HCL color model.¶

Lets-Plot now uses the HCL color model instead of HLV. This change affects hue scale and gradient scales (both color and greyscale).

In [1]:

from lets_plot import *

In [2]:

LetsPlot.setup_html()

In [3]:

data = { 'x': ['A', 'B', 'C', 'D', 'E', 'F'] }
p = ggplot(data) \
    + geom_boxplot(aes(x='x', fill='x'), stat='identity', lower=25, middle=50, upper=75, ymin=0, ymax=100)

Palette for discrete data:

In [4]:

p + scale_fill_hue()

Out[4]:

Hue gradient:

In [5]:

data = {
    'x': list(range(256))
}

ggplot(data) \
    + geom_tile(aes(x='x', fill='x', color='x'), size=1) \
    + scale_fill_hue() \
    + scale_color_hue() \
    + coord_cartesian() \
    + ggsize(800, 200)

Out[5]:

Gradient:

In [6]:

df = { 
    'x': list(range(256)) 
}

ggplot(df) \
    + geom_tile(aes(x='x', fill='x', color='x'), size=1) \
    + scale_fill_gradient(low="#00FF00", high="#FF0000") \
    + scale_color_gradient(low="#00FF00", high="#FF0000") \
    + coord_cartesian() \
    + ggsize(800, 200)

Out[6]:

Gradientn

In [7]:

df = { 
    'x': list(range(256)) 
}

ggplot(df) \
    + geom_tile(aes(x='x', fill='x', color='x'), size=1) \
    + scale_fill_gradientn(colors=["#00FF00", "#FF0000", "#0000FF"]) \
    + scale_color_gradientn(colors=["#00FF00", "#FF0000", "#0000FF"]) \
    + coord_cartesian() \
    + ggsize(800, 200)

Out[7]:

Greyscale gradient:

In [8]:

df = { 
    'x': list(range(256)) 
}

ggplot(df) \
    + geom_tile(aes(x='x', fill='x', color='x'), size=1) \
    + scale_color_grey(start=0.1, end=0.9) \
    + scale_fill_grey(start=0.1, end=0.9) \
    + coord_cartesian() \
    + ggsize(800, 200)

Out[8]:

Viridis

In [9]:

df = { 
    'x': list(range(256)) 
}

ggplot(df) \
    + geom_tile(aes(x='x', fill='x', color='x'), size=1) \
    + scale_fill_viridis() \
    + scale_color_viridis() \
    + coord_cartesian() \
    + ggsize(800, 200)

Out[9]:

Parameter h_start now works with descrete data:

In [10]:

p + scale_fill_hue(h_start=180)

Out[10]:

Parameter l now correctly controls lightness:

In [11]:

p + scale_fill_hue(c=95, l=75) + ggtitle('scale_fill_hue(c=95, l=75)')

Out[11]:

SANDBOX¶

In [12]:

def dump_spec(plot, display=None):
    import json

    try:
        import clipboard
    except:
        clipboard = None
        
    from lets_plot._type_utils import standardize_dict
    
    plot_dict = standardize_dict(plot.as_dict())
    plot_json = json.dumps(plot_dict, indent=2)
    
    if clipboard:
        clipboard.copy('')
        clipboard.copy(str(plot_json))
    else:
        if display is None:
            display = True
    
    if display:
        print(plot_json)

    return plot

In [13]:

data = {
    'x': list(range(60))
}

dump_spec(ggplot(data) \
    + geom_tile(aes(x='x', fill='x', color='x'), size=1) \
    + scale_fill_hue() \
    + scale_color_hue() \
    + coord_cartesian() \
    + ggsize(600, 200))

Out[13]:

In [14]:

dump_spec(ggplot(data) \
    + geom_tile(aes(x='x', fill='x', color='x'), size=1) \
    + scale_fill_grey() \
    + scale_color_grey() \
    + coord_cartesian() \
    + ggsize(600, 200))

Out[14]:

In [15]:

df = { 'x': list(range(59)) }
dump_spec(
    ggplot(df) \
        + geom_tile(aes(x='x', fill='x', color='x'), size=1, height=40) \
        + scale_fill_gradient(low="#00FF00", high="#FF0000") \
        + scale_color_gradient(low="#00FF00", high="#FF0000")
)

Out[15]:

In [16]:

ggplot(df) + geom_tile(aes(x='x', fill='x'), height=40) + scale_fill_gradient(low = "yellow", high = "red")

Out[16]:

In [17]:

dump_spec(p + scale_fill_hue(h = [15, 375], c = 100, l = 100))

Out[17]:

In [18]:

df = { 
    'x': list(range(256)) 
}

ggplot(df) \
    + geom_tile(aes(x='x', fill='x', color='x'), size=1) \
    + scale_fill_viridis() \
    + scale_color_viridis() \
    + coord_cartesian() \
    + ggsize(800, 400)

Out[18]:

In [19]:

ggplot(df) \
    + geom_tile(aes(x='x', fill='x', color='x'), size=1) \
    + scale_fill_viridis() \
    + scale_color_viridis(option='A') \
    + coord_cartesian() \
    + ggsize(800, 400)

Out[19]:

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