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DOC: improved dual_moving_average.py example algo

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Victor Grau Serrat
2017-11-27 21:10:17 -07:00
parent 1da4ccfb8c
commit a52e201f86
1 changed files with 9 additions and 9 deletions
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catalyst/examples/dual_moving_average.py
+9 -9
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@@ -1,10 +1,10 @@
import numpy as np
import pandas as pd
from logbook import Logger
import matplotlib.pyplot as plt
import matplotlib.pyplot as plt
from catalyst import run_algorithm
from catalyst.api import (order, record, symbol, order_target_percent,
from catalyst.api import (order, record, symbol, order_target_percent,
get_open_orders)
from catalyst.exchange.stats_utils import extract_transactions
@@ -18,7 +18,7 @@ def initialize(context):
def handle_data(context, data):
# define the windows for the moving averages
# define the windows for the moving averages
short_window = 50
long_window = 200
@@ -27,11 +27,11 @@ def handle_data(context, data):
if context.i < long_window:
return
# Compute moving averages calling data.history() for each
# Compute moving averages calling data.history() for each
# moving average with the appropriate parameters. We choose to use
# minute bars for this simulation -> freq="1m"
# Returns a pandas dataframe.
short_mavg = data.history(context.asset, 'price',
short_mavg = data.history(context.asset, 'price',
bar_count=short_window, frequency="1m").mean()
long_mavg = data.history(context.asset, 'price',
bar_count=long_window, frequency="1m").mean()
@@ -79,7 +79,7 @@ def analyze(context, perf):
# Get the base_currency that was passed as a parameter to the simulation
base_currency = context.exchanges.values()[0].base_currency.upper()
# First subgraph: Plot portfolio value using base_currency
# First chart: Plot portfolio value using base_currency
ax1 = plt.subplot(411)
perf.loc[:, ['portfolio_value']].plot(ax=ax1)
ax1.legend_.remove()
@@ -87,7 +87,7 @@ def analyze(context, perf):
start, end = ax1.get_ylim()
ax1.yaxis.set_ticks(np.arange(start, end, (end-start)/5))
# Second subgraph: Plot asset price, moving averages and buys/sells
# Second chart: Plot asset price, moving averages and buys/sells
ax2 = plt.subplot(412, sharex=ax1)
perf.loc[:, ['price','short_mavg','long_mavg']].plot(ax=ax2, label='Price')
ax2.legend_.remove()
@@ -119,7 +119,7 @@ def analyze(context, perf):
label=''
)
# Third subgraph: Compare percentage change between our portfolio
# Third chart: Compare percentage change between our portfolio
# and the price of the asset
ax3 = plt.subplot(413, sharex=ax1)
perf.loc[:, ['algorithm_period_return', 'price_change']].plot(ax=ax3)
@@ -128,7 +128,7 @@ def analyze(context, perf):
start, end = ax3.get_ylim()
ax3.yaxis.set_ticks(np.arange(start, end, (end-start)/5))
# Plot our cash
# Fourth chart: Plot our cash
ax4 = plt.subplot(414, sharex=ax1)
perf.cash.plot(ax=ax4)
ax4.set_ylabel('Cash\n({})'.format(base_currency))