---
title: "3. Plotting trajectories of theoretic stress directions"
author: "Tobias Stephan"
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{3. Plotting trajectories of theoretic stress directions}
  %\VignetteEncoding{UTF-8}
  %\VignetteEngine{knitr::rmarkdown}
editor_options: 
  markdown: 
    wrap: 72
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

This vignette teaches you how to plot the trajectories of the predicted 
stress directions.

```{r setup, echo=TRUE,message=FALSE}
library(tectonicr)
library(ggplot2) # load ggplot library
library(sf)

theme_set(theme_bw())
```

## Equivalent rotations

Relative plate motions from a set of (global) plate motions can be retrieved by 
transforming the set of the Euler rotations parameters to equivalent rotations.

The NUVEL1 data set offers the global plate motions relative to the Pacific 
plate (DeMets et al. 1990). In order to extract the plate motions between two other plates 
(e.g. all plates relative to Eurasia), one has to transform the rotations in to 
a new, equivalent reference system (i.e. all rotation with respect to (wrt.)
Eurasia). 

In **tectonicr** this can be done with `equivalent_rotation()`:

```{r nuvel_eq, echo=TRUE}
data("nuvel1")
nuvel1.eu <- equivalent_rotation(nuvel1, fixed = "eu")
head(nuvel1.eu)
```

Alternatively, the PB2002 model by Bird (2003) is also provided as an ready-to 
use example dataset for global plate motions.

```{r pb2002_eq, echo=TRUE}
data("pb2002")
pb2002.eu <- equivalent_rotation(pb2002, fixed = "eu")
head(pb2002.eu)
```

## Plotting Pole of Rotation Grids

To visualize the theoretical trajectories of the direction of $\sigma_{Hmax}$ 
(great circles, small circles, and loxodomes), we need to transform the 
locations from the geographical coordinate system into the *PoR* coordinate 
system. The transformations are done through the function functions 
`geographical_to_PoR()` and `PoR_to_geographical()`. They are the base of the 
functions `eulerpole_smallcircles()`, `eulerpole_greatcircles()`, and 
`eulerpole_loxodromes()` that allow to draw the theoretical trajectories in
geographical coordinates.

### Small Circles

Function `eulerpole_smallcircles(x, gridsize)` returns small circles as as 
simple feature(`sf`) by giving a `data.frame` of the PoR
coordinates in lat and lon (`x`) and the number of small circles (`n`).

For example the small circles around the pole of the relative
motion of the Indian plate relative to the Eurasian plate (transformed from the 
from the NUVEL1 model).

```{r nuvel_euin, echo=TRUE}
por <-
  subset(nuvel1.eu, nuvel1$plate.rot == "in") # India relative to Eurasia
```

The `returnclass` option in `eulerpole_smallcircles()` provides the output 
types `"sf"` (for a simple feature) and `"sp"` (`Spatial*` object) for the
small circles. 

To eventually plot the small circles with `ggplot`, I recommend to extract a 
`sf` feature and plot the it with `geom_sf()`: 

```{r small_circles_around_ep, echo=TRUE}
por.sm <- eulerpole_smallcircles(por)
data("plates") # load plate boundary data set
# world <- rnaturalearth::ne_countries(scale = "small", returnclass = "sf")

ggplot() +
  # geom_sf(data = world, alpha = .5) +
  geom_sf(
    data = plates,
    color = "#FB8861FF",
    alpha = .5
  ) +
  labs(title = "India relative to Eurasia", subtitle = "source: NUVEL1") +
  geom_sf(
    data = por.sm,
    aes(lty = "small circles"),
    color = "#51127CFF", fill = NA,
    alpha = .5
  ) +
  geom_point(
    data = por,
    aes(lon, lat),
    shape = 21,
    colour = "#B63679FF",
    size = 2,
    fill = "#51127CFF",
    stroke = 1
  ) +
  geom_point(
    data = por,
    aes(lon + 180, -lat),
    shape = 21,
    colour = "#B63679FF",
    size = 2,
    fill = "#51127CFF",
    stroke = 1
  ) +
  coord_sf(default_crs = "WGS84", crs = sf::st_crs("ESRI:54030"))
```

<!-- ![Predicted SHmax trajectories that are small circles around the In-Eu pole of rotation.](smallcircles.png) -->


### Great Circles

Great circles are lines that cut the small circles at 90$^{\circ}$ and
the PoR. Function `eulerpole_greatcircles(x, n)` returns great
circles as `sf` object by giving a `data.frame` of the Pole of Rotation (PoR)
coordinates in lat and lon (`x`) and the number of great circles `n`,
or the great circle angles (`360/d`).

```{r great_circles_around_ep, echo=TRUE}
por.gm <- eulerpole_greatcircles(por)

ggplot() +
  # geom_sf(data = world, alpha = .5) +
  geom_sf(
    data = plates,
    color = "#FB8861FF",
    alpha = .5
  ) +
  labs(title = "India relative to Eurasia", subtitle = "source: NUVEL1") +
  geom_sf(
    data = por.sm,
    aes(lty = "small circles"),
    color = "#51127CFF",
    alpha = .5
  ) +
  geom_sf(
    data = por.gm,
    aes(lty = "great circles"),
    color = "#51127CFF"
  ) +
  geom_point(
    data = por,
    aes(lon, lat),
    shape = 21,
    colour = "#B63679FF",
    size = 2,
    fill = "#51127CFF",
    stroke = 1
  ) +
  geom_point(
    data = por,
    aes(lon + 180, -lat),
    shape = 21,
    colour = "#B63679FF",
    size = 2,
    fill = "#51127CFF",
    stroke = 1
  ) +
  coord_sf(default_crs = "WGS84", crs = sf::st_crs("ESRI:54030"))
```

<!-- ![Predicted SHmax trajectories that are great circles passing through the In-Eu pole of rotation.](greatcircles.png) -->

### Loxodromes

Loxodrome (also called Rhumb Line) is a curve cutting the small circles
at a constant angle. Thus, small and great circles are 0$^{\circ}$ and
90$^{\circ}$ loxodromes, respectively.

Function `eulerpole_loxodromes(x, n)` returns loxodromes as
`sf` object by giving a `data.frame` of the PoR
coordinates in lat and lon (`x`) and the angle between the loxodromes, the
direction, and the sense.


```{r loxodromes, echo=TRUE}
por.ld <- eulerpole_loxodromes(x = por, angle = 45, n = 10, cw = TRUE)

ggplot() +
  labs(title = "India relative to Eurasia", subtitle = "source: NUVEL1") +
  # geom_sf(data = world, alpha = .5) +
  geom_sf(
    data = plates,
    color = "#FB8861FF",
    alpha = .5
  ) +
  geom_sf(
    data = por.sm,
    aes(lty = "small circles"),
    color = "#51127CFF",
    alpha = .5
  ) +
  geom_sf(
    data = por.ld,
    aes(lty = "clockwise loxodromes"),
    color = "#51127CFF"
  ) +
  geom_point(
    data = por,
    aes(lon, lat),
    shape = 21,
    colour = "#B63679FF",
    size = 2,
    fill = "#51127CFF",
    stroke = 1
  ) +
  geom_point(
    data = por,
    aes(lon + 180, -lat),
    shape = 21,
    colour = "#B63679FF",
    size = 2,
    fill = "#51127CFF",
    stroke = 1
  ) +
  coord_sf(default_crs = "WGS84", crs = sf::st_crs("ESRI:54030"))
```

<!-- ![Predicted SHmax trajectories that are 45-degree loxodromes circles directed towards the In-Eu pole of rotation.](loxodromes.png) -->

# References

Bird, Peter. 2003. “An Updated Digital Model of Plate Boundaries” 
*Geochemistry, Geophysics, Geosystems* 4 (3). 
doi: 10.1029/2001gc000252.
<!---[10.1029/2001gc000252](https://doi.org/10.1029/2001GC000252).-->


DeMets, C., R. G. Gordon, D. F. Argus, and S. Stein. 1990. “Current Plate Motions” 
*Geophysical Journal International* 101 (2): 425–78. 
doi: [10.1111/j.1365-246x.1990.tb06579.x](https://doi.org/10.1111/j.1365-246x.1990.tb06579.x).
