advanced-algorithmic-trading

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# up days and red for down days
csticks = candlestick_ohlc(
ax, df[
[’date_fmt’, ’Open’, ’High’, ’Low’, ’Close’]
].values, width=0.6,
colorup=’#000000’, colordown=’#ff0000’
)
ax.set_axis_bgcolor((1,1,0.9))
ax.xaxis_date()
plt.setp(
plt.gca().get_xticklabels(),
rotation=45, horizontalalignment=’right’
)
plt.show()
def plot_3d_normalised_candles(data):
"""
Plot a 3D scatterchart of the open-normalised bars
highlighting the separate clusters by colour
"""
fig = plt.figure(figsize=(12, 9))
ax = Axes3D(fig, elev=21, azim=-136)
ax.scatter(
data["H/O"], data["L/O"], data["C/O"],
c=labels.astype(np.float)
)
ax.set_xlabel(’High/Open’)
ax.set_ylabel(’Low/Open’)
ax.set_zlabel(’Close/Open’)
plt.show()
def plot_cluster_ordered_candles(data):
"""
Plot a candlestick chart ordered by cluster membership
with the dotted blue line representing each cluster
boundary.
"""
# Set the format for the axis to account for dates
# correctly, particularly Monday as a major tick
mondays = WeekdayLocator(MONDAY)
alldays = DayLocator()
weekFormatter = DateFormatter("")
fig, ax = plt.subplots(figsize=(16,4))