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

# ## Plotting with plot.ly backend

# In[1]:


# Basic imports
from physt.examples import normal_h2, normal_h1
from physt.plotting import plotly
import physt.plotting

import numpy as np
np.random.seed(42)

# Set that we want plotly
physt.plotting.set_default_backend("plotly")


# The following lines are necessary if you want to display plots in the Jupyter notebook.

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import plotly.offline as po
po.init_notebook_mode()


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# Define the 1-D example
H = normal_h1()


# The default plot is `bar`.

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H.plot()  # Same as H.plot.bar()


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H.plot.line()


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H.plot.scatter()


# ## Matplotlib compatibility
# 
# Plot.ly supports to convert matplotlib figures into plot.ly ones.
# You can use this compatibility with several fancy properties.
# 
# Just add the `mpl` keyword argument to your plotting call:

# In[7]:


H.plot.line(color="red", lw=5, yscale="log", mpl=True)


# ## Plot.ly object
# 
# If you want to further manipulate the figures, you can return them from
# the function as-is using the `raw` keyword.

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H.plot.scatter(raw=True)


# ## 2D histograms

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H2 = normal_h2()


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# Default is heatmap
H2.plot()


# ## Collections

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from physt.histogram_collection import HistogramCollection

collection = HistogramCollection.h1({
    "small": np.random.normal(160, 20, 600),
    "tall": np.random.normal(180, 20, 1000),
    "huge": np.random.normal(200, 20, 400),
    "gigantic": np.random.normal(220, 20, 200)
}, "human")


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collection.plot.line()


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# Let's see normalized histograms in the collection
collection.normalize_bins().plot(barmode="overlay", alpha=0.3)


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# ...and how they look like when stacked
collection.normalize_bins().plot(barmode="stack")