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# Visualisation

```{eval-rst}
.. autoclass:: portfolio_plan.visualisation.theme_rose_pine
   :members:
   :show-inheritance:
```

```{code-cell}
from plotnine import geom_line, ggplot, aes
from plotnine.data import economics

from portfolio_plan.visualisation import theme_rose_pine


p = (
    ggplot(data=economics, mapping=aes(x="date", y="unemploy"))
    + geom_line()
)

p
```
```{code-cell}
p + theme_rose_pine(variant="main")
```

```{code-cell}
p + theme_rose_pine(variant="moon")
```
```{code-cell}
p + theme_rose_pine(variant="dawn")
```

## Custom Discrete Color Scales

The Rose Pine theme also includes custom discrete color scales for mapping categories to colors. These scales are available for both `color` and `fill` aesthetics.

### Example: Discrete Color Scale

```{code-cell}
from plotnine import ggplot, aes, geom_point
import pandas as pd
from portfolio_plan.visualisation import scale_rose_pine_discrete

# Example data
data = pd.DataFrame({
    "x": [1, 2, 3, 4, 5, 6],
    "y": [10, 15, 20, 25, 30, 35],
    "category": pd.Categorical(["love", "rose", "gold", "pine", "foam", "iris"], ordered=True),
})

# Create a plot with the custom color scale
plot = (
    ggplot(data, aes(x="x", y="y", color="category")) +
    geom_point(size=5) +
    scale_rose_pine_discrete(variant="moon")
)

plot
```

### Example: Discrete Fill Scale

```{code-cell}
from plotnine import ggplot, aes, geom_bar
import pandas as pd
from portfolio_plan.visualisation import scale_rose_pine_fill_discrete

# Example data
data = pd.DataFrame({
    "category": pd.Categorical(["love", "gold", "rose", "pine", "foam", "iris"], ordered=True),

    "value": [10, 15, 20, 25, 30, 35],
})

# Create a bar chart with the custom fill scale
plot = (
    ggplot(data, aes(x="category", y="value", fill="category")) +
    geom_bar(stat="identity") +
    scale_rose_pine_fill_discrete(variant="dawn")
)

plot
```

### Example: Brewer Fill Scale

```{code-cell}
from plotnine import ggplot, aes, geom_bar
import pandas as pd
from portfolio_plan.visualisation import scale_brewer_fill_discrete

# Example data
data = pd.DataFrame({
    "category": pd.Categorical(["A", "B", "C", "D", "E", "F"], ordered=True),

    "value": [5, 10, 15, 20, 25, 30],
})

# Create a bar chart with the brewer fill scale
plot = (
    ggplot(data, aes(x="category", y="value", fill="category")) +
    geom_bar(stat="identity") +
    scale_brewer_fill_discrete(palette="Set3")
)

plot
```