# Tutorial

## TL;DR: If you read nothing else, read this

The most common use case for this package is plotting iso lines. Here's a complete example that lets you do that, while showing off all of the most important features of the package:

```
for cl in levels(contours(x,y,z))
lvl = level(cl) # the z-value of this contour level
for line in lines(cl)
xs, ys = coordinates(line) # coordinates of this line segment
plot(xs, ys, color=lvl) # pseuod-code; use whatever plotting package you prefer
end
end
```

## Preface: some test data...

The Contour module expects input data to be on a Cartesian grid, and supports both uniform and non-uniform grid spacings. For the following examples, `x`

and `y`

are 1D sorted arrays that contain the grid coordinates, and `z`

is a matrix arranged such that `z[xi,yi]`

correspond to the location `(x[xi], y[yi])`

.

Let's consider the function $z(x,y) = x^2 + y^2$:

```
x = -3:0.01:3
y = -4:0.02:5
z = [Float64((xi^2 + yi^2)) for xi in x, yi in y]
nothing # hide
```

`x`

and `y`

don't have to be evenly spaced - they can just as well be (sorted) arrays of coordinate values.

## Example: plotting isolines

Usually, you'll start by calling `contours`

:

`c = contours(x,y,z)`

The package is designed so that you shouldn't have to worry about the types of the outputs - instead, there are functions that let you extract the data you need. So, instead of simply returning a `Vector{ContourLevel}`

, we return a special object which supports the `levels`

function. `levels`

in turn returns an iterable, where each item represents a contour level:

```
for cl in levels(c)
# do something
end
```

On each level (`cl`

in the snippet above) there are two pieces of information that can be of interest. You find the $z$-value of the isoline with the `level`

function, while `lines`

yields an iterable collection of line segments (remember that there might be more than one isoline for a given $z$-value):

```
level(cl) # the z-value of the current isoline collection
lines(cl) # an iterable collection of isolines
```

This contour level only had one line. An isoline is represented as a sequence of vertices, which either starts and ends at the boundaries of the data set, or closes on itself, in which case the first and last points are equal.

The $x$- and $y$-coordinates of an isoline are extracted using the `coordinates`

function:

```
l = first(lines(cl))
xs, ys = coordinates(l)
```

Now we understand all the parts of the plotting example at the top:

```
for cl in levels(contours(x,y,z))
lvl = level(cl) # the z-value of this contour level
for line in lines(cl)
xs, ys = coordinates(line) # coordinates of this line segment
plot(xs, ys, color=lvl) # pseuod-code; use whatever plotting package you prefer
end
end
```

## Affecting the choice of contour levels

There are several ways to affect the choice of contour levels.

First, you can specify them manually:

`contours(x, y, z, [2,3])`

You can also just specify the number of levels you want, and let the package choose them:

`contours(x, y, z, 2)`

The package uses `Contour.contourlevels`

to choose the levels, so it's entirely possible to investigate what levels would be traced without doing any plotting:

`Contour.contourlevels(z, 4)`

If you only want a single contour level, use the `contour`

function directly - its fourth parameter is the $z$-value at which to trace the isolines:

`contour(x, y, z, 2.3)`