def totalTogether(stockSymbol,Webster,currentInfo): #plots all the graphs together
fig=go.create_candlestick(Webster.Open,Webster.High,Webster.Low,Webster.Close,dates=Webster.index)
figure=obj.Trace(y=Webster.High,x=Webster.index,line=dict(color=('rgb(0,50,100)')))
currentFigure=obj.Trace(y=currentInfo[0]['LastTradePrice'],x=currentInfo[0]['LastTradeDateTime'],line=dict(color=('rgb(0,0,0)')))
fig['data'].extend([figure])
fig['data'].extend([currentFigure])
py.plot(fig, filename=stockSymbol+'_Line',validate=False)
def totalTogether(stockSymbol, Webster, currentInfo, Predict, Pointy,
Rsi): #plots all the graphs together
old_stdout = sys.stdout
sys.stdout = open(os.devnull, "w")
# Does not work in linux!!!
temp = Webster.index
temp = temp.tz_localize("UTC")
figure = obj.Scatter(y=Webster.High,
x=temp,
line=dict(color=('rgb(0,50,100)')),
name="Past Data for " + stockSymbol) #Past Data Line
currentFigure = obj.Trace(y=currentInfo[0]['LastTradePrice'],
x=currentInfo[0]['LastTradeDateTime'],
line=dict(color=('rgb(0,0,0)')),
name='Current Data for ' +
stockSymbol) #Current Point
Predicts = obj.Scatter(y=Predict,
x=ArrayNCalc.getWorkDates(len(Predict)),
line=dict(color=('rgb(255,165,0)')),
name="Prediction " + stockSymbol) #Prediction Line
point = obj.Trace(y=Pointy,
x=datetime.now(pytz.utc) + timedelta(days=1),
line=dict(color=pointColorMaker(Pointy, currentInfo)),
name="Prediction " + stockSymbol) #point of prediciton
RSI = obj.Scatter(y=Rsi,
x=ArrayNCalc.getWorkDates(len(Rsi)),
line=dict(color=('rgb(0,0,0)')),
name="RSI for " + stockSymbol) #Prediction Line
fig = tools.make_subplots(rows=2, cols=1)
#data=Data([figure,currentFigure,Predicts, point]) #Data Array of Figures
data = Data([Predicts, point, currentFigure, figure])
fig.append_trace(data[0], 1, 1)
fig.append_trace(data[1], 1, 1)
fig.append_trace(data[2], 1, 1)
fig.append_trace(data[3], 1, 1)
fig.append_trace(RSI, 2, 1)
fig['layout']['yaxis1'].update(title='Dollars ($)', domain=[0, 0.7])
fig['layout']['yaxis2'].update(title='RSI percentage (%)',
range=[0, 100],
domain=[0.8, 1])
sys.stdout.close()
sys.stdout = old_stdout
return py.plot(fig, filename=stockSymbol + '_Line',
auto_open=False) #Plot The Function
def make_trace(df, package, rgb):
x_date = df["commit_date"]
y_package = df[package]
return go.Trace(x=x_date,
y=y_package,
name=package,
marker=go.Marker(color=rgb))
def update_graph_scatter():
df1 = pd.read_csv(file_path+'df_ytd_week.csv',encoding='gbk')
trace = [
go.Trace(
x=df1['week'], # assign x as the dataframe column 'x'
y=df1['净现金业绩'],
name='净现金业绩'
),
go.Trace(
x=df1['week'], # assign x as the dataframe column 'x'
y=df1['本期收款'],
name='本期收款'
)
]
layout = go.Layout(
title='各周收款、净现金业绩',
xaxis=dict(title='横坐标：周数'),
yaxis=dict(title='金额(百万)')
)
return {'data': trace, 'layout':layout}
def makeLineGraph(
stockSymbol, Webster, currentInfo
): # Makes Line graph for both historic data (webster), current Stock Info (currentInfo)
old_stdout = sys.stdout
sys.stdout = open(os.devnull, "w")
figure = obj.Scatter(y=Webster.High, x=Webster.index) # Line
currentFigure = obj.Trace(
y=currentInfo[0]['LastTradePrice'],
x=currentInfo[0]['LastTradeDateTime'],
line=dict(color=('rgb(0,0,0)'))) # Current Point Data
data = [figure, currentFigure]
py.plot(data, filename=stockSymbol + '_Line')
sys.stdout.close()
sys.stdout = old_stdout
"../data2/sauer/2.csv",
"../data2/sauer/3.csv",
"../data2/sauer/4.csv",
"../data2/sauer/5.csv",
"../data2/schale_morgen/1.csv",
"../data2/schale_morgen/2.csv",
"../data2/schale_morgen/3.csv",
"../data2/schale_morgen/4.csv",
"../data2/schale_morgen/5.csv",
])
data = [
go.Trace(
x=group.wavelength,
y=group.power,
name="{} - {}".format(key[0], key[1])
)
for key, group
in input_data.groupby(["label", "reading"])
]
ply.plot(go.Figure(data=data))
sensor_data_avg = input_data\
.drop("reading", axis=1)\
.groupby(["label", "wavelength"])\
.mean()\
.reset_index()