import time
from math import pi
import pandas as pd
from bokeh.io import output_notebook
from bokeh.plotting import figure, show
from bokeh.models import ColumnDataSource, Rect, HoverTool, Range1d, LinearAxis, WheelZoomTool, PanTool, ResetTool, ResizeTool, PreviewSaveTool
output_notebook()

quotes = get_price('000001.XSHE', start_date='2016-01-01', end_date='2016-7-09', frequency='daily',skip_paused=False)
quotes[quotes['volume']==0]=np.nan
quotes= quotes.dropna()
openp=quotes['open']
closep=quotes['close']
highp=quotes['high']
lowp=quotes['low']
volume=quotes['volume']
time=quotes.index
date=[x.strftime("%Y-%m-%d") for x in quotes.index]
quotes['date']=date

w = 12*60*60*1000 # half day in ms
mids = (openp + closep)/2
spans = abs(closep-openp)
inc = closep > openp
dec = openp > closep
ht = HoverTool(tooltips=[
            ("date", "@date"),
            ("open", "@open"),
            ("close", "@close"),
            ("high", "@high"),
            ("low", "@low"),
            ("volume", "@volume"),
            ("money", "@money"),])
TOOLS = [ht, WheelZoomTool(dimensions=['width']), ResizeTool(), ResetTool(),PanTool(dimensions=['width']), PreviewSaveTool()]

max_x = max(highp)
min_x = min(lowp)
x_range = max_x - min_x  
y_range = (min_x - x_range / 2.0, max_x + x_range * 0.1)  
p = figure(x_axis_type="datetime", tools=TOOLS, plot_height=600, plot_width=950,toolbar_location="above", y_range=y_range)

p.xaxis.major_label_orientation = pi/4
p.grid.grid_line_alpha=0.3
p.background_fill = "black"

quotesdate=dict(date1=quotes['date'],open1=openp,close1=closep,high1=highp,low1=lowp)
ColumnDataSource(quotesdate)
x_rect_inc_src =ColumnDataSource(quotes[inc])
x_rect_dec_src =ColumnDataSource(quotes[dec])

p.rect(time[inc], mids[inc], w, spans[inc], fill_color="red", line_color="red", source=x_rect_inc_src)
p.rect(time[dec], mids[dec], w, spans[dec], fill_color="green", line_color="green", source=x_rect_dec_src)
p.segment(time[inc], highp[inc], time[inc], lowp[inc], color="red")
p.segment(time[dec], highp[dec], time[dec], lowp[dec], color="green")
show(p)

import matplotlib.pyplot as plt
import matplotlib as mat
import numpy as np
import datetime as dt
import matplotlib.pyplot as plt

quotes = get_price('000001.XSHG', start_date='2016-01-01', end_date='2016-07-09', frequency='daily',skip_paused=False,fq='pre')
quotes[quotes['volume']==0]=np.nan
quotes= quotes.dropna()
Close=quotes['close']
Open=quotes['open']
High=quotes['high']
Low=quotes['low']
T0 = quotes.index.values

length=len(Close)

fig = plt.figure(figsize=(16, 8))
ax1 = plt.subplot2grid((10,4),(0,0),rowspan=10,colspan=4)
#fig = plt.figure()
#ax1 = plt.axes([0,0,3,2])

X=np.array(range(0, length))
pad_nan=X+nan

    #计算上 下影线
max_clop=Close.copy()
max_clop[Close<Open]=Open[Close<Open]
min_clop=Close.copy()
min_clop[Close>Open]=Open[Close>Open]

    #上影线
line_up=np.array([High,max_clop,pad_nan])
line_up=np.ravel(line_up,'F')
    #下影线
line_down=np.array([Low,min_clop,pad_nan])
line_down=np.ravel(line_down,'F')

    #计算上下影线对应的X坐标
pad_nan=nan+X
pad_X=np.array([X,X,X])
pad_X=np.ravel(pad_X,'F')


    #画出实体部分,先画收盘价在上的部分
up_cl=Close.copy()
up_cl[Close<=Open]=nan
up_op=Open.copy()
up_op[Close<=Open]=nan

down_cl=Close.copy()
down_cl[Open<=Close]=nan
down_op=Open.copy()
down_op[Open<=Close]=nan


even=Close.copy()
even[Close!=Open]=nan

    #画出收红的实体部分
pad_box_up=np.array([up_op,up_op,up_cl,up_cl,pad_nan])
pad_box_up=np.ravel(pad_box_up,'F')
pad_box_down=np.array([down_cl,down_cl,down_op,down_op,pad_nan])
pad_box_down=np.ravel(pad_box_down,'F')
pad_box_even=np.array([even,even,even,even,pad_nan])
pad_box_even=np.ravel(pad_box_even,'F')

    #X的nan可以不用与y一一对应
X_left=X-0.25
X_right=X+0.25
box_X=np.array([X_left,X_right,X_right,X_left,pad_nan])
box_X=np.ravel(box_X,'F')




    #Close_handle=plt.plot(pad_X,line_up,color='k') 

vertices_up=array([box_X,pad_box_up]).T
vertices_down=array([box_X,pad_box_down]).T
vertices_even=array([box_X,pad_box_even]).T

handle_box_up=mat.patches.Polygon(vertices_up,color='r',zorder=1)
handle_box_down=mat.patches.Polygon(vertices_down,color='g',zorder=1)
handle_box_even=mat.patches.Polygon(vertices_even,color='k',zorder=1)

ax1.add_patch(handle_box_up)
ax1.add_patch(handle_box_down)
ax1.add_patch(handle_box_even)

handle_line_up=mat.lines.Line2D(pad_X,line_up,color='k',linestyle='solid',zorder=0) 
handle_line_down=mat.lines.Line2D(pad_X,line_down,color='k',linestyle='solid',zorder=0) 

ax1.add_line(handle_line_up)
ax1.add_line(handle_line_down)

v=[0,length,Open.min()-0.5,Open.max()+0.5]
plt.axis(v)

T1 = T0[-len(T0):].astype(dt.date)/1000000000
Ti=[]
for i in range(len(T0)/5):
    a=i*5
    d = dt.date.fromtimestamp(T1[a])
    #print d
    T2=d.strftime('$%Y-%m-%d$')
    Ti.append(T2)
    #print tab
d1= dt.date.fromtimestamp(T1[len(T0)-1])
d2=d1.strftime('$%Y-%m-%d$')
Ti.append(d2)

ax1.set_xticks(np.linspace(-2,len(Close)+2,len(Ti))) 

ll=Low.min()*0.97
hh=High.max()*1.03
ax1.set_ylim(ll,hh) 

ax1.set_xticklabels(Ti)

plt.grid(True)
plt.setp(plt.gca().get_xticklabels(), rotation=45, horizontalalignment='right')
plt.show()

import datetime as dt
import matplotlib.pyplot as plt
from matplotlib.finance import candlestick_ohlc

quotes2 = get_price('000001.XSHE', start_date='2016-01-01', end_date='2016-7-09', frequency='daily',skip_paused=False)
quotes2[quotes2['volume']==0]=np.nan
quotes2= quotes2.dropna()
openp=quotes2['open'].values
closep=quotes2['close'].values
highp=quotes2['high'].values
lowp=quotes2['low'].values
volume=quotes2['volume'].values

x=0
y=len(closep)
date = np.linspace(0,y,y)
candleAr = []
while x < y:
    appendLine = date[x],openp[x],highp[x],lowp[x],closep[x],volume[x]
    candleAr.append(appendLine)
    x += 1

t = quotes2.index.values
t1 = t[-len(t):].astype(dt.date)/1000000000
ti=[]
for i in range(len(t)/5):
    a=i*5
    d = dt.date.fromtimestamp(t1[a])
    #print d
    t2=d.strftime('$%Y-%m-%d$')
    ti.append(t2)
    #print tab
d1= dt.date.fromtimestamp(t1[len(t)-1])
d2=d1.strftime('$%Y-%m-%d$')
ti.append(d2)

fig = plt.figure(figsize=(16, 8))
ax1 = plt.subplot2grid((10,4),(0,0),rowspan=10,colspan=4)
candlestick_ohlc(ax1, candleAr, width=0.5, colorup='r', colordown='g', alpha=0.6)

ax1.set_xticks(np.linspace(-2,len(closep)+2,len(ti))) 
ll=lowp.min()*0.98
hh=highp.max()*1.02
ax1.set_ylim(ll,hh) 


ax1.set_xticklabels(ti)

plt.grid(True)
plt.setp(plt.gca().get_xticklabels(), rotation=45, horizontalalignment='right')
plt.show()