def test_Circle_Subvector_Plot(monkeypatch):
monkeypatch.setattr(plt, 'show', lambda: None)
Circle = MakeCircle()
Vector1 = Circle.cycles[0]
Vector2 = hys.resample(Vector1, 30)
Vector3 = hys.resample(Circle, 10)
Vector1.plot()
Vector2.plot()
Vector3.plot(True)
assert True == True
def test_compare(monkeypatch):
ExpHys, AnalHys = getHys()
AnalHys.recalculateCycles(peakProminence=0.0045)
ExpHys.recalculateCycles(peakProminence=0.035 * 4.1 / 100 / 2)
AnalHys = hys.resample(AnalHys, 10)
ExpHys = hys.resample(ExpHys, 10)
Diff, Diffs = hys.compareHys(AnalHys, ExpHys)
test1 = abs(Diff - 6.79762) < 0.00001
assert test1 == True
def test_comapre_basic():
t = np.linspace(0, 4, 1000) * np.pi
x = np.sin(t)
y = np.cos(t) * t
xy = np.column_stack([x, y])
myHys = hys.Hysteresis(xy)
myHys.plot(plotCycles=True)
smallHys = hys.resample(myHys, 10)
# samllHys.plot()
out = hys.compareHys(smallHys, myHys)
assert out[0] == 0
# t = np.linspace(0,4,1000)*np.pi
# x = np.sin(t)
# y = np.cos(t)*t
# xy = np.column_stack([x,y])
# myHys = hys.Hysteresis(xy)
# myHys.plot(plotCycles = True)
# smallHys = hys.reSample(myHys, 10)
# smallHys.xy[:,1] = smallHys.xy[:,1] / 4
# smallHys = hys.Hysteresis(smallHys.xy)
# smallHys.plot()
# # smallHys.xy[:,1] = smallHys.xy[:,1]/2
# out = hys.CompareHys(smallHys,myHys)
def test_DownSampled_Plotting(monkeypatch):
""" Tests if the resampled hystresis can plot correctly """
monkeypatch.setattr(plt, 'show', lambda: None)
DamperHys = hys.Hysteresis(testHys2)
downsampledHys = hys.resample(DamperHys, 20)
downsampledHys.plot(plotCycles=True)
plt.close()
downsampledHys.plotCycles([2, 3])
plt.close()
downsampledHys.plotArea()
plt.close()
downsampledHys.plotSlope()
plt.close()
assert True == True
AnalHys.plotLoadProtocol(comparisonProtocol = ExpHys.loadProtocol)
"""
Now that each hysteresis has the same number of cycles, it's possible to
compare how "similar" each cycle is.
We will first shift each curve into a similar domain/range using the resample
functon. This will take each curve in the hystersis, and use linear
interpolation to define 10 evenly spaced points along that curve.
"""
NsamplesPerCurve = 10
AnalHysDx = hys.resample(AnalHys, NsamplesPerCurve)
ExpHysDx = hys.resample(ExpHys, NsamplesPerCurve)
fig, ax = plt.subplots()
line1 = AnalHysDx.plot(True)
line2 = ExpHysDx.plot(True)
ax.lines[2].set_color('C3')
ax.lines[3].set_color('C2')
ax.set_xlabel('Drift (%)')
ax.set_ylabel('Force (kN)')
plt.minorticks_on()
ax.grid(which='major', color='grey', linewidth=0.5, alpha = 0.8)
ax.grid(b=True, which='minor', linewidth=0.5, alpha = 0.4)
plt.show()
# by recalculating the peaks with a prominence comand AnalHys.recalculateCycles(peakProminence=0.005) # AnalHys.plotLoadProtocol(comparisonProtocol = ExpHys.loadProtocol) # Almost there! It looks like we are missing one of the Analysis points # To get there, lets cut off the appropriate number of points AnalHys = hys.Hysteresis(Wall_anal_xy[500:, :]) AnalHys.recalculateCycles(peakProminence=0.0045) # AnalHys.plotLoadProtocol(comparisonProtocol = ExpHys.loadProtocol) # ============================================================================= # resample # ============================================================================= # Now we can resample and compare the curves! AnalHysDx = hys.resample(AnalHys, 10) ExpHysDx = hys.resample(ExpHys, 10) fig, ax = plt.subplots() AnalHysDx.plotLoadProtocol(comparisonProtocol=ExpHysDx.loadProtocol) fig, ax = plt.subplots() AnalHysDx.plot(True) ExpHysDx.plot(True) # fig, ax = plt.subplots() Diff, Diffs = hys.compareHys(AnalHysDx, ExpHysDx) # We can plot the difference over each cycle fig, ax = plt.subplots()
basePoints = np.linspace(0, 1, 1000) * 2 * np.pi
testCirclex = np.cos(basePoints)
testCircley = np.sin(basePoints)
Circlexy = np.column_stack((testCirclex, testCircley))
Circle = hys.Hysteresis(Circlexy)
Circle.plot(plotCycles=True)
Circle.plotArea(plotCycles=True)
Circle.plotSlope(plotCycles=True, ylim=[-10, 10])
Circle.setPeaks()
fig, ax = Circle.plotCycles(plotCycles=True, plotPeaks=True)
# fig, ax = Circle.plotSubVector(0)
Vector1 = Circle.Cycles[0]
Vector2 = hys.resample(Vector1, 30)
Vector3 = hys.resample(Circle, 10)
Vector1.plot()
Vector2.plot()
Vector3.plot(True)
fig, ax = Circle.plot()
xy = Vector3.xy
plt.plot(xy[:, 0], xy[:, 1])
ax.set_xlabel('x')
ax.set_ylabel('y')
plt.minorticks_on()
ax.grid(which='major', color='grey', linewidth=0.5, alpha=0.8)
ax.grid(b=True, which='minor', linewidth=0.5, alpha=0.4)