def plot(self):
if self.backend == "mpl":
plt.show()
elif self.backend == "ipt":
iplot_mpl(self.fig)
else:
plot_mpl(self.fig)
def EpochRawData(raw,
event_id,
stimChannel,
preStim=-0.2,
postStim=0.2,
initial_event_=True,
min_duration_=.01,
plot=False,
reject_=None):
events = mne.find_events(raw,
stimChannel,
'onset',
initial_event=initial_event_,
consecutive=True,
min_duration=min_duration_)
picks = mne.pick_types(raw.info, meg='mag')
if reject_ is not None:
reject_dict = {'mag': reject_}
else:
reject_dict = None
epochs = mne.Epochs(raw,
events,
reject=reject_dict,
event_id=event_id,
tmin=preStim,
tmax=postStim,
preload=True,
baseline=None,
picks=picks)
if plot:
fig = mne.viz.plot_events(events,
raw.info['sfreq'],
raw.first_samp,
show=False)
# convert plot to plotly
update = dict(layout=dict(showlegend=True),
data=[dict(name=e) for e in event_id])
iplot_mpl(plt.gcf(), update)
return epochs
def plotFromMPL():
'''
take the current matplotlib plot and instead render it with plotly
'''
fig = plt.gcf() # Get current figure
ply.iplot_mpl(fig, show_link=False)
import plotly.graph_objs as go
py.iplot(go.Data([go.Scatter(x=X, y=Y,)])) # 直接在interactive地在jupyter里显示
py.plot(fig, filename='the_graph.html') # 或者直接保存成文件
# 之后可以用加载html的方式显示出来
with open(html_path) as f:
display(HTML(f.read()))
# convert matplot to plotly
# https://plot.ly/matplotlib/modifying-a-matplotlib-figure/
# https://plot.ly/matplotlib/
#
# plot...
py.iplot_mpl(plt.gcf())
# plot stacked
traces = []
cum = None
for sr in info_data['position']:
data = info_data['position'][sr]
if cum is None:
cum = np.zeros(data.shape)
text = data.apply(str)
cum += data.values
offline.init_notebook_mode()
offline.iplot([{"y": [1, 2, 1]}])
# %%
import numpy as np
import matplotlib.pyplot as plt
from plotly import offline as py
py.init_notebook_mode()
t = np.linspace(0, 20, 500)
plt.plot(t, np.sin(t))
py.iplot_mpl(plt.gcf())
# %%
from IPython.display import JSON
data = {"foo": {"bar": "baz"}, "a": 1}
JSON(data)
# %%
import sympy as sp
sp.init_printing(use_latex="mathjax")
x, y, z = sp.symbols("x y z")
f = sp.sin(x * y) + sp.cos(y * z)
sp.integrate(f, x)
def creatSTwithPlot(self,futshare,Cal1,c1share,Cal2,c2share,Put1,p1share,Put2,p2share,showrange,up,down,customcur,risk_free_rate=0.0136):
stcom = []
Cal1=int(Cal1)
Cal2=int(Cal2)
Put1=int(Put1)
Put2=int(Put2)
if futshare!=0:
st = ['future',self.get_future(),0,futshare]
stcom.append(st)
if c1share!=0:
st = ['Call',Cal1,
float(self.Callless[self.Callless['履約價']==Cal1]['成交'].values[0]),
self.Callless[self.Callless['履約價']==Cal1]['組合價'].values[0],
c1share]
stcom.append(st)
if c2share!=0:
st = ['Call',Cal2,
float(self.Callless[self.Callless['履約價']==Cal2]['成交'].values[0]),
self.Callless[self.Callless['履約價']==Cal2]['組合價'].values[0],
c2share]
stcom.append(st)
if p1share!=0:
st = ['Put', Put1,
float(self.Putless[self.Putless['履約價']==Put1]['成交'].values[0]),
self.Putless[self.Putless['履約價']==Put1]['組合價'].values[0],
p1share]
stcom.append(st)
if p2share!=0:
st = ['Put',Put2,
float(self.Putless[self.Putless['履約價']==Put2]['成交'].values[0]),
self.Putless[self.Putless['履約價']==Put2]['組合價'].values[0],
p2share]
stcom.append(st)
print(stcom)
if len(stcom)>0:
lastEXP = self.lastexprice
twsecurrent = self.TWSEquote()
TWSErange = np.arange(lastEXP-showrange,lastEXP+showrange,10)
Tcul = self.Call.dropna().TCUL.iloc[0]/255#self.Callless['TCUL'].iloc[3]/255
#risk_free_rate = self.risk_free_rate
futureprofit = []
Callprofit = []
Putprofit = []
Callintimeprofit = []
Putintimeprofit = []
Calltimectrl =[]
Puttimectrl = []
for s in stcom:
if s[0] == 'future':
futureprofit.append((TWSErange-s[1])*s[3])
if s[0] =='Call':
Callprofit.append(((abs(TWSErange-s[1])+TWSErange-s[1])/2-s[2])*s[4])
IV = self.Call[self.Call['履約價']==s[1]]['隱含波動率'].values[0]/100
Callintimeprofit.append((bs_call(TWSErange,s[1],Tcul,risk_free_rate,IV)-s[2])*s[4])
Calltimectrl.append((bs_call(TWSErange,s[1],Tcul*customcur,risk_free_rate,IV)-s[2])*s[4])
if s[0] =='Put':
Putprofit.append(((abs(s[1]-TWSErange)-TWSErange+s[1])/2-s[2])*s[4])
IV = self.Put[self.Put['履約價']==s[1]]['隱含波動率'].values[0]/100
Putintimeprofit.append((bs_put(TWSErange,s[1],Tcul,risk_free_rate,IV)-s[2])*s[4])
Puttimectrl.append((bs_put(TWSErange,s[1],Tcul*customcur,risk_free_rate,IV)-s[2])*s[4])
STprofit = 0
STtime = 0
customcurve = 0
if len(futureprofit)!=0:
for f in futureprofit:
STprofit = STprofit + f
STtime = STtime + f
customcurve = customcurve + f
if len(Callprofit)!=0:
for Call in Callprofit:
STprofit = STprofit + Call
if len(Putprofit)!=0:
for Put in Putprofit:
STprofit = STprofit + Put
if len(Callintimeprofit)!=0:
for Callt in Callintimeprofit:
STtime = STtime + Callt
if len(Putintimeprofit)!=0:
for Putt in Putintimeprofit:
STtime = STtime + Putt
if len(Calltimectrl)!=0:
for Callti in Calltimectrl:
customcurve = customcurve + Callti
if len(Puttimectrl)!=0:
for Putti in Puttimectrl:
customcurve = customcurve + Putti
lastexpX = [lastEXP,lastEXP]
lastexpY = [-down,up]
twseX = [twsecurrent,twsecurrent]
futureX = [self.get_future(),self.get_future()]
twseY = [-down+40,up-40]
opX = np.array([s[3] for s in stcom if s[0]!='future']).mean()
optionX = [opX, opX]
Xra = 300
lastexpXup = [lastEXP+Xra,lastEXP+Xra]
lastexpXdown = [lastEXP-Xra,lastEXP-Xra]
fig = plt.figure(figsize=(16*3/4,9*3/4))
ax = fig.add_subplot(1,1,1)
ax.plot(TWSErange,np.zeros(len(TWSErange)),'gray',label='zeros')
ax.plot(lastexpX,lastexpY,color=(0.2,0.2,0.7),label='last_exp')
ax.plot(lastexpXup,lastexpY,color=(0.2,0.7,0.2),label='exp_up')
ax.plot(lastexpXdown,lastexpY,color=(0.2,0.7,0.2),label='exp_down')
ax.plot(twseX,twseY,'y',label='twse_current')
ax.plot(futureX,twseY,'c',label='future_current')
ax.plot(optionX,twseY,'r',label='option_current')
ax.plot(TWSErange,STprofit,label='EXdcurve',color = 'k',linewidth=1.5 )
ax.plot(TWSErange,STtime,label='todaycurve',color = 'dimgray')
ax.plot(TWSErange,customcurve,label='customcurve',color = (0.3,0.6,0.6))
#ax.legend()
ax.set_xlim(lastEXP-showrange,lastEXP+showrange)
ax.grid()
ax.set_xlabel('Stock price')
ax.set_ylabel('Profit (loss)')
#plt.show()
iplot_mpl(fig)