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Added sparse discrete mean reverting oracle and config.
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@@ -18,4 +18,5 @@ cd project | |
| git clone https://github.com/abides-sim/abides.git | ||
| cd abides | ||
| pip install -r requirements.txt | ||
| ``` | ||
| ``` | ||
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| import ast | ||
| import matplotlib | ||
| matplotlib.use('TkAgg') | ||
| import matplotlib.pyplot as plt | ||
| import pandas as pd | ||
| import os | ||
| import re | ||
| import sys | ||
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| from joblib import Memory | ||
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| # Auto-detect terminal width. | ||
| pd.options.display.width = None | ||
| pd.options.display.max_rows = 1000 | ||
| pd.options.display.max_colwidth = 200 | ||
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| BETWEEN_START = pd.to_datetime('09:30').time() | ||
| BETWEEN_END = pd.to_datetime('16:00:00').time() | ||
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| # Linewidth for plots. | ||
| LW = 2 | ||
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| # Main program starts here. | ||
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| if len(sys.argv) < 2: | ||
| print ("Usage: python sparse_fundamental.py <Simulator Fundamental file>") | ||
| sys.exit() | ||
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| # TODO: only really works for one symbol right now. | ||
| sim_file = sys.argv[1] | ||
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| m = re.search(r'fundamental_(.+?)\.', sim_file) | ||
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| if not m: | ||
| print ("Usage: python sparse_fundamental.py <Simulator Fundamental file>") | ||
| print ("{} does not appear to be a fundamental value log.".format(sim_file)) | ||
| print () | ||
| sys.exit() | ||
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| symbol = m.group(1) | ||
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| print ("Visualizing simulated fundamental from {}".format(sim_file)) | ||
| df_sim = pd.read_pickle(sim_file, compression='bz2') | ||
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| plt.rcParams.update({'font.size': 12}) | ||
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| print (df_sim.head()) | ||
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| # Use to restrict time to plot. | ||
| #df_sim = df_sim.between_time(BETWEEN_START, BETWEEN_END) | ||
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| fig,ax = plt.subplots(figsize=(12,9), nrows=1, ncols=1) | ||
| axes = [ax] | ||
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| # For smoothing... | ||
| #hist_window = 100 | ||
| #sim_window = 100 | ||
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| hist_window = 1 | ||
| sim_window = 1 | ||
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| #df_sim['PRICE'] = df_sim['PRICE'].rolling(window=sim_window).mean() | ||
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| df_sim['FundamentalValue'].plot(color='C1', grid=True, linewidth=LW, alpha=0.9, ax=axes[0]) | ||
| axes[0].legend(['Simulated']) | ||
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| plt.suptitle('Fundamental Value: {}'.format(symbol)) | ||
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| axes[0].set_ylabel('Fundamental Value') | ||
| axes[0].set_xlabel('Fundamental Time') | ||
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| #plt.savefig('background_{}.png'.format(b)) | ||
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| plt.show() | ||
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,157 @@ | ||
| import ast | ||
| import matplotlib | ||
| matplotlib.use('TkAgg') | ||
| import matplotlib.pyplot as plt | ||
| import pandas as pd | ||
| import os | ||
| import sys | ||
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| from joblib import Memory | ||
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| # Auto-detect terminal width. | ||
| pd.options.display.width = None | ||
| pd.options.display.max_rows = 1000 | ||
| pd.options.display.max_colwidth = 200 | ||
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| # Initialize a persistent memcache. | ||
| mem_hist = Memory(cachedir='./.cached_plot_hist', verbose=0) | ||
| mem_sim = Memory(cachedir='./.cached_plot_sim', verbose=0) | ||
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| PRINT_BASELINE = False | ||
| PRINT_DELTA_ONLY = False | ||
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| BETWEEN_START = pd.to_datetime('09:30').time() | ||
| BETWEEN_END = pd.to_datetime('16:00:00').time() | ||
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| # Linewidth for plots. | ||
| LW = 2 | ||
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| # Used to read and cache simulated quotes. | ||
| # Doesn't actually pay attention to symbols yet. | ||
| #@mem_sim.cache | ||
| def read_simulated_quotes (file, symbol): | ||
| print ("Simulated quotes were not cached. This will take a minute.") | ||
| df = pd.read_pickle(file, compression='bz2') | ||
| df['Timestamp'] = df.index | ||
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| # Keep only the last bid and last ask event at each timestamp. | ||
| df = df.drop_duplicates(subset=['Timestamp','EventType'], keep='last') | ||
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| del df['Timestamp'] | ||
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| df_bid = df[df['EventType'] == 'BEST_BID'].copy() | ||
| df_ask = df[df['EventType'] == 'BEST_ASK'].copy() | ||
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| if len(df) <= 0: | ||
| print ("There appear to be no simulated quotes.") | ||
| sys.exit() | ||
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| df_bid['BEST_BID'] = [b for s,b,bv in df_bid['Event'].str.split(',')] | ||
| df_bid['BEST_BID_VOL'] = [bv for s,b,bv in df_bid['Event'].str.split(',')] | ||
| df_ask['BEST_ASK'] = [a for s,a,av in df_ask['Event'].str.split(',')] | ||
| df_ask['BEST_ASK_VOL'] = [av for s,a,av in df_ask['Event'].str.split(',')] | ||
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| df_bid['BEST_BID'] = df_bid['BEST_BID'].str.replace('$','').astype('float64') | ||
| df_ask['BEST_ASK'] = df_ask['BEST_ASK'].str.replace('$','').astype('float64') | ||
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| df_bid['BEST_BID_VOL'] = df_bid['BEST_BID_VOL'].astype('float64') | ||
| df_ask['BEST_ASK_VOL'] = df_ask['BEST_ASK_VOL'].astype('float64') | ||
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| df = df_bid.join(df_ask, how='outer', lsuffix='.bid', rsuffix='.ask') | ||
| df['BEST_BID'] = df['BEST_BID'].ffill().bfill() | ||
| df['BEST_ASK'] = df['BEST_ASK'].ffill().bfill() | ||
| df['BEST_BID_VOL'] = df['BEST_BID_VOL'].ffill().bfill() | ||
| df['BEST_ASK_VOL'] = df['BEST_ASK_VOL'].ffill().bfill() | ||
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| df['MIDPOINT'] = (df['BEST_BID'] + df['BEST_ASK']) / 2.0 | ||
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| return df | ||
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| # Main program starts here. | ||
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| if len(sys.argv) < 3: | ||
| print ("Usage: python midpoint_plot.py <Ticker symbol> <Simulator DataFrame file>") | ||
| sys.exit() | ||
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| # TODO: only really works for one symbol right now. | ||
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| symbol = sys.argv[1] | ||
| sim_file = sys.argv[2] | ||
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| print ("Visualizing simulated {} from {}".format(symbol, sim_file)) | ||
| df_sim = read_simulated_quotes(sim_file, symbol) | ||
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| if PRINT_BASELINE: | ||
| baseline_file = os.path.join(os.path.dirname(sim_file) + '_baseline', os.path.basename(sim_file)) | ||
| print (baseline_file) | ||
| df_baseline = read_simulated_quotes(baseline_file, symbol) | ||
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| plt.rcParams.update({'font.size': 12}) | ||
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| # Use to restrict time to plot. | ||
| df_sim = df_sim.between_time(BETWEEN_START, BETWEEN_END) | ||
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| if PRINT_BASELINE: | ||
| df_baseline = df_baseline.between_time(BETWEEN_START, BETWEEN_END) | ||
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| fig,ax = plt.subplots(figsize=(12,9), nrows=1, ncols=1) | ||
| axes = [ax] | ||
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| # For smoothing... | ||
| #hist_window = 100 | ||
| #sim_window = 100 | ||
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| hist_window = 1 | ||
| sim_window = 1 | ||
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| if PRINT_BASELINE: | ||
| # For nanosecond experiments, turn it into int index. Pandas gets weird if all | ||
| # the times vary only by a few nanoseconds. | ||
| rng = pd.date_range(start=df_sim.index[0], end=df_sim.index[-1], freq='1N') | ||
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| df_baseline = df_baseline[~df_baseline.index.duplicated(keep='last')] | ||
| df_baseline = df_baseline.reindex(rng,method='ffill') | ||
| df_baseline = df_baseline.reset_index(drop=True) | ||
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| df_sim = df_sim[~df_sim.index.duplicated(keep='last')] | ||
| df_sim = df_sim.reindex(rng,method='ffill') | ||
| df_sim = df_sim.reset_index(drop=True) | ||
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| # Print both separately. | ||
| if PRINT_DELTA_ONLY: | ||
| # Print the difference as a single series. | ||
| df_diff = df_sim['MIDPOINT'] - df_baseline['MIDPOINT'] | ||
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| # Smoothing. | ||
| df_diff = df_diff.rolling(window=10).mean() | ||
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| df_diff.plot(color='C0', grid=True, linewidth=LW, ax=axes[0]) | ||
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| axes[0].legend(['Bid-ask Midpoint Delta']) | ||
| else: | ||
| df_baseline['MIDPOINT'].plot(color='C0', grid=True, linewidth=LW, ax=axes[0]) | ||
| df_sim['MIDPOINT'].plot(color='C1', grid=True, linewidth=LW, alpha=0.9, ax=axes[0]) | ||
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| axes[0].legend(['Baseline', 'With Impact']) | ||
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| else: | ||
| #df_sim['PRICE'] = df_sim['PRICE'].rolling(window=sim_window).mean() | ||
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| df_sim['MIDPOINT'].plot(color='C1', grid=True, linewidth=LW, alpha=0.9, ax=axes[0]) | ||
| axes[0].legend(['Simulated']) | ||
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| plt.suptitle('Bid-Ask Midpoint: {}'.format(symbol)) | ||
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| axes[0].set_ylabel('Quote Price') | ||
| axes[0].set_xlabel('Quote Time') | ||
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| #plt.savefig('background_{}.png'.format(b)) | ||
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| plt.show() | ||
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