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test_addplot.py
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import os
import os.path
import glob
import mplfinance as mpf
import matplotlib.pyplot as plt
from matplotlib.testing.compare import compare_images
print('mpf.__version__ =',mpf.__version__) # for the record
print("plt.rcParams['backend'] =",plt.rcParams['backend']) # for the record
base='addplot'
tdir = os.path.join('tests','test_images')
refd = os.path.join('tests','reference_images')
globpattern = os.path.join(tdir,base+'*.png')
oldtestfiles = glob.glob(globpattern)
for fn in oldtestfiles:
try:
os.remove(fn)
except:
print('Error removing file "'+fn+'"')
# IMGCOMP_TOLERANCE = 7.0 # this works fine for linux
IMGCOMP_TOLERANCE = 11.0 # required for a windows pass. (really 10.25 may do it).
def test_addplot01(bolldata):
df = bolldata
fname = base+'01.png'
tname = os.path.join(tdir,fname)
rname = os.path.join(refd,fname)
mpf.plot(df,volume=True,savefig=tname)
tsize = os.path.getsize(tname)
print(glob.glob(tname),'[',tsize,'bytes',']')
rsize = os.path.getsize(rname)
print(glob.glob(rname),'[',rsize,'bytes',']')
result = compare_images(rname,tname,tol=IMGCOMP_TOLERANCE)
if result is not None:
print('result=',result)
assert result is None
def test_addplot02(bolldata):
df = bolldata
fname = base+'02.png'
tname = os.path.join(tdir,fname)
rname = os.path.join(refd,fname)
apdict = mpf.make_addplot(df['LowerB'])
mpf.plot(df,volume=True,addplot=apdict,savefig=tname)
tsize = os.path.getsize(tname)
print(glob.glob(tname),'[',tsize,'bytes',']')
rsize = os.path.getsize(rname)
print(glob.glob(rname),'[',rsize,'bytes',']')
result = compare_images(rname,tname,tol=IMGCOMP_TOLERANCE)
if result is not None:
print('result=',result)
assert result is None
def percentB_aboveone(percentB,price):
import numpy as np
signal = []
previous = 2
for date,value in percentB.items():
if value > 1 and previous <= 1:
signal.append(price[date]*1.01)
else:
signal.append(np.nan)
previous = value
return signal
def percentB_belowzero(percentB,price):
import numpy as np
signal = []
previous = -1.0
for date,value in percentB.items():
if value < 0 and previous >= 0:
signal.append(price[date]*0.99)
else:
signal.append(np.nan)
previous = value
return signal
def test_addplot03(bolldata):
df = bolldata
fname = base+'03.png'
tname = os.path.join(tdir,fname)
rname = os.path.join(refd,fname)
tcdf = df[['LowerB','UpperB']] # DataFrame with two columns
low_signal = percentB_belowzero(df['PercentB'], df['Close'])
high_signal = percentB_aboveone(df['PercentB'], df['Close'])
apds = [ mpf.make_addplot(tcdf),
mpf.make_addplot(low_signal,scatter=True,markersize=200,marker='^'),
mpf.make_addplot(high_signal,scatter=True,markersize=200,marker='v'),
mpf.make_addplot((df['PercentB']),panel='lower',color='g')
]
mpf.plot(df,addplot=apds,figscale=1.3,volume=True,savefig=tname)
tsize = os.path.getsize(tname)
print(glob.glob(tname),'[',tsize,'bytes',']')
rsize = os.path.getsize(rname)
print(glob.glob(rname),'[',rsize,'bytes',']')
result = compare_images(rname,tname,tol=IMGCOMP_TOLERANCE)
if result is not None:
print('result=',result)
assert result is None
def test_addplot04(bolldata):
df = bolldata
fname = base+'04.png'
tname = os.path.join(tdir,fname)
rname = os.path.join(refd,fname)
tcdf = df[['LowerB','UpperB']] # DataFrame with two columns
low_signal = percentB_belowzero(df['PercentB'], df['Close'])
high_signal = percentB_aboveone(df['PercentB'], df['Close'])
apds = [ mpf.make_addplot(tcdf,linestyle='dashdot'),
mpf.make_addplot(low_signal,scatter=True,markersize=200,marker='^'),
mpf.make_addplot(high_signal,scatter=True,markersize=200,marker='v'),
mpf.make_addplot((df['PercentB']),panel='lower',color='g',linestyle='dotted')
]
mpf.plot(df,addplot=apds,figscale=1.5,volume=True,
style='starsandstripes',savefig=tname)
tsize = os.path.getsize(tname)
print(glob.glob(tname),'[',tsize,'bytes',']')
rsize = os.path.getsize(rname)
print(glob.glob(rname),'[',rsize,'bytes',']')
result = compare_images(rname,tname,tol=IMGCOMP_TOLERANCE)
if result is not None:
print('result=',result)
assert result is None
def test_addplot05(bolldata):
df = bolldata
fname = base+'05.png'
tname = os.path.join(tdir,fname)
rname = os.path.join(refd,fname)
tcdf = df[['LowerB','UpperB']] # DataFrame with two columns
low_signal = percentB_belowzero(df['PercentB'], df['Close'])
high_signal = percentB_aboveone(df['PercentB'], df['Close'])
import math
new_low_signal = [x*20.*math.sin(x) for x in low_signal]
apds = [ mpf.make_addplot(tcdf,linestyle='dashdot'),
mpf.make_addplot(new_low_signal,scatter=True,markersize=200,marker='^'),
mpf.make_addplot(high_signal,scatter=True,markersize=200,marker='v'),
mpf.make_addplot((df['PercentB']),panel='lower',color='g',linestyle='dotted')
]
mpf.plot(df,addplot=apds,figscale=1.5,volume=True,
style='sas',savefig=tname)
tsize = os.path.getsize(tname)
print(glob.glob(tname),'[',tsize,'bytes',']')
rsize = os.path.getsize(rname)
print(glob.glob(rname),'[',rsize,'bytes',']')
result = compare_images(rname,tname,tol=IMGCOMP_TOLERANCE)
if result is not None:
print('result=',result)
assert result is None
def test_addplot06(bolldata):
df = bolldata
fname = base+'06.png'
tname = os.path.join(tdir,fname)
rname = os.path.join(refd,fname)
tcdf = df[['LowerB','UpperB']] # DataFrame with two columns
low_signal = percentB_belowzero(df['PercentB'], df['Close'])
high_signal = percentB_aboveone(df['PercentB'], df['Close'])
import math
new_low_signal = [x*20.*math.sin(x) for x in low_signal]
apds = [ mpf.make_addplot(tcdf,linestyle='dashdot'),
mpf.make_addplot(new_low_signal,scatter=True,markersize=200,marker='^'),
mpf.make_addplot(high_signal,scatter=True,markersize=200,marker='v'),
mpf.make_addplot((df['PercentB']),panel='lower',color='g',linestyle='dotted')
]
mpf.plot(df,addplot=apds,figscale=1.5,volume=True,
style='default',savefig=tname)
tsize = os.path.getsize(tname)
print(glob.glob(tname),'[',tsize,'bytes',']')
rsize = os.path.getsize(rname)
print(glob.glob(rname),'[',rsize,'bytes',']')
result = compare_images(rname,tname,tol=IMGCOMP_TOLERANCE)
if result is not None:
print('result=',result)
assert result is None
def test_addplot07(bolldata):
df = bolldata
fname = base+'07.png'
tname = os.path.join(tdir,fname)
rname = os.path.join(refd,fname)
mpf.plot(df,volume=True,savefig=tname,mav=(20,40,60))
tsize = os.path.getsize(tname)
print(glob.glob(tname),'[',tsize,'bytes',']')
rsize = os.path.getsize(rname)
print(glob.glob(rname),'[',rsize,'bytes',']')
result = compare_images(rname,tname,tol=IMGCOMP_TOLERANCE)
if result is not None:
print('result=',result)
assert result is None
def test_addplot08(bolldata):
df = bolldata
fname = base+'08.png'
tname = os.path.join(tdir,fname)
rname = os.path.join(refd,fname)
tcdf = df[['LowerB','UpperB']] # DataFrame with two columns
low_signal = percentB_belowzero(df['PercentB'], df['Close'])
high_signal = percentB_aboveone(df['PercentB'], df['Close'])
import math
new_low_signal = [x*20.*math.sin(x) for x in low_signal]
apds = [ mpf.make_addplot(tcdf,linestyle='dashdot'),
mpf.make_addplot(new_low_signal,scatter=True,markersize=200,marker='^'),
mpf.make_addplot(high_signal,scatter=True,markersize=200,marker='v'),
mpf.make_addplot((df['PercentB']),panel='lower',color='g',linestyle='dotted')
]
mpf.plot(df,addplot=apds,figscale=1.5,volume=True,
mav=(15,30,45),style='default',savefig=tname)
tsize = os.path.getsize(tname)
print(glob.glob(tname),'[',tsize,'bytes',']')
rsize = os.path.getsize(rname)
print(glob.glob(rname),'[',rsize,'bytes',']')
result = compare_images(rname,tname,tol=IMGCOMP_TOLERANCE)
if result is not None:
print('result=',result)
assert result is None
def test_addplot09(bolldata):
sdf = bolldata[50:130]
fname = base+'09.png'
tname = os.path.join(tdir,fname)
rname = os.path.join(refd,fname)
ap = mpf.make_addplot((sdf['PercentB'])-0.45,panel=1,color='g',type='bar', width=0.75, mav=(7,10,15))
mpf.plot(sdf,addplot=ap,panel_ratios=(1,1),figratio=(1,1),figscale=1.5,savefig=tname)
tsize = os.path.getsize(tname)
print(glob.glob(tname),'[',tsize,'bytes',']')
rsize = os.path.getsize(rname)
print(glob.glob(rname),'[',rsize,'bytes',']')
# Using 0.9*IMGCOMP_TOLERANCE here because discovered that if
# the only difference is the presence or absence of mav lines,
# then the default IMGCOMP_TOLERANCE is too linient:
result = compare_images(rname,tname,tol=0.9*IMGCOMP_TOLERANCE)
if result is not None:
print('result=',result)
assert result is None
def test_addplot10(bolldata):
sdf = bolldata[50:130]
fname = base+'10.png'
tname = os.path.join(tdir,fname)
rname = os.path.join(refd,fname)
ap = mpf.make_addplot(sdf,panel=1,type='candle',ylabel='Candle',mav=12)
mpf.plot(sdf,mav=10,ylabel='OHLC',addplot=ap,panel_ratios=(1,1),figratio=(1,1),figscale=1.5,savefig=tname)
tsize = os.path.getsize(tname)
print(glob.glob(tname),'[',tsize,'bytes',']')
rsize = os.path.getsize(rname)
print(glob.glob(rname),'[',rsize,'bytes',']')
# Using 0.9*IMGCOMP_TOLERANCE here because discovered that if
# the only difference is the presence or absence of mav lines,
# then the default IMGCOMP_TOLERANCE is too linient:
result = compare_images(rname,tname,tol=0.9*IMGCOMP_TOLERANCE)
if result is not None:
print('result=',result)
assert result is None
def test_addplot11(bolldata):
df = bolldata[50:130].copy()
fname = base+'11.png'
tname = os.path.join(tdir,fname)
rname = os.path.join(refd,fname)
df.loc[:,'trend'] = 0
df.loc[df['Close'] < df['Open'], 'trend'] = - 1
df.loc[df['Close'] > df['Open'], 'trend'] = 1
ap = mpf.make_addplot(df['trend'],panel=1,type='step',ylabel='simple trend')
mpf.plot(df,ylabel='OHLC',addplot=ap,savefig=tname)
tsize = os.path.getsize(tname)
print(glob.glob(tname),'[',tsize,'bytes',']')
rsize = os.path.getsize(rname)
print(glob.glob(rname),'[',rsize,'bytes',']')
result = compare_images(rname,tname,tol=IMGCOMP_TOLERANCE)
if result is not None:
print('result=',result)
assert result is None
def test_addplot12(bolldata):
df = bolldata
fname = base+'12.png'
tname = os.path.join(tdir,fname)
rname = os.path.join(refd,fname)
mpf.plot(df,type='candle',volume=True,savefig=tname,mav={'period':(20,40,60), 'shift': [5,10,20]})
tsize = os.path.getsize(tname)
print(glob.glob(tname),'[',tsize,'bytes',']')
rsize = os.path.getsize(rname)
print(glob.glob(rname),'[',rsize,'bytes',']')
result = compare_images(rname,tname,tol=IMGCOMP_TOLERANCE)
if result is not None:
print('result=',result)
assert result is None