improved

git-svn-id: http://moon:8086/svn/projects/Stock@302 fda53097-d464-4ada-af97-ba876c37ca34

date_plot.py

@@ -0,0 +1,40 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.dates as mdates
+import matplotlib.cbook as cbook
+
+years = mdates.YearLocator()   # every year
+months = mdates.MonthLocator()  # every month
+years_fmt = mdates.DateFormatter('%Y')
+
+# Load a numpy structured array from yahoo csv data with fields date, open,
+# close, volume, adj_close from the mpl-data/example directory.  This array
+# stores the date as an np.datetime64 with a day unit ('D') in the 'date'
+# column.
+with cbook.get_sample_data('/home/jens/Downloads/goog.npz') as datafile:
+    data = np.load(datafile)['price_data']
+
+print (data)
+fig, ax = plt.subplots()
+ax.plot('date', 'adj_close', data=data)
+
+# format the ticks
+ax.xaxis.set_major_locator(years)
+ax.xaxis.set_major_formatter(years_fmt)
+ax.xaxis.set_minor_locator(months)
+
+# round to nearest years.
+datemin = np.datetime64(data['date'][0], 'Y')
+datemax = np.datetime64(data['date'][-1], 'Y') + np.timedelta64(1, 'Y')
+ax.set_xlim(datemin, datemax)
+
+# format the coords message box
+ax.format_xdata = mdates.DateFormatter('%Y-%m-%d')
+ax.format_ydata = lambda y: '$%1.2f' % y  # format the price.
+ax.grid(True)
+
+# rotates and right aligns the x labels, and moves the bottom of the
+# axes up to make room for them
+fig.autofmt_xdate()
+
+plt.show()

mpl_test.py

@@ -0,0 +1,25 @@
+from matplotlib import pyplot as plt
+
+class LineBuilder:
+    def __init__(self, line):
+        self.line = line
+        self.xs = list(line.get_xdata())
+        self.ys = list(line.get_ydata())
+        self.cid = line.figure.canvas.mpl_connect('button_press_event', self)
+
+    def __call__(self, event):
+        print('click', event)
+        if event.inaxes!=self.line.axes: return
+        self.xs.append(event.xdata)
+        self.ys.append(event.ydata)
+        self.line.set_data(self.xs, self.ys)
+        self.line.figure.canvas.draw()
+
+fig = plt.figure()
+ax = fig.add_subplot(111)
+ax.set_title('click to build line segments')
+line, = ax.plot([0], [0])  # empty line
+linebuilder = LineBuilder(line)
+
+plt.show()
+

pandas_eval.py

@@ -101,9 +101,14 @@ titles.append('AAPL')
 titles.append('XLNX')
 titles.append('QCOM')
 titles.append('DPW.DE')
+titles.append('CSCO')
+titles.append('AIR')
 
-for title in titles:
+show_title = 'QCOM'
+show_range_days = 20
 
+pd.DatetimeIndex
+def fetch(title):
 	filename = title + '.h5'
 	fetch = False
 	today = dt.date.today()
@@ -111,11 +116,14 @@ for title in titles:
 	try:
 		hdf = pd.HDFStore(filename, 'r')
 		hdf.close()
-	except IOError as e:
+	except:
 		fetch = True
 
-	lastmodified = dt.datetime.fromtimestamp(os.stat(filename).st_mtime).date()
+	try:
-	if lastmodified != today:
+		lastmodified = dt.datetime.fromtimestamp(os.stat(filename).st_mtime).date()
+		if lastmodified != today:
+			fetch = True
+	except:
 		fetch = True
 
 	if fetch:
@@ -131,30 +139,60 @@ for title in titles:
 		data = hdf[title]
 	hdf.close()
 
+def show(title):
 
-data['ema'] = ema(data, key='close', alpha=0.75)
+	k_euro = 1/1.11
-data['macd'] = macd(data, key='close')
-data['sma'] = sma(data, key='close', window_days=30)
-boll = bollinger(data, window_days=30)
 
-plt.subplot(311)
+	filename = title + '.h5'
-plt.title(title)
-data['close'].plot()
-data['ema'].plot()
-data['sma'].plot()
-plt.legend()
-plt.grid()
 
-plt.subplot(312)
+	hdf = pd.HDFStore(filename, 'r')
-boll['upper'].plot()
+	data_full = hdf[title]*k_euro
-boll['mid'].plot()
-boll['lower'].plot()
-plt.legend()
-plt.grid()
 
-plt.subplot(313)
+	data_full['ema'] = ema(data_full, key='close', alpha=0.75)
-data['macd'].plot()
+	data_full['macd'] = macd(data_full, key='close')
-plt.legend()
+	data_full['sma'] = sma(data_full, key='close', window_days=30)
-plt.grid()
+	boll = bollinger(data_full, window_days=30)
+	hdf.close()
 
-plt.show()
+	data = data_full[len(data_full)-1 - show_range_days:]
+	dates = data.index
+
+	fig = plt.figure(1)
+
+	ax = plt.subplot(311)
+
+	def hover(event):
+		if event.inaxes == ax:
+			x_idx = int(event.xdata)
+			ax.format_xdata = lambda x: dates[x_idx]
+			ax.format_ydata = lambda y: '{:.2f}'.format(data['close'][x_idx])
+
+	fig.canvas.mpl_connect("motion_notify_event", hover)
+
+	data['close'].plot()
+	data['ema'].plot()
+	data['sma'].plot()
+	plt.title(title)
+	plt.legend()
+	plt.grid()
+
+	plt.subplot(312)
+	boll['upper'].plot()
+	boll['mid'].plot()
+	boll['lower'].plot()
+	plt.legend()
+	plt.grid()
+
+	plt.subplot(313)
+	data['macd'].plot()
+	plt.legend()
+	plt.grid()
+
+	plt.show()
+
+
+
+for title in titles:
+	fetch(title)
+
+show(show_title)

picker.py

@@ -0,0 +1,39 @@
+"""
+compute the mean and stddev of 100 data sets and plot mean vs stddev.
+When you click on one of the mu, sigma points, plot the raw data from
+the dataset that generated the mean and stddev
+"""
+import numpy as np
+import matplotlib.pyplot as plt
+
+X = np.random.rand(100, 1000)
+xs = np.mean(X, axis=1)
+ys = np.std(X, axis=1)
+
+fig = plt.figure()
+ax = fig.add_subplot(111)
+ax.set_title('click on point to plot time series')
+line, = ax.plot(xs, ys, 'o', picker=5)  # 5 points tolerance
+
+
+def onpick(event):
+
+    if event.artist!=line: return True
+
+    N = len(event.ind)
+    if not N: return True
+
+
+    figi = plt.figure()
+    for subplotnum, dataind in enumerate(event.ind):
+        ax = figi.add_subplot(N,1,subplotnum+1)
+        ax.plot(X[dataind])
+        ax.text(0.05, 0.9, 'mu=%1.3f\nsigma=%1.3f'%(xs[dataind], ys[dataind]),
+                transform=ax.transAxes, va='top')
+        ax.set_ylim(-0.5, 1.5)
+    figi.show()
+    return True
+
+fig.canvas.mpl_connect('pick_event', onpick)
+
+plt.show()