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import numpy as np
from IPython.display import display
from bqplot import *


    

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size = 100
np.random.seed(0)
x_data = np.arange(size)
y_data = np.cumsum(np.random.randn(100)  * 100.0)


    

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x_sc = LinearScale()
y_sc = LinearScale()

ax_x = Axis(label='X', scale=x_sc, grid_lines='solid')
ax_y = Axis(label='Y', scale=y_sc, orientation='vertical', grid_lines='solid')

line = Lines(x=x_data, y=x_data, scales={'x': x_sc, 'y': y_sc})
fig = Figure(axes=[ax_x, ax_y], marks=[line])
display(fig)


    

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dates = np.arange('2005-02', '2005-03', dtype='datetime64[D]')
size = len(dates)
prices = 100 + 5 * np.cumsum(np.random.randn(size))


    

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dt_x = DateScale()
lin_y = LinearScale()

x_ax = Axis(label='Date', scale=dt_x, tick_format='%b-%d', grid_lines='solid')
x_ay = Axis(label=('Price'), scale=lin_y, orientation='vertical', tick_format='0.0f', grid_lines='solid')

lc = Lines(x=dates, y=prices, scales={'x': dt_x, 'y': lin_y}, colors=['blue'])

fig = Figure(marks=[lc], axes=[x_ax, x_ay], fig_color='lightgreen')
display(fig)


    

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fig.fig_color = 'Black'


    

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sc_x = LinearScale()
sc_y = LinearScale()
scatter = Scatter(x=x_data, y=y_data, scales={'x': sc_x, 'y': sc_y}, default_colors=['blue'])

ax_x = Axis(label='Test X', scale=sc_x)
ax_y = Axis(label='Test Y', scale=sc_y, orientation='vertical', tick_format='0.2f')

fig = Figure(axes=[ax_x, ax_y], marks=[scatter])
display(fig)


    

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scale_x = LinearScale()
scale_y = LinearScale()
hist = Hist(sample=y_data, scales={'sample': scale_x, 'count': scale_y})

ax_x = Axis(label='X', scale=scale_x, tick_format='0.2f')
ax_y = Axis(label='Y', scale=scale_y, orientation='vertical', grid_lines='solid')
fig = Figure(axes=[ax_x, ax_y], marks=[hist])
display(fig)


    

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sc_x1 = OrdinalScale()
sc_y1 = LinearScale()

bar_x = Axis(label='X', scale=sc_x1)
bar_y = Axis(label='Y', scale=sc_y1, orientation='vertical', tick_format='0.0f', grid_lines='solid')
bar_chart = Bars(x=['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'P', 'Q', 'R', 'S', 'T', 'U'],
                 y=np.abs(y_data[:20]), scales={'x': sc_x1, 'y': sc_y1})

fig = Figure(axes=[bar_x, bar_y], marks=[bar_chart], padding_x=0)
display(fig)