Plot functions with simple syntax

## Project description

A thin wrapper for matplotlib

Fplot’s goal is to provide simple syntax for plotting functions, with sensible defaults. Matplotlib is powerful, but has awkward syntax, odd default display settings, and requires setting up data arrays manually. Making pretty function plots requires multiple lines of code. Fplot aims to fix this; it’s especially suited for visualizing functions when learning math.

Python 3 only.

## Included functions

• plot: One input, one output.
• parametric: One input, two or three outputs. If three, use a 3d graph.
• contour: Two inputs, one output.
• surface: Two inputs, one output.
• vector: Two inputs, two outputs.
• vector3d: Three inputs, three outputs.
• polar: One input (angle), one output (radius)

## Bonus functions

• plot2: Smoothed API for matplotlib 2d plotting that works properly in Jupyter notebooks. ie syntax like plt.plot, which doesn’t work properly in Jupyter. Arguments: (args, marker=’b-‘, linewidth: float=2.0, grid: bool=False, color: str=None, title: str=None, equal_aspect: bool=False, style: str=None, show: bool=True)
• imshow: Like plot2, but as a replacement for plt.imshow.

## Installation

```pip install fplot
```

## Basic documentation

Examples

The only required arguments for fplot funcs are the function to plot, and the min and max ranges. Example optional keyword arguments are shown. Example output is shown in the link above.

For most plotting functions, you can plot multiple functions at once by passing a list or tuple as the first argument.

Show a graph (1 input, 1 output)

```f = lambda x: x**2 + 2
fplot.plot(f, -10, 10, title='Hello world')
```

Show a contour plot (2 inputs, 1 output)

```g = lambda x, y: x**2 + y**2 + 10
fplot.contour(g, -10, 10, equal_aspect=True)
```

Show a surface plot (2 inputs, 1 output)

```g = lambda x, y: x**2 + y**2 + 10
fplot.surface(g, -10, 10)
```

Show a 2d parametric plot (1 input, 2 outputs)

```h = lambda t: (np.sin(t), np.cos(t))
fplot.parametric(h, 0, Ï„, equal_aspect=True, color='m')
```

Show a 3d parametric plot (1 input, 3 outputs)

```i = lambda t: (np.sin(t), np.cos(t), t**2)
fplot.parametric(i, 0, 20, color='red')
```

Show a 2d vector plot (2 inputs, 2 outputs)

```f = lambda x, y: (x**2 + y, y**2 * cos(x))
fplot.vector(f, -10, 10, stream=False)
```

Show a 3d vector plot (3 inputs, 3 outputs)

```f = lambda x, y, z: (x**2, y**2, z)
fplot.vector3d(f, -10, 10)
```

Show a 2d polar plot (1 input, 1 output)

```f = lambda theta: np.sin(3*theta)
fplot.polar(f, 0, tau, color='purple')
```

Example of an interactive plot with Ipython widgets in Jupyter notebook

```from numpy import sin, cos
from ipywidgets import interactive
import fplot

def make_plot(a, b):
f = lambda t: (a*sin(t), a*cos(t), b*t)
ax = fplot.parametric(f, -20, 20, show=False)

ax.set_xlim3d(-3, 3)
ax.set_ylim3d(-3, 3)
ax.set_zlim3d(-3, 3)
plt.show()

interactive_plot = interactive(make_plot, a=(-2.0, 2.0), b=(-3.0, 3.0))
interactive_plot
```
Optional arguments:
• show: Defaults to True. Instantly display the plot. If False, return the axis object.
• resolution: Controls how many points to draw, based on function input. Higher resolution allows more zooming, but may lower performance.
• color: (ie line color)
• linewidth: line width.
• y_min and y_max: (only for 2d input)
• theta_min and theta_max (only for polar plots)
• style: (ie from plt.use.style())
• grid: defaults to True
• equal_aspect: defaults to False
• title: Shown at the top of the plot
• stream: vector plot only; show a stream plot if True
• contours: surface plot only; show contour plots along each axis if True
• num_contours: contour plot only; set number of contour lines to draw. Defaults to 10.