#!/usr/bin/env python
# coding: utf-8

# # 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()


# 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)


# 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)


# 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)


# 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)


# 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)


# Parameter `h_start` now works with descrete data:

# In[10]:


p + scale_fill_hue(h_start=180)


# Parameter `l` now correctly controls lightness:

# In[11]:


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


# # 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))


# 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))


# 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")
)


# In[16]:


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


# In[17]:


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


# 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)


# 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)


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