Automated formatting changes

example/Example-Analysis.py

@@ -337,11 +337,11 @@
 plt.show()
 
 # plot RSI with custom arguments
-rsi(dis, oversold = 20, overbought = 80)
+rsi(dis, oversold=20, overbought=80)
 plt.show()
 
 # plot RSI standalone graph
-rsi(dis, oversold = 20, overbought = 80, standalone=True)
+rsi(dis, oversold=20, overbought=80, standalone=True)
 plt.show()
 
 # <codecell>
@@ -353,9 +353,9 @@
 plt.show()
 
 # plot MACD using custom arguments
-macd(dis, longer_ema_window = 30, shorter_ema_window = 15, signal_ema_window = 10)
+macd(dis, longer_ema_window=30, shorter_ema_window=15, signal_ema_window=10)
 plt.show()
 
 # plot MACD standalone graph
-macd(standlone = True)
+macd(standlone=True)
 plt.show()

finquant/momentum_indicators.py

@@ -4,10 +4,15 @@
 import matplotlib.pyplot as plt
 import pandas as pd
 
-def relative_strength_index(data, window_length: int = 14, oversold: int = 30,
-                            overbought: int = 70, standalone: bool = False) -> None:
 
-    """ Computes and visualizes a RSI graph,
+def relative_strength_index(
+    data,
+    window_length: int = 14,
+    oversold: int = 30,
+    overbought: int = 70,
+    standalone: bool = False,
+) -> None:
+    """Computes and visualizes a RSI graph,
         plotted along with the prices in another sub-graph
         for comparison.
 
@@ -68,24 +73,33 @@ def relative_strength_index(data, window_length: int = 14, oversold: int = 30,
         # Single plot
         fig = plt.figure()
         ax = fig.add_subplot(111)
-        ax.axhline(y = oversold, color = 'g', linestyle = '--')
-        ax.axhline(y = overbought, color = 'r', linestyle ='--')
-        data['rsi'].plot(ylabel = 'RSI', xlabel = 'Date', ax = ax, grid = True)
+        ax.axhline(y=oversold, color="g", linestyle="--")
+        ax.axhline(y=overbought, color="r", linestyle="--")
+        data["rsi"].plot(ylabel="RSI", xlabel="Date", ax=ax, grid=True)
         plt.title("RSI Plot")
         plt.legend()
     else:
         # RSI against price in 2 plots
         fig, ax = plt.subplots(2, 1, sharex=True, sharey=False)
-        ax[0].axhline(y = oversold, color = 'g', linestyle = '--')
-        ax[0].axhline(y = overbought, color = 'r', linestyle ='--')
-        ax[0].set_title('RSI + Price Plot')
+        ax[0].axhline(y=oversold, color="g", linestyle="--")
+        ax[0].axhline(y=overbought, color="r", linestyle="--")
+        ax[0].set_title("RSI + Price Plot")
         # plot 2 graphs in 2 colors
         colors = plt.rcParams["axes.prop_cycle"]()
-        data['rsi'].plot(ylabel = 'RSI', ax = ax[0], grid = True, color = next(colors)["color"], legend=True)
-        data[stock].plot(xlabel = 'Date', ylabel = 'Price', ax = ax[1], grid = True,
-                         color = next(colors)["color"], legend = True)
+        data["rsi"].plot(
+            ylabel="RSI", ax=ax[0], grid=True, color=next(colors)["color"], legend=True
+        )
+        data[stock].plot(
+            xlabel="Date",
+            ylabel="Price",
+            ax=ax[1],
+            grid=True,
+            color=next(colors)["color"],
+            legend=True,
+        )
         plt.legend()
-
+
+
 def macd(
     data,
     longer_ema_window: int = 26,
@@ -121,8 +135,8 @@ def macd(
     if longer_ema_window < shorter_ema_window:
         raise ValueError("longer ema window should be > shorter ema window")
     if longer_ema_window < signal_ema_window:
-        raise ValueError("longer ema window should be > signal ema window")    
-        
+        raise ValueError("longer ema window should be > signal ema window")
+
     # converting data to pd.DataFrame if it is a pd.Series (for subsequent function calls):
     if isinstance(data, pd.Series):
         data = data.to_frame()
@@ -171,9 +185,9 @@ def macd(
 
         for i, key in enumerate(hist.index):
             if hist[key] < 0:
-                ax.bar(data.index[i], hist[key], color = 'orange')
+                ax.bar(data.index[i], hist[key], color="orange")
             else:
-                ax.bar(data.index[i], hist[key], color = 'black')
+                ax.bar(data.index[i], hist[key], color="black")
     else:
         # RSI against price in 2 plots
         fig, ax = plt.subplots(2, 1, sharex=True, sharey=False)
@@ -197,9 +211,9 @@ def macd(
 
         for i, key in enumerate(hist.index):
             if hist[key] < 0:
-                ax.bar(data.index[i], hist[key], color = 'orange')
+                ax.bar(data.index[i], hist[key], color="orange")
             else:
-                ax.bar(data.index[i], hist[key], color = 'black')
+                ax.bar(data.index[i], hist[key], color="black")
 
         data[stock].plot(
             xlabel="Date",

tests/test_momentum_indicators.py

@@ -2,13 +2,12 @@
 import numpy as np
 import pandas as pd
 
-from finquant.momentum_indicators import (
-    relative_strength_index as rsi,
-    macd,
-)
+from finquant.momentum_indicators import macd
+from finquant.momentum_indicators import relative_strength_index as rsi
 
 plt.switch_backend("Agg")
 
+
 def test_rsi():
     x = np.sin(np.linspace(1, 10, 100))
     xlabel_orig = "Date"
@@ -18,23 +17,24 @@ def test_rsi():
     rsi(df)
     # get data from axis object
     ax = plt.gca()
-    # ax.lines[0] is the data we passed to plot_bollinger_band    
+    # ax.lines[0] is the data we passed to plot_bollinger_band
     line1 = ax.lines[0]
     stock_plot = line1.get_xydata()
     xlabel_plot = ax.get_xlabel()
     ylabel_plot = ax.get_ylabel()
     # tests
-    assert (df['Stock'].index.values == stock_plot[:, 0]).all()
+    assert (df["Stock"].index.values == stock_plot[:, 0]).all()
     assert (df["Stock"].values == stock_plot[:, 1]).all()
     assert xlabel_orig == xlabel_plot
     assert ylabel_orig == ylabel_plot
-
+
+
 def test_rsi_standalone():
     x = np.sin(np.linspace(1, 10, 100))
     xlabel_orig = "Date"
     ylabel_orig = "RSI"
-    labels_orig = ['rsi']
-    title_orig = 'RSI Plot'
+    labels_orig = ["rsi"]
+    title_orig = "RSI Plot"
     df = pd.DataFrame({"Stock": x}, index=np.linspace(1, 10, 100))
     df.index.name = "Date"
     rsi(df, standalone=True)
@@ -45,20 +45,21 @@ def test_rsi_standalone():
     rsi_plot = line1.get_xydata()
     xlabel_plot = ax.get_xlabel()
     ylabel_plot = ax.get_ylabel()
-    print (xlabel_plot, ylabel_plot)    
+    print(xlabel_plot, ylabel_plot)
     # tests
-    assert (df['rsi'].index.values == rsi_plot[:, 0]).all()
+    assert (df["rsi"].index.values == rsi_plot[:, 0]).all()
     # for comparing values, we need to remove nan
-    a, b = df['rsi'].values, rsi_plot[:, 1]
+    a, b = df["rsi"].values, rsi_plot[:, 1]
     a, b = map(lambda x: x[~np.isnan(x)], (a, b))
     assert (a == b).all()
     labels_plot = ax.get_legend_handles_labels()[1]
     title_plot = ax.get_title()
     assert labels_plot == labels_orig
     assert xlabel_plot == xlabel_orig
-    assert ylabel_plot == ylabel_orig    
+    assert ylabel_plot == ylabel_orig
     assert title_plot == title_orig
 
+
 def test_macd():
     x = np.sin(np.linspace(1, 10, 100))
     xlabel_orig = "Date"
@@ -68,19 +69,20 @@ def test_macd():
     macd(df)
     # get data from axis object
     ax = plt.gca()
-    # ax.lines[0] is the data we passed to plot_bollinger_band    
+    # ax.lines[0] is the data we passed to plot_bollinger_band
     line1 = ax.lines[0]
     stock_plot = line1.get_xydata()
     xlabel_plot = ax.get_xlabel()
     ylabel_plot = ax.get_ylabel()
     # tests
-    assert (df['Stock'].index.values == stock_plot[:, 0]).all()
+    assert (df["Stock"].index.values == stock_plot[:, 0]).all()
     assert (df["Stock"].values == stock_plot[:, 1]).all()
     assert xlabel_orig == xlabel_plot
     assert ylabel_orig == ylabel_plot
-
+
+
 def test_macd_standalone():
-    labels_orig = ['MACD', 'diff', 'SIGNAL']    
+    labels_orig = ["MACD", "diff", "SIGNAL"]
     x = np.sin(np.linspace(1, 10, 100))
     xlabel_orig = "Date"
     ylabel_orig = "MACD"
@@ -94,12 +96,12 @@ def test_macd_standalone():
     ylabel_plot = ax.get_ylabel()
     assert labels_plot == labels_orig
     assert xlabel_plot == xlabel_orig
-    assert ylabel_plot == ylabel_orig    
+    assert ylabel_plot == ylabel_orig
     # ax.lines[0] is macd data
     # ax.lines[1] is diff data
     # ax.lines[2] is macd_s data
     # tests
-    for i, key in ((0, 'macd'), (1, 'diff'), (2, 'macd_s')):
+    for i, key in ((0, "macd"), (1, "diff"), (2, "macd_s")):
         line = ax.lines[i]
         data_plot = line.get_xydata()
         # tests