def __init__(self, parent=None):
super(Example2, self).__init__(parent)
figure1 = plt.figure(1) # 返回当前的figure
x = [1, 2, 3]
y = [4, 5, 6]
plt.plot(x, y)
plt.title('Example1')
plt.xlabel('x')
plt.ylabel('y')
figure2 = plt.figure(2) # 返回当前的figure
x = [7, 8, 9]
y = [4, 5, 6]
plt.plot(x, y)
plt.title('Example2')
plt.xlabel('x')
plt.ylabel('y')
self.canvas1 = figureCanvas(figure1)
self.canvas2 = figureCanvas(figure2)
self.canvas1.draw()
self.canvas2.draw()
layout = QHBoxLayout(self)
layout.addWidget(self.canvas1)
layout.addWidget(self.canvas2)
def draw_pic(self, radii, result):
if (self.canvas is not None):
self.layout.removeWidget(self.canvas)
figure = plt.gcf() #返回当前的figure
self.canvas = figureCanvas(figure)
radii = [abs(1.0 / i * 20) for i in list(radii)]
ax = axes([0.025, 0.025, 0.95, 0.95],
polar=True) #axes(轴)代表维度,polar用来画极坐标图
N = 10 #元素的个数
theta = np.arange(0.0, 2 * np.pi, 2 * np.pi /
N) # 是一个pi/10的递增的列表#print "theta=%s"%theta
width = np.pi / 4 * np.random.rand(N) #小于4分之1 PI的随机数
bars = plt.bar(theta, radii, width=width, bottom=0.0)
i = 0
for r, bar in zip(radii, bars):
bar.set_facecolor(cm.jet(r / 1000.))
bar.set_alpha(0.5)
height = bar.get_height()
ax.text(bar.get_x() + bar.get_width() / 2., 1.03 * height,
"%s" % result[i])
i += 1
ax.set_xticklabels(["Funcitons"])
ax.set_yticklabels(["possiblitly"
]) # savefig('figure/polar_ex_LSI.png', dpi=48)
self.canvas.draw()
self.layout.addWidget(self.canvas)
def __init__(self, parent=None):
super(Example3, self).__init__(parent)
figure = plt.figure(figsize=(10, 60), facecolor='green', edgecolor='red')
# figsize = (8,4)表示figure的大小，屏幕显示 640 * 320 ， 输出显示 800*400，这个要注意。
# 显示色和外框线条颜色设置。
self.canvas = figureCanvas(figure)
plt.subplot(211) # 子区，2行，2列
x = [1, 2, 3]
y = [4, 5, 6]
plt.plot(x, y)
plt.title('Example')
plt.xlabel('x')
plt.ylabel('y')
plt.subplot(223) # 子区，2行，2列
x = [1, 2, 3]
y = [4, 5, 6]
plt.bar(x, y)
plt.title('Example')
plt.xlabel('x')
plt.ylabel('y')
plt.subplot(224) # 子区，2行，2列
x = [1, 2, 3]
y = [4, 5, 6]
plt.scatter(x, y)
plt.title('Example')
plt.xlabel('x')
plt.ylabel('y')
self.canvas.draw()
layout = QHBoxLayout(self)
layout.addWidget(self.canvas)
def __init__(self, parent):
# super(StocksGraphView, self).__init__(parent)
self.fatherHandle = parent
self.figure = plt.gcf()
self.ax = self.figure.gca()
self.canvas = figureCanvas(self.figure)
self.hintText = self.ax.text(-.5, -.5, "", ha="right", va="baseline", fontdict={"size": 15})
self.figure.canvas.mpl_connect('key_press_event', self._on_key_press)
self.figure.canvas.mpl_connect('button_press_event', self._on_button_press)
# figure.canvas.mpl_disconnect(figure.canvas.manager.key_press_handler_id)
self.figure.canvas.mpl_connect('motion_notify_event', self._on_mouse_move)
self._lines = {}
self._hHintLine = None
self._vHintLine = None
self.ax.fmt_date = matplotlib.dates.DateFormatter('%Y-%m-%d')
self.strpdate2num = matplotlib.dates.strpdate2num('%Y-%m-%d')
plt.subplots_adjust(left=.04, bottom=.0, right=.98, top=.97,
wspace=.0, hspace=.0)
plt.minorticks_on()
self.ax.grid()
self.ax.xaxis.set_major_formatter(matplotlib.dates.DateFormatter('%y\n-\n%m\n-\n%d'))
def createSubOverviewPage(self):
layout = QtGui.QGridLayout()
w = QtGui.QWidget()
sns.set(style="whitegrid")
f, ax = plt.subplots(figsize=(20, 12))
canvas = figureCanvas(f)
canvas.setParent(w)
sns.set(style="whitegrid")
q = QtSql.QSqlQuery("""SELECT EXP_DATE, SUM(AMOUNT), SUM(AMOUNT*(1+EXP_RETURN*(datediff(EXP_DATE, SETTLE_DATE)+1)/36500.0)) FROM LIABILITY WHERE EXP_DATE>='%s' GROUP BY EXP_DATE ORDER BY EXP_DATE"""%self.sysdate.date().toPyDate())
dates, vals = [], []
x_amt = range(0,1000000000,100000000)
while q.next():
dates.append(q.value(0).toDate().toPyDate().isoformat())
vals.append((q.value(1).toDouble()[0], q.value(2).toDouble()[0]))
data = pd.DataFrame(vals, index=dates, columns=['Amount', 'Total Return'])
# Plot the total crashes
sns.set_color_codes("pastel")
sns.barplot(x='Total Return', y=dates, data=data,
label='Interest', color="b")
# Plot the crashes where alcohol was involved
sns.set_color_codes("muted")
sns.barplot(x='Amount', y=dates, data=data,
label="Principal", color="b")
# Add a legend and informative axis label
ax.legend(ncol=2, loc="upper right", frameon=True)
ax.set(ylabel="Maturity Date", title='Liability Overview')
sns.despine(left=True, bottom=True)
layout.addWidget(w, 0, 0, 1, 1)
return layout
def __init__(self, parent=None, tp=1, trade_interval=60):
super(figure, self).__init__(parent)
self.type = tp
figure.fig_num += 1
self.fig_num = figure.fig_num
self.title = ''
self.sid = ''
self.init_figure()
self.interval = del2num(trade_interval)
self.canvas1 = figureCanvas(self.figure1)
self.canvas1.draw()
self.layout = QHBoxLayout(self)
self.layout.addWidget(self.canvas1)
if self.type != figure.CDF_PLOT:
if trade_interval < 60:
self.xlocater = SecondLocator(bysecond=range(0, 60, trade_interval))
self.xformatter = DateFormatter("%H:%M:%S")
else:
self.xlocater = MinuteLocator(byminute=range(0, 60, trade_interval / 60))
self.xformatter = DateFormatter("%H:%M")
else:
if trade_interval < 5:
self.xlocater = SecondLocator(bysecond=range(0, 60, 12 * trade_interval))
self.xformatter = DateFormatter("%H:%M:%S")
else:
self.xlocater = MinuteLocator(byminute=range(0, 60, trade_interval / 5))
self.xformatter = DateFormatter("%H:%M")
def __init__(self,parent=None,year=0,month=0,day=0,stock='0'):
super(cdf_graph,self).__init__(parent)
interval=5
self.data=getHistoricalData(year=year,month=month,day=day,stock=stock,interval=interval)
interval=delta2num(interval)
figure2 = plt.figure(2)
x3 = [ele[0] for ele in self.data]
y3 = getOrderSize(stock)
for i in range(1,len(y3)):
y3[i]=y3[i]+y3[i-1]
y3=[ele/y3[-1] for ele in y3]
ax3=figure2.add_subplot(111)
ax3.xaxis.set_major_locator(minutes)
ax3.xaxis.set_major_formatter(minute_formatter)
line_percent=ax3.plot(x3,y3,'-D',label='Completion Percentage')
figure2.autofmt_xdate()
plt.grid()
plt.legend(loc='upper left')
plt.title('%s'%stock.upper(),fontsize=20)
plt.xlabel('Time',fontsize=20)
plt.ylabel('Completion Percentage',fontsize=15)
self.canvas2 = figureCanvas(figure2)
self.canvas2.draw()
self.toolbar2=NavigationToolBar(self.canvas2,self)
layout = QHBoxLayout(self)
rightLayout=QVBoxLayout(self)
layout.addLayout(rightLayout)
rightLayout.addWidget(self.canvas2)
rightLayout.addWidget(self.toolbar2)
def __init__(self,parent=None):
super(DrawWidget,self).__init__(parent)
figure = plt.gcf() #返回当前的figure
self.canvas = figureCanvas(figure)
x = [1,2,3]
y = [4,5,6]
plt.plot(x,y)
plt.title('Example')
plt.xlabel('x')
plt.ylabel('y')
self.canvas.draw()
layout = QHBoxLayout(self)
layout.addWidget(self.canvas)
def __init__(self,parent=None):
super(Example1,self).__init__(parent)
# 返回当前的figure
figure = plt.gcf()
self.canvas = figureCanvas(figure)
x = [1,2,3]
y = [4,5,6]
plt.plot(x,y)
plt.title('Example')
plt.xlabel('x')
plt.ylabel('y')
self.canvas.draw()
layout = QHBoxLayout(self)
layout.addWidget(self.canvas)
def __init__(self, parent=None):
super(Example4, self).__init__(parent)
figure = plt.figure(figsize=(10, 6), dpi=100, facecolor='white')
canvas = figureCanvas(figure)
x = np.linspace(-np.pi, np.pi, 256, endpoint=True)
c = np.cos(x)
s = np.sin(x)
plt.plot(x, c, color='blue', linewidth=1.0, linestyle='-', label='$cos(x)$') # 设置颜色，线条的格式和粗细
plt.plot(x, s, color='green', linewidth=1.0, linestyle='-', label='$sin(x)$')
ax = plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.spines['bottom'].set_position(('data', 0))
ax.yaxis.set_ticks_position('left')
ax.spines['left'].set_position(('data', 0))
plt.xlim(x.min() * 1.1, x.max() * 1.1) # X轴的范围
plt.xticks([-np.pi, -np.pi / 2, 0, np.pi / 2, np.pi],
[r'$-\pi$', r'$-\pi/2$', r'$0$', r'$\pi/2$', r'$\pi$']) # X轴的刻度值
plt.ylim(s.min() * 1.1, s.max() * 1.1) # Y轴的范围
plt.yticks([-1, 0, 1], [r'$-1$', r'$0$', r'$+1$']) # 设置Y轴的刻度值,第二个参数对其进行格式化
# 添加注释和箭头以及虚线
t = np.pi * 2 / 3
plt.plot([t, t], [0, np.sin(t)], color='red', linewidth=2.5, linestyle='--')
plt.scatter([t], [np.sin(t)], 50, color='red') # 50代表散点的大小，应该是像素值
plt.plot([t, t], [0, np.cos(t)], color='green', linewidth=2.5, linestyle='--')
plt.scatter([t], [np.cos(t)], 50, color='green')
plt.annotate(r'$sin(\frac{2\pi}{3})=(\frac{\sqrt{3}}{2})$',
xy=(t, np.sin(t)), xycoords='data',
xytext=(10, 30), textcoords='offset points', fontsize=16,
arrowprops=dict(arrowstyle='->', connectionstyle='arc3,rad=.1'))
plt.annotate(r'$cos(\frac{2\pi}{3})=(\frac{\sqrt{3}}{2})$',
xy=(t, np.cos(t)), xycoords='data',
xytext=(-120, -30), textcoords='offset points', fontsize=16,
arrowprops=dict(arrowstyle='->', connectionstyle='arc3,rad=.1')) # 后面的参数应该是角度，类似于偏离度，1的时候接近垂直
plt.legend(loc='upper left')
for i in ax.get_xticklabels() + ax.get_yticklabels():
i.set_fontsize(15)
i.set_bbox(dict(facecolor='white', edgecolor='none', alpha=0.65))
canvas.draw()
layout = QHBoxLayout(self)
layout.addWidget(canvas)
def __init__(self, parent=None):
super(DrawWidget3, self).__init__(parent)
figure = plt.figure(figsize=(10, 6), dpi=100, facecolor='white')
canvas = figureCanvas(figure)
plt.axes([0.1, 0.1, 0.5, 0.5])
plt.xticks([])
plt.yticks([])
plt.text(0.2, 0.2, 'hello axes', alpha='0.65', size=16)
plt.text(0.6, 0.4, 'hello axes', alpha='0.65', size=16)
canvas.draw()
layout = QHBoxLayout(self)
layout.addWidget(canvas)
def createSubOverviewPage(self):
layout = QtGui.QGridLayout()
w = QtGui.QWidget()
sns.set(style="whitegrid")
f, ax = plt.subplots(figsize=(20, 12))
canvas = figureCanvas(f)
canvas.setParent(w)
sns.set(style="whitegrid")
q = QtSql.QSqlQuery(
"""SELECT EXP_DATE, SUM(AMOUNT), SUM(AMOUNT*(1+EXP_RETURN*(datediff(EXP_DATE, SETTLE_DATE)+1)/36500.0)) FROM LIABILITY WHERE EXP_DATE>='%s' GROUP BY EXP_DATE ORDER BY EXP_DATE"""
% self.sysdate.date().toPyDate())
dates, vals = [], []
x_amt = range(0, 1000000000, 100000000)
while q.next():
dates.append(q.value(0).toDate().toPyDate().isoformat())
vals.append((q.value(1).toDouble()[0], q.value(2).toDouble()[0]))
data = pd.DataFrame(vals,
index=dates,
columns=['Amount', 'Total Return'])
# Plot the total crashes
sns.set_color_codes("pastel")
sns.barplot(x='Total Return',
y=dates,
data=data,
label='Interest',
color="b")
# Plot the crashes where alcohol was involved
sns.set_color_codes("muted")
sns.barplot(x='Amount',
y=dates,
data=data,
label="Principal",
color="b")
# Add a legend and informative axis label
ax.legend(ncol=2, loc="upper right", frameon=True)
ax.set(ylabel="Maturity Date", title='Liability Overview')
sns.despine(left=True, bottom=True)
layout.addWidget(w, 0, 0, 1, 1)
return layout
def __init__(self, parent):
# super(StocksGraphView, self).__init__(parent)
self.fatherHandle = parent
self.figure = plt.gcf()
self.ax = self.figure.gca()
self.canvas = figureCanvas(self.figure)
self.hintText = self.ax.text(-.5,
-.5,
"",
ha="right",
va="baseline",
fontdict={"size": 15})
self.figure.canvas.mpl_connect('key_press_event', self._on_key_press)
self.figure.canvas.mpl_connect('button_press_event',
self._on_button_press)
# figure.canvas.mpl_disconnect(figure.canvas.manager.key_press_handler_id)
self.figure.canvas.mpl_connect('motion_notify_event',
self._on_mouse_move)
self._lines = {}
self._hHintLine = None
self._vHintLine = None
self.ax.fmt_date = matplotlib.dates.DateFormatter('%Y-%m-%d')
self.strpdate2num = matplotlib.dates.strpdate2num('%Y-%m-%d')
plt.subplots_adjust(left=.04,
bottom=.0,
right=.98,
top=.97,
wspace=.0,
hspace=.0)
plt.minorticks_on()
self.ax.grid()
self.ax.xaxis.set_major_formatter(
matplotlib.dates.DateFormatter('%y\n-\n%m\n-\n%d'))
def __init__(self, parent=None):
super(DrawWidget, self).__init__(parent)
figure = plt.gcf()
x = [1, 2, 3, 3]
y = [4, 5, 5, 6]
t = np.arange(0., 5., 0.2)
# plt.plot(t, t, 'g--', t, t*2, 'bs', t, t**2, 'r^')
# plt.axis([-2, 10, -2, 30])
# # 是指定xy坐标的起始范围，它的参数是列表[xmin, xmax, ymin, ymax]。
# plt.text(2, .25, r'$\mu=100,\ \sigma=15$')
# plt.title('example')
# plt.xlabel('x')
# plt.ylabel('y')
self.xxlineH = None
self.xxlineV = None
self.xxax = figure.gca()
# fig, ax = plt.subplots(1)
# np.random.seed(14)
x = ppl.plot(figure.gca(), t, t, '--', color=(255/255.,150/255.,250/255.), label=str('t, t'), pickradius=28.0)
ppl.plot(figure.gca(), t, t*2, label=str(' t, t*2'), pickradius=8.0)
ppl.plot(figure.gca(), t, t**2, label=str('t, t**2'), pickradius=8.0)
ppl.legend(figure.gca(), loc='upper left', ncol=3)
# figure.gca().lines.remove(x[0])
# ax = plt.gca()#移动坐标轴
# ax.spines['right'].set_color('none')#去除右边的轴
# ax.spines['top'].set_color('none')#去除顶轴
# ax.xaxis.set_ticks_position('bottom')
# #下轴移至数据0点，理想状态下0点为中心点，具体跟数据位置有关
# ax.spines['bottom'].set_position(('data', 0))
# ax.yaxis.set_ticks_position('left')
# ax.spines['left'].set_position(('data', 0))
# plt.xlim(t.min()*1.1, t.max()*1.1)#X轴的范围
# plt.xticks([-np.pi, -np.pi/2, 0, np.pi/2, np.pi],#从新定义刻度
# [r'$-\pi$',r'$-\pi/2$',r'$0$',r'$\pi/2$',r'$\pi$'])#X轴的刻度值
# plt.ylim(s.min()*1.1,s.max()*1.1)#Y轴的范围
# plt.yticks([-1,0,1],[r'$-1$',r'$0$',r'$+1$']) #设置Y轴的刻度值,第二个参数对其进行格式化
plt.annotate(r'$sin(\frac{2\pi}{3})=(\frac{\sqrt{3}}{2})$',
xy=(5, 5), xycoords='data',
xytext=(15, 200), textcoords='offset points', fontsize=16,
arrowprops = dict(arrowstyle='->', connectionstyle='arc3,rad=.1'))
plt.plot([5, 5], [0, 5], 'ro', color='black', linewidth=1.0, linestyle='--', label='$cos(x)$')
# plt.plot([5, 5], [0, 5],'ro', linewidth=5.0, label='$sin(x)$')
# plt.scatter([5, 5], [0, 5], 50, color='red')
# for i in ax.get_xticklabels() + ax.get_yticklabels():#从新设置所有bbox
# i.set_fontsize(15)
# i.set_bbox(dict(facecolor='white',edgecolor='none',alpha=0.65))
# 'button_press_event':鼠标按键按下时触发
# 'button_release_event':鼠标按键释放时触发
# 'motion_notify_event':鼠标移动时触发
# 当前的所有注册的响应函数可以通过Figure.canvas.callbacks.callbacks
for key, funcs in figure.canvas.callbacks.callbacks.iteritems():
print key
for cid, wrap in sorted(funcs.items()):
func = wrap.func
print " {0}:{1}.{2}".format(cid, func.__module__, func)
self.text = figure.gca().text(0.5, 10.5, "event", ha="center", va="center", fontdict={"size":20})
self.canvas = figureCanvas(figure)
self.canvas.setFocusPolicy( QtCore.Qt.ClickFocus) ##qt4需要加这两句，否者信号被qt拦截，无法到达matplot
self.canvas.setFocus()
figure.canvas.mpl_connect('key_press_event', self.on_key_press)
# figure.canvas.mpl_disconnect(figure.canvas.manager.key_press_handler_id)
figure.canvas.mpl_connect('motion_notify_event', self.on_mouse_move)
self.canvas.draw()
figure2 = plt.figure(2, figsize=(8, 4), facecolor='green', edgecolor='red')
#figsize = (8,4)表示figure的大小，屏幕显示 640 * 320 ， 输出显示 800*400，这个要注意。
#显示色和外框线条颜色设置。
self.canvas2 = figureCanvas(figure2)
plt.subplot(311)# 子区，3行，1列, 第1个
y = [1, 2, 3, 4]
x = [4, 5, 5, 6]
plt.plot(x, y, 'bo', x, y, 'r')
plt.title('examrple2')
plt.xlabel('x')
plt.ylabel('y')
plt.subplot(323)# 子区，3行，2列, 第3个
x = [1, 2, 3]
y = [4, 5, 6]
plt.bar(x, y)
plt.title('Example3')
plt.xlabel('x')
plt.ylabel('y')
plt.subplot(336)# 子区，3行，3列, 第6个
x = [1, 2, 3]
y = [4, 5, 6]
plt.scatter(x, y)
plt.title('Example4')
plt.xlabel('x')
plt.ylabel('y')
plt.subplot(313)# 子区，3行，1列, 第3个
mu, sigma = 100, 15
x = mu + sigma*np.random.randn(10000)
# the histogram of the data
n, bins, patches = plt.hist(x, 150, normed=1, facecolor='g', alpha=0.75)
plt.xlabel('Smarts')
plt.ylabel('Probability')
plt.title('Histogram of IQ')
plt.text(60, .025, r'$\mu=100,\ \sigma=15$')
plt.axis([40, 160, 0, 0.03])
plt.grid(True)
# import prettyplotlib as ppl
# fig, ax = plt.subplots(1)
# np.random.seed(14)
# n = 10
# ppl.bar(plt.gca(), np.arange(n), np.abs(np.random.randn(n)), annotate=True, grid='y')
layout = QtGui.QHBoxLayout(self)
layout.addWidget(self.canvas)
layout.addWidget(self.canvas2)
self.canvas2.draw()
"""
实验数据x, y和拟合函数之间的差，p为拟合需要找到的系数
"""
return y - func(x, p)
x = np.linspace(0, -2*np.pi, 100)
A, k, theta = 10, 0.34, np.pi/6 # 真实数据的函数参数
y0 = func(x, [A, k, theta]) # 真实数据
y1 = y0 + 2 * np.random.randn(len(x)) # 加入噪声之后的实验数据
p0 = [7, 0.2, 0] # 第一次猜测的函数拟合参数
# 调用leastsq进行数据拟合
# residuals为计算误差的函数
# p0为拟合参数的初始值
# args为需要拟合的实验数据
plsq = leastsq(residuals, p0, args=(y1, x))
print u"真实参数:", [A, k, theta]
print u"拟合参数", plsq[0] # 实验数据拟合后的参数
figure = plt.gcf()
figureCanvas(figure)
plt.plot(x, y0, label=u"真实数据")
plt.plot(x, y1, label=u"带噪声的实验数据")
plt.plot(x, func(x, plsq[0]), label=u"拟合数据")
plt.legend()
plt.show()
from scipy.stats import pearsonr
def __init__(self, parent=None, stock='sz002024', year=0, month=0, day=0):
super(graph, self).__init__(parent)
interval = 5
self.data = getHistoricalData(stock,
year,
month,
day,
interval=interval)
interval = delta2num(interval)
figure1 = plt.figure(1) #返回当前的figure
x = [ele[0] for ele in self.data]
y = [ele[1] for ele in self.data]
tm = datetime(year, month, day, 11, 30, 0)
ta = datetime(year, month, day, 13, 0, 0)
morningend = date2num(tm)
afternoonbegin = date2num(ta)
c = 0
x01 = []
x02 = []
y01 = []
y02 = []
for ele in x:
if ele <= morningend:
x01.append(ele)
y01.append(y[c])
elif ele >= afternoonbegin:
x02.append(ele)
y02.append(y[c])
c = c + 1
ymax = max(y)
ymin = min(y)
x1 = [ele + interval * 0.1 for ele in x]
y1 = [ele[3] for ele in self.data]
s = sum(y1)
y1 = [ele / s * 100 for ele in y1]
y1max = max(y1)
x2 = [ele + interval * 0.5 for ele in x]
print(len(x2))
y2 = getOrderSize(stock)
y2 = [ele * 100 for ele in y2]
y1max = max(y1max, max(y2))
#ratio=0.3
#y2 = [ele*sum(y1)*ratio for ele in y2]
ax1 = figure1.add_subplot(111)
ax1.xaxis.set_major_locator(minutes)
ax1.xaxis.set_major_formatter(minute_formatter)
plt.ylabel('Volume(%)', fontsize=15)
plt.ylim([0, y1max * 1.5])
plt.xlabel('Time', fontsize=15)
ax2 = ax1.twinx()
bar_history = ax1.bar(x1,
y1,
width=interval * 0.4,
color='c',
label='Historical Volume')
bar_order = ax1.bar(x2,
y2,
width=interval * 0.4,
color=[1, 0.4, 0.6],
label='Order Size')
line_price, = ax2.plot(x01, y01, color='b', label='Price')
ax2.plot(x02, y02, color='b')
plt.title('%s' % stock.upper(), fontsize=20)
plt.ylabel('Price', fontsize=15)
plt.ylim([ymin - 2 * (ymax - ymin), ymax + 0.25 * (ymax - ymin)])
figure1.autofmt_xdate()
plt.grid()
plt.legend(handles=(line_price, bar_history, bar_order),
loc='upper right',
ncol=3)
#plt.legend(handles=(bar_history,),bbox_to_anchor=(0.5,-0.25),loc='lower center')
plt.tight_layout()
#plt.autoscale(tight=True)
self.canvas1 = figureCanvas(figure1)
self.canvas1.draw()
self.toolbar1 = NavigationToolBar(self.canvas1, self)
layout = QHBoxLayout(self)
leftLayout = QVBoxLayout(self)
rightLayout = QVBoxLayout(self)
layout.addLayout(leftLayout)
#layout.addLayout(rightLayout)
leftLayout.addWidget(self.canvas1)
leftLayout.addWidget(self.toolbar1)
实验数据x, y和拟合函数之间的差，p为拟合需要找到的系数
"""
return y - func(x, p)
x = np.linspace(0, -2 * np.pi, 100)
A, k, theta = 10, 0.34, np.pi / 6 # 真实数据的函数参数
y0 = func(x, [A, k, theta]) # 真实数据
y1 = y0 + 2 * np.random.randn(len(x)) # 加入噪声之后的实验数据
p0 = [7, 0.2, 0] # 第一次猜测的函数拟合参数
# 调用leastsq进行数据拟合
# residuals为计算误差的函数
# p0为拟合参数的初始值
# args为需要拟合的实验数据
plsq = leastsq(residuals, p0, args=(y1, x))
print u"真实参数:", [A, k, theta]
print u"拟合参数", plsq[0] # 实验数据拟合后的参数
figure = plt.gcf()
figureCanvas(figure)
plt.plot(x, y0, label=u"真实数据")
plt.plot(x, y1, label=u"带噪声的实验数据")
plt.plot(x, func(x, plsq[0]), label=u"拟合数据")
plt.legend()
plt.show()
from scipy.stats import pearsonr
def __init__(self,parent=None,stock='0',year=0,month=0,day=0,alg='TVWAP'):
super(graph,self).__init__(parent)
interval=5
self.data=getHistoricalData(stock,year,month,day,interval=interval)
interval=delta2num(interval)
figure1 = plt.figure(1) #返回当前的figure
x = [ele[0] for ele in self.data]
y = [ele[1] for ele in self.data]
tm=datetime(year,month,day,11,30,0)
ta=datetime(year,month,day,13,0,0)
morningend=date2num(tm)
afternoonbegin=date2num(ta)
c=0;
x01=[];x02=[];
y01=[];y02=[];
for ele in x:
if ele<=morningend:
x01.append(ele)
y01.append(y[c])
elif ele>=afternoonbegin:
x02.append(ele)
y02.append(y[c])
c=c+1
if alg=='TVWAP':
ymax=max(y);ymin=min(y)
x1 = [ele+interval*0.1 for ele in x]
y1 = [ele[2] for ele in self.data]
s=sum(y1)
y1max=max(y1)
x2 = [ele+interval*0.5 for ele in x]
print(len(x2))
y2 = getOrderSize(stock)
y2 = [ele*s/10 for ele in y2]
y1max=max(y1max,max(y2))
elif alg=='VWAP':
ymax=max(y);ymin=min(y)
x1 = [ele+interval*0.1 for ele in x]
y1 = [ele[2] for ele in self.data]
s=sum(y1)
y1max=max(y1)
x2 = [ele+interval*0.5 for ele in x]
print(len(x2))
y2 = self.__getOrderSize()
elif alg=='TWAP':
ymax=max(y);ymin=min(y)
x1 = [ele+interval*0.1 for ele in x]
y1 = [ele[2] for ele in self.data]
s=sum(y1)
y1=[ele for ele in y1]
y1max=max(y1)
x2 = [ele+interval*0.5 for ele in x]
print(len(x2))
y2 = []
for ele in range(len(y1)):
y2.append(s/len(y1)/5)
#ratio=0.3
#y2 = [ele*sum(y1)*ratio for ele in y2]
ax1=figure1.add_subplot(111)
# ax1.xaxis.set_major_locator(minutes)
# ax1.xaxis.set_major_formatter(minute_formatter)
plt.ylabel('Volume',fontsize=15)
plt.ylim([0,y1max*1.5])
plt.xlabel('Time',fontsize=15)
ax2=ax1.twinx()
# if alg=='TVWAP':
# bar_history=ax1.bar(x1,y1,width=interval*0.4,color='c',label='Historical Volume')
# else:
# bar_history=ax1.bar(x1,y1,width=interval*0.4,color='c',label='Volume')
# bar_order=ax1.bar(x2,y2,width=interval*0.4,color=[1,0.4,0.6],label='Order Size')
x01=[736321.3958912037, 736321.3959606482, 736321.3959953703, 736321.3961342593, 736321.3962037037, 736321.3962731481, 736321.3964120371, 736321.3964814815, 736321.3965509259, 736321.3965856482, 736321.3966898149, 736321.3967592593, 736321.3969328704, 736321.3971759259, 736321.3973842593, 736321.3974537037, 736321.397488426, 736321.3975578704, 736321.397662037, 736321.3977314815, 736321.3977662037, 736321.3979398148, 736321.3993634259, 736321.399675926, 736321.3997106481, 736321.3998148148, 736321.3999189815, 736321.3999884259, 736321.4000578703, 736321.4000925926, 736321.4002662037, 736321.4003703704, 736321.4005439815, 736321.4006134259, 736321.400787037, 736321.4008217592, 736321.4008912037, 736321.4010300926, 736321.4011689815, 736321.4012731481, 736321.4013078704, 736321.4013773148, 736321.4014814815, 736321.4015162037, 736321.4015509259, 736321.4015856482, 736321.401863426, 736321.4019675925, 736321.4027893519, 736321.402962963, 736321.4031018518, 736321.4031712963, 736321.4032407408, 736321.4033101852, 736321.4033796296, 736321.403587963, 736321.4036226852, 736321.4036921297, 736321.4037615741, 736321.4040046296, 736321.404212963, 736321.4044212963, 736321.4044560185, 736321.4044907407, 736321.404525463, 736321.4046990741, 736321.4047337963, 736321.4065162037, 736321.406724537, 736321.4068981481, 736321.4069328704, 736321.4069675925, 736321.4070023148, 736321.4070370371, 736321.4071412038, 736321.4098148148, 736321.4099189815, 736321.4099537038, 736321.4099884259, 736321.4134953704, 736321.413599537, 736321.4136689815, 736321.4141203704, 736321.4142245371, 736321.4142939815, 736321.4143287037, 736321.4143981482, 736321.4145717593, 736321.414675926, 736321.4147453704, 736321.4150578703, 736321.4152546297, 736321.415300926, 736321.4153587963, 736321.4155671296, 736321.415636574, 736321.4157060186, 736321.4160185185, 736321.4160879629, 736321.4168171296, 736321.4168865741, 736321.417199074, 736321.4176851852, 736321.4177893519, 736321.4178587963, 736321.4182060185, 736321.4182407408, 736321.4185532407, 736321.4168171296, 736321.4168865741, 736321.417199074, 736321.4176851852, 736321.4177893519, 736321.4178587963, 736321.4182060185, 736321.4182407408, 736321.4185532407, 736321.4187268518, 736321.4187962963, 736321.4189699074, 736321.4190509259, 736321.4190856481, 736321.4191898148, 736321.4192939815, 736321.4193634259, 736321.4193981482, 736321.4194328703, 736321.419537037, 736321.4195717593, 736321.4196412037, 736321.4197106481, 736321.4198842592, 736321.4199189815]
y01=[0.001, 0.002, 0.003, 0.004, 0.005, 0.006, 0.007, 0.008, 0.009, 0.01, 0.011, 0.012, 0.013, 0.014, 0.015, 0.016, 0.017, 0.018, 0.019, 0.02, 0.021, 0.0215, 0.023, 0.0245, 0.026, 0.0275, 0.029, 0.0305, 0.032, 0.0335, 0.035, 0.0365, 0.038, 0.0395, 0.041, 0.0425, 0.044, 0.0455, 0.047, 0.0485, 0.05, 0.0515, 0.053, 0.0545, 0.056, 0.0575, 0.059, 0.06, 0.0605, 0.061, 0.0615, 0.062, 0.0625, 0.063, 0.0635, 0.064, 0.0645, 0.065, 0.0655, 0.066, 0.0665, 0.067, 0.0675, 0.068, 0.0685, 0.069, 0.0695, 0.07, 0.0705, 0.071, 0.0715, 0.072, 0.0725, 0.073, 0.0735, 0.074, 0.0745, 0.075, 0.0755, 0.0775, 0.0795, 0.0815, 0.0835, 0.0855, 0.0875, 0.0895, 0.0915, 0.0935, 0.0955, 0.0975, 0.0995, 0.1015, 0.1035, 0.1055, 0.1075, 0.1095, 0.1115, 0.1135, 0.1155, 0.1175, 0.1195, 0.1215, 0.1235, 0.1255, 0.1275, 0.1295, 0.1315, 0.1325, 0.135, 0.1375, 0.14, 0.1425, 0.145, 0.1475, 0.15, 0.1525, 0.155, 0.1575, 0.16, 0.1625, 0.165, 0.1675, 0.17, 0.1725, 0.175, 0.1775, 0.18, 0.1825, 0.185, 0.1875, 0.19, 0.1925, 0.195]
line_price,=ax2.plot(x01,y01,color='b',label='Price')
# ax2.plot(x02,y02,color='b')
plt.title('%s'%stock.upper(),fontsize=20)
plt.ylabel('Price',fontsize=15)
plt.ylim([ymin-2*(ymax-ymin),ymax+0.25*(ymax-ymin)])
# figure1.autofmt_xdate()
plt.grid()
# plt.legend(handles=(line_price,bar_history,bar_order),loc='upper right',ncol=3)
#plt.legend(handles=(bar_history,),bbox_to_anchor=(0.5,-0.25),loc='lower center')
plt.tight_layout()
plt.autoscale(tight=True)
self.canvas1 = figureCanvas(figure1)
self.canvas1.draw()
self.toolbar1=NavigationToolBar(self.canvas1,self)
layout = QHBoxLayout(self)
leftLayout=QVBoxLayout(self)
rightLayout=QVBoxLayout(self)
layout.addLayout(leftLayout)
#layout.addLayout(rightLayout)
leftLayout.addWidget(self.canvas1)
leftLayout.addWidget(self.toolbar1)
def __init__(self, parent=None):
super(DrawWidget2, self).__init__(parent)
figure = plt.figure(figsize=(10, 6), dpi=100, facecolor='white')
canvas = figureCanvas(figure)
x = np.linspace(-np.pi, np.pi, 256, endpoint=True)
c = np.cos(x)
s = np.sin(x)
plt.plot(x,
c,
color='blue',
linewidth=1.0,
linestyle='-',
label='$cos(x)$') # 设置颜色，线条的格式和粗细
plt.plot(x,
s,
color='green',
linewidth=1.0,
linestyle='-',
label='$sin(x)$')
ax = plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.spines['bottom'].set_position(('data', 0))
ax.yaxis.set_ticks_position('left')
ax.spines['left'].set_position(('data', 0))
plt.xlim(x.min() * 1.1, x.max() * 1.1) # X轴的范围
plt.xticks(
[-np.pi, -np.pi / 2, 0, np.pi / 2, np.pi],
[r'$-\pi$', r'$-\pi/2$', r'$0$', r'$\pi/2$', r'$\pi$']) # X轴的刻度值
plt.ylim(s.min() * 1.1, s.max() * 1.1) # Y轴的范围
plt.yticks([-1, 0, 1],
[r'$-1$', r'$0$', r'$+1$']) # 设置Y轴的刻度值,第二个参数对其进行格式化
# 添加注释和箭头以及虚线
t = np.pi * 2 / 3
plt.plot([t, t], [0, np.sin(t)],
color='red',
linewidth=2.5,
linestyle='--')
plt.scatter([t], [np.sin(t)], 50, color='red') # 50代表散点的大小，应该是像素值
plt.plot([t, t], [0, np.cos(t)],
color='green',
linewidth=2.5,
linestyle='--')
plt.scatter([t], [np.cos(t)], 50, color='green')
plt.annotate(r'$sin(\frac{2\pi}{3})=(\frac{\sqrt{3}}{2})$',
xy=(t, np.sin(t)),
xycoords='data',
xytext=(10, 30),
textcoords='offset points',
fontsize=16,
arrowprops=dict(arrowstyle='->',
connectionstyle='arc3,rad=.1'))
plt.annotate(
r'$cos(\frac{2\pi}{3})=(\frac{\sqrt{3}}{2})$',
xy=(t, np.cos(t)),
xycoords='data',
xytext=(-120, -30),
textcoords='offset points',
fontsize=16,
arrowprops=dict(
arrowstyle='->',
connectionstyle='arc3,rad=.1')) # 后面的参数应该是角度，类似于偏离度，1的时候接近垂直
plt.legend(loc='upper left')
for i in ax.get_xticklabels() + ax.get_yticklabels():
i.set_fontsize(15)
i.set_bbox(dict(facecolor='white', edgecolor='none', alpha=0.65))
canvas.draw()
layout = QHBoxLayout(self)
layout.addWidget(canvas)
