotation increases accuracy but also computation time.

```python
# disable rotation correction entirely
shape_similarity(shape1, shape2, checkRotation=False)

# higher accuracy, but slower
shape_similarity(shape1, shape2, rotation=30)

```

--------------------------------

### Calculate and visualize shape similarity

Source: https://pypi.org/project/shapesimilarity/1.0.0

Calculate the similarity between two shapes defined as NumPy arrays and visualize them using Matplotlib. Ensure shapes are preprocessed and formatted correctly.

```python
from shapesimilarity import shape_similarity
import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(1, -1, num=200)

y1 = 2*x**2 + 1
y2 = 2*x**2 + 2

shape1 = np.column_stack((x, y1))
shape2 = np.column_stack((x, y2))

similarity = shape_similarity(shape1, shape2)

plt.plot(shape1[:,0], shape1[:,1], linewidth=2.0)
plt.plot(shape2[:,0], shape2[:,1], linewidth=2.0)

plt.title(f'Shape similarity is: {similarity}', fontsize=14, fontweight='bold')
plt.show()
```

--------------------------------

### Customize shape_similarity function parameters

Source: https://pypi.org/project/shapesimilarity/1.0.0

Adjust the precision and rotation correction of the shape_similarity function. Increasing the rotation parameter improves accuracy but increases computation time. Disabling checkRotation can be done for specific use cases.

```python
# disable rotation correction entirely
shape_similarity(shape1, shape2, checkRotation=False)

# higher accuracy, but slower
shape_similarity(shape1, shape2, rotation=30)
```

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