viviBartPlot {bartMan} | R Documentation |

## viviBartPlot

### Description

Plots a Heatmap showing variable importance on the diagonal and variable interaction on the off-diagonal with uncertainty included.

### Usage

```
viviBartPlot(
matrix,
intPal = NULL,
impPal = NULL,
intLims = NULL,
impLims = NULL,
uncIntLims = NULL,
uncImpLims = NULL,
unc_levels = 4,
max_desat = 0.6,
pow_desat = 0.2,
max_light = 0.6,
pow_light = 1,
angle = 0,
border = FALSE,
label = NULL
)
```

### Arguments

`matrix` |
Matrices, such as that returned by viviBartMatrix, of values to be plotted. |

`intPal` |
A vector of colours to show interactions, for use with scale_fill_gradientn. Palette number has to be 2^x/2 |

`impPal` |
A vector of colours to show importance, for use with scale_fill_gradientn. Palette number has to be 2^x/2 |

`intLims` |
Specifies the fit range for the color map for interaction strength. |

`impLims` |
Specifies the fit range for the color map for importance. |

`uncIntLims` |
Specifies the fit range for the color map for interaction strength uncertainties. |

`uncImpLims` |
Specifies the fit range for the color map for importance uncertainties. |

`unc_levels` |
The number of uncertainty levels |

`max_desat` |
The maximum desaturation level. |

`pow_desat` |
The power of desaturation level. |

`max_light` |
The maximum light level. |

`pow_light` |
The power of light level. |

`angle` |
The angle to rotate the x-axis labels. Defaults to zero. |

`border` |
Logical. If TRUE then draw a black border around the diagonal elements. |

`label` |
legend label for the uncertainty measure. |

### Value

Either a heatmap, VSUP, or quantile heatmap plot.

### Examples

```
if(requireNamespace("dbarts", quietly = TRUE)){
# Load the dbarts package to access the bart function
library(dbarts)
# Get Data
df <- na.omit(airquality)
# Create Simple dbarts Model For Regression:
set.seed(1701)
dbartModel <- bart(df[2:6], df[, 1], ntree = 5, keeptrees = TRUE, nskip = 10, ndpost = 10)
# Tree Data
trees_data <- extractTreeData(model = dbartModel, data = df)
# VSUP Matrix
vsupMat <- viviBartMatrix(trees = trees_data,
type = 'vsup',
metric = 'propMean',
metricError = 'CV')
# Plot
viviBartPlot(vsupMat, label = 'CV')
}
```

*bartMan*version 0.1.1 Index]