<jupyter_start><jupyter_text>Separate per faultY parameter<jupyter_code>print(Loc2000["FaultY"].unique())

Loc2000f100 = FilterDataForFloatEquality(Loc2000, "FaultY", 100)<jupyter_output><empty_output><jupyter_text>Comparing the same location at different QP<jupyter_code>for q in range(4):
    LocQ1 = Loc2000f100.loc[Loc2000f100["q"].eq(q),["Time","Slip","SlipRate"]]
    plt.plot(LocQ1.Time, LocQ1["Slip"])
# Live Plotting of a underwritting file
class SlipDataObject:
    def __init__(self, filename):
        self.FileName = filename
        self.Data = pd.read_csv(filename,sep="\t")
    #end __init__
    
    # Default object printing information
    def __repr__(self):
        return "File loaded: {}".format(self.FileName)
    #end __repr__
    
    def __str__(self):
        return "File loaded: {}".format(self.FileName)
    #end __str__
    
    def FilterDataForFloatEquality(self, Data, Column, Value, Tolerance = 1e-1):
        return Data.loc[(abs(self.Data[Column]-Value).lt(Tolerance))]

    def reload(self):
        self.Data = pd.read_csv(self.FileName, sep="\t")
    
    def getDataSubDomain(self, FaultX, FaultXValue, FaultY, FaultYValue, q):
        FxData = self.FilterDataForFloatEquality(self.Data, FaultX, FaultXValue)
        FyData = self.FilterDataForFloatEquality(FxData, FaultY, FaultYValue)
        return FyData.loc[FyData["q"].eq(q)]


def format_axes(fig):
    for i, ax in enumerate(fig.axes):
        ax.set_xlim(-0.5,4)
        ax.set_ylim(-0.5,10)
        
    Lines = fig.axes[-1].get_lines()[-5:]
    
    legend2 = fig.axes[-1].legend(Lines, ['Reference', '8km','6km', '4km', '2km'], loc=1)
    fig.axes[-1].add_artist(legend2)

def GenericFigAxis():
    fig = plt.figure(constrained_layout=True, figsize=[12,4])
    gs = GridSpec(1, 2, figure=fig)

    ax1 = fig.add_subplot(gs[0, 0])
    ax2 = fig.add_subplot(gs[0, 1])
    
    
    return fig, [ax1, ax2]
def Plotting(fig, axis, DataObj,FilteringSpecs):
    DataObj.reload()
    FilteredDataframe = DataObj.getDataSubDomain(**FilteringSpecs)

    x_values = FilteredDataframe.Time
    y_values = FilteredDataframe.Slip
    yPrime_values = FilteredDataframe.SlipRate

    AA=0
    axis[0].plot(x_values, np.cumsum(yPrime_values)*(x_values.iloc[1]-x_values.iloc[0]))
    #axis[0].plot(x_values, np.cumsum(y_values))
    #axis[0].plot(x_values, y_values)
    axis[0].set_xlabel('Time = {}'.format(FilteredDataframe.Time.iloc[-1]))
    axis[0].set_ylabel('Slip')
    axis[0].set_title('Slip')

    axis[1].plot(x_values, yPrime_values)
    axis[1].set_ylabel('Slip rate')
    axis[1].set_title('Slip rate')
    axis[1].set_xlabel('Time = {}'.format(FilteredDataframe.Time.iloc[-1]))
    
    fig.gca().relim()
    fig.gca().autoscale_view()<jupyter_output><empty_output><jupyter_text>P6$S = \Delta V\  dt + \frac{\delta}{\mu}(c-f(t)(-\sigma^{avg}_{yy}))$$dS = S - S_{t-1}$$\gamma=\frac{dS}{2\delta} P_n(\phi/2\delta)$$S_{q}\ =S_{t-1} + dS$$\dot{S}_{q}=dS\ /\ dt$<jupyter_code>Path = "/home/nico/Documents/TEAR/Codes_TEAR/se2dr/Runs/P6/"
DataObj = SlipDataObject(Path+"SlipAtReceiver.txt")

fig, axis = GenericFigAxis()
fig.suptitle("Plastic Multiplier approach")

FilteringSpecs = {"FaultX":"FaultX", "FaultXValue":2000,
                 "FaultY":"FaultY", "FaultYValue":100, 
                 "q":0}
plt.ion()
[item.PlotReference(axis[0], "Slip", filtering=True) for item in RefList]
[item.PlotReference(axis[1], "SlipRate", filtering=True) for item in RefList]

Plotting(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":2000})
Plotting(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":4000})
Plotting(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":6000})
#format_axes(fig)<jupyter_output><empty_output><jupyter_text>P1$\dot{S} = \Delta V - \frac{\delta}{\mu}(\frac{f(t)-f(t-1)}{dt})(-\sigma^{avg}_{yy})$$dS = \dot{S}\ dt $$\gamma=\frac{dS}{2\delta} P_n(\phi/2\delta)$$S_{q}\ += S$$\dot{S}_{q}=dS\ /\ dt$<jupyter_code>Path = "/home/nico/Documents/TEAR/Codes_TEAR/se2dr/Runs/P1/"
DataObj = SlipDataObject(Path+"SlipAtReceiver.txt")

fig, axis = GenericFigAxis()
fig.suptitle("Plastic Multiplier approach")

FilteringSpecs = {"FaultX":"FaultX", "FaultXValue":2000,
                  "FaultY":"FaultY", "FaultYValue":100, 
                  "q":0}
plt.ion()
[item.PlotReference(axis[0], "Slip", filtering=True) for item in RefList]
[item.PlotReference(axis[1], "SlipRate", filtering=True) for item in RefList]

Plotting(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":0})
Plotting(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":2000})
Plotting(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":4000})
Plotting(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":6000})
format_axes(fig)<jupyter_output><empty_output><jupyter_text>P9$S = \Delta U + \frac{\delta}{\mu}(c-f(t)(-\sigma^{avg}_{yy}))$$dS = S - S_{t-1}$$\gamma=\frac{dS}{2\delta} P_n(\phi/2\delta)$$S_{q}\ = S$$\dot{S}_{q}=dS\ /\ dt$<jupyter_code>Path = "/home/nico/Documents/TEAR/Codes_TEAR/se2dr/Runs/P9/"
DataObj = SlipDataObject(Path+"SlipAtReceiver.txt")

fig, axis = GenericFigAxis()
fig.suptitle("Plastic Multiplier approach")

FilteringSpecs = {"FaultX":"FaultX", "FaultXValue":2000,
                  "FaultY":"FaultY", "FaultYValue":100, 
                  "q":0}
plt.ion()
[item.PlotReference(axis[0], "Slip", filtering=True) for item in RefList]
[item.PlotReference(axis[1], "SlipRate", filtering=True) for item in RefList]

Plotting(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":0})
Plotting(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":2000})
Plotting(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":4000})
Plotting(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":6000})
#format_axes(fig)<jupyter_output><empty_output><jupyter_text>Looks like I didnt save the code when I commented out the slip updating scheme. Of course it was not calculating correctly the accumulationgod...I start again and the plotting function is changed to not scroll up again<jupyter_code>def Plottings(fig, axis, DataObj,FilteringSpecs):
    DataObj.reload()
    FilteredDataframe = DataObj.getDataSubDomain(**FilteringSpecs)

    x_values = FilteredDataframe.Time
    y_values = FilteredDataframe.Slip
    yPrime_values = FilteredDataframe.SlipRate

    AA=0
    #axis[0].plot(x_values, np.cumsum(yPrime_values)*(x_values.iloc[1]-x_values.iloc[0]))
    axis[0].plot(x_values, y_values)
    axis[0].set_xlabel('Time = {}'.format(FilteredDataframe.Time.iloc[-1]))
    axis[0].set_ylabel('Slip')
    axis[0].set_title('Slip')

    axis[1].plot(x_values, yPrime_values)
    axis[1].set_ylabel('Slip rate')
    axis[1].set_title('Slip rate')
    axis[1].set_xlabel('Time = {}'.format(FilteredDataframe.Time.iloc[-1]))
    
    fig.gca().relim()
    fig.gca().autoscale_view()<jupyter_output><empty_output><jupyter_text>P2$S = \Delta U + \frac{\delta}{\mu}(c-f(t)(-\sigma^{avg}_{yy}))$$dS = S - S_{t-1}$$\gamma=\frac{dS}{2\delta} P_n(\phi/2\delta)$$S_{q}\ += dS$$\dot{S}_{q}=dS\ /\ dt$<jupyter_code>Path = "/home/nico/Documents/TEAR/Codes_TEAR/se2dr/Runs/P2/"
DataObj = SlipDataObject(Path+"SlipAtReceiver.txt")

fig, axis = GenericFigAxis()
fig.suptitle("Plastic Multiplier approach")

FilteringSpecs = {"FaultX":"FaultX", "FaultXValue":2000,
                  "FaultY":"FaultY", "FaultYValue":100, 
                  "q":0}
plt.ion()
#[item.PlotReference(axis[0], "Slip", filtering=True) for item in RefList]
#[item.PlotReference(axis[1], "SlipRate", filtering=True) for item in RefList]

Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":0})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":2000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":4000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":6000})
#format_axes(fig)<jupyter_output><empty_output><jupyter_text>^After that change, now the slip is consistent with the slip rate  P3$S = \Delta U + \frac{\delta}{\mu}(c-f(t)(-\sigma^{avg}_{yy}))$$dS = S - S_{t-1}$$\gamma=\frac{S}{2\delta} P_n(\phi/2\delta)$$S_{q}\ += dS$$\dot{S}_{q}=dS\ /\ dt$<jupyter_code>Path = "/home/nico/Documents/TEAR/Codes_TEAR/se2dr/Runs/P3/"
DataObj = SlipDataObject(Path+"SlipAtReceiver.txt")

fig, axis = GenericFigAxis()
fig.suptitle("Plastic Multiplier approach")

FilteringSpecs = {"FaultX":"FaultX", "FaultXValue":2000,
                  "FaultY":"FaultY", "FaultYValue":100, 
                  "q":0}
plt.ion()
[item.PlotReference(axis[0], "Slip", filtering=True) for item in RefList]
[item.PlotReference(axis[1], "SlipRate", filtering=True) for item in RefList]

Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":0})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":2000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":4000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":6000})
#format_axes(fig)<jupyter_output><empty_output><jupyter_text>P4$\dot{S} = \Delta V - \frac{\delta}{\mu}(\frac{f(t)-f(t-1)}{dt})(-\sigma^{avg}_{yy})$$dS = \dot{S}\ dt$$\gamma=\frac{dS}{2\delta} P_n(\phi/2\delta)$$S_{q}\ += dS$$\dot{S}_{q}=dS\ /\ dt$<jupyter_code>Path = "/home/nico/Documents/TEAR/Codes_TEAR/se2dr/Runs/P4/"
DataObj = SlipDataObject(Path+"SlipAtReceiver.txt")

fig, axis = GenericFigAxis()
fig.suptitle("Plastic Multiplier approach")

FilteringSpecs = {"FaultX":"FaultX", "FaultXValue":2000,
                  "FaultY":"FaultY", "FaultYValue":100, 
                  "q":0}
plt.ion()
[item.PlotReference(axis[0], "Slip", filtering=True) for item in RefList]
[item.PlotReference(axis[1], "SlipRate", filtering=True) for item in RefList]

#Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":0})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":2000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":4000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":6000})
#format_axes(fig)<jupyter_output><empty_output><jupyter_text>P10$S = \Delta U + \frac{\delta}{\mu}\ (f_{static}\sigma_{n}-f(t)\sigma^{avg}_{yy}) $$dS = S - S_{t-1}$$\gamma=\frac{S}{2\delta} P_n(\phi/2\delta)$$S_{q}\ += dS$$\dot{S}_{q}=dS\ /\ dt$<jupyter_code>Path = "/home/nico/Documents/TEAR/Codes_TEAR/se2dr/Runs/P10/"
DataObj = SlipDataObject(Path+"SlipAtReceiver.txt")

fig, axis = GenericFigAxis()
fig.suptitle("Plastic Multiplier approach")

FilteringSpecs = {"FaultX":"FaultX", "FaultXValue":2000,
                  "FaultY":"FaultY", "FaultYValue":100, 
                  "q":0}
plt.ion()
#[item.PlotReference(axis[0], "Slip", filtering=True) for item in RefList]
#[item.PlotReference(axis[1], "SlipRate", filtering=True) for item in RefList]

Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":0})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":2000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":4000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":6000})
#format_axes(fig)<jupyter_output><empty_output><jupyter_text>P11$\dot{S} = \Delta V - \frac{\delta}{\mu}\ \frac{(f(t)-f(t-dt))}{dt}(-\sigma^{avg}_{yy}) $$dS = \dot{S}dt$$\gamma=\frac{dS}{2\delta} P_n(\phi/2\delta)$--------------$\sigma_{xy} = 2\mu\ \gamma$$S_{q}\ += dS$$\dot{S}_{q}=dS\ /\ dt$<jupyter_code>Path = "/home/nico/Documents/TEAR/Codes_TEAR/se2dr/Runs/P11/"
DataObj = SlipDataObject(Path+"SlipAtReceiver.txt")

fig, axis = GenericFigAxis()
fig.suptitle("Plastic Multiplier approach (TransectStressAvg branch)")

FilteringSpecs = {"FaultX":"FaultX", "FaultXValue":2000,
                  "FaultY":"FaultY", "FaultYValue":100, 
                  "q":0}
plt.ion()
[item.PlotReference(axis[0], "Slip", filtering=True) for item in RefList]
[item.PlotReference(axis[1], "SlipRate", filtering=True) for item in RefList]

#Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":0})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":2000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":4000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":6000})
#format_axes(fig)
Path = "/home/nico/Documents/TEAR/Codes_TEAR/se2dr/Runs/P13/"
DataObj = SlipDataObject(Path+"SlipAtReceiver.txt")

fig, axis = GenericFigAxis()
fig.suptitle("Plastic Multiplier approach")

FilteringSpecs = {"FaultX":"FaultX", "FaultXValue":2000,
                  "FaultY":"FaultY", "FaultYValue":100, 
                  "q":0}
plt.ion()
#[item.PlotReference(axis[0], "Slip", filtering=True) for item in RefList]
#[item.PlotReference(axis[1], "SlipRate", filtering=True) for item in RefList]

Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":0})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":2000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":4000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":6000})
#format_axes(fig)<jupyter_output><empty_output><jupyter_text>P11$\dot{S} = \Delta V - \frac{\delta}{\mu}\ \frac{(f(t)-f(t-dt))}{dt}(-\sigma^{avg}_{yy}) $$dS = \dot{S}dt$$\gamma=\frac{dS}{2\delta} P_n(\phi/2\delta)$$S_{q}\ += dS$$\dot{S}_{q}=dS\ /\ dt$<jupyter_code>Path = "/home/nico/Documents/TEAR/Codes_TEAR/se2dr/Runs/TransectVersion50m/"
DataObj = SlipDataObject(Path + "SlipAtReceiver.txt")

fig, axis = GenericFigAxis()
fig.suptitle("Plastic Multiplier approach")

FilteringSpecs = {"FaultX":"FaultX", "FaultXValue":2000,
                  "FaultY":"FaultY", "FaultYValue":50, 
                  "q":0}
plt.ion()
#[item.PlotReference(axis[0], "Slip", filtering=True) for item in RefList]
#[item.PlotReference(axis[1], "SlipRate", filtering=True) for item in RefList]

Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":0})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":2000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":4000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":6000})
#format_axes(fig)


Path = "/home/nico/Documents/TEAR/Codes_TEAR/se2dr/Runs/TransectVersion/"
DataObj = SlipDataObject(Path + "SlipAtReceiver.txt")


FilteringSpecs = {"FaultX":"FaultX", "FaultXValue":2000,
                  "FaultY":"FaultY", "FaultYValue":100, 
                  "q":0}

Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":0})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":2000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":4000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":6000})
#format_axes(fig)
Path = "/home/nico/Documents/TEAR/Codes_TEAR/se2dr/Runs/TransectVersion50mdelta100/"
DataObj = SlipDataObject(Path + "SlipAtReceiver.txt")

fig, axis = GenericFigAxis()
fig.suptitle("Plastic Multiplier approach")

FilteringSpecs = {"FaultX":"FaultX", "FaultXValue":2000,
                  "FaultY":"FaultY", "FaultYValue":100, 
                  "q":0}
plt.ion()
#[item.PlotReference(axis[0], "Slip", filtering=True) for item in RefList]
#[item.PlotReference(axis[1], "SlipRate", filtering=True) for item in RefList]

Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":0})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":2000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":4000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":6000})
#format_axes(fig)


Path = "/home/nico/Documents/TEAR/Codes_TEAR/se2dr/Runs/TransectVersion/"
DataObj = SlipDataObject(Path + "SlipAtReceiver.txt")


FilteringSpecs = {"FaultX":"FaultX", "FaultXValue":2000,
                  "FaultY":"FaultY", "FaultYValue":100, 
                  "q":0}

Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":0})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":2000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":4000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":6000})
#format_axes(fig)
Path = "/home/nico/Documents/TEAR/Codes_TEAR/se2dr/Runs/TransectVersion/"
DataObj = SlipDataObject(Path + "SlipAtReceiver.txt")

fig, axis = GenericFigAxis()
fig.suptitle("Plastic Multiplier approach")

FilteringSpecs = {"FaultX":"FaultX", "FaultXValue":2000,
                  "FaultY":"FaultY", "FaultYValue":100, 
                  "q":0}
plt.ion()
#[item.PlotReference(axis[0], "Slip", filtering=True) for item in RefList]
#[item.PlotReference(axis[1], "SlipRate", filtering=True) for item in RefList]

Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":0})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":2000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":4000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":6000})
#format_axes(fig)


Path = "/home/nico/Documents/TEAR/Codes_TEAR/se2dr/Runs/PlasticMultiplier/"
DataObj = SlipDataObject(Path + "SlipAtReceiver.txt")


FilteringSpecs = {"FaultX":"FaultX", "FaultXValue":2000,
                  "FaultY":"FaultY", "FaultYValue":100, 
                  "q":0}

Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":0})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":2000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":4000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":6000})
#format_axes(fig)
Path = "/home/nico/Documents/TEAR/Codes_TEAR/se2dr/Runs/PlasticMultiplier2/"
DataObj = SlipDataObject(Path+"SlipAtReceiver.txt")

fig, axis = GenericFigAxis()
fig.suptitle("Plastic Multiplier approach")

FilteringSpecs = {"FaultX":"FaultX", "FaultXValue":2000,
                  "FaultY":"FaultY", "FaultYValue":100, 
                  "q":0}
plt.ion()
#[item.PlotReference(axis[0], "Slip", filtering=True) for item in RefList]
#[item.PlotReference(axis[1], "SlipRate", filtering=True) for item in RefList]

Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":0})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":2000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":4000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":6000})
#format_axes(fig)
Path = "/home/nico/Documents/TEAR/Codes_TEAR/se2dr/Runs/PlasticMultiplier/"
DataObj = SlipDataObject(Path + "SlipAtReceiver.txt")

fig, axis = GenericFigAxis()
fig.suptitle("Plastic Multiplier approach")

FilteringSpecs = {"FaultX":"FaultX", "FaultXValue":2000,
                  "FaultY":"FaultY", "FaultYValue":100, 
                  "q":0}
plt.ion()
#[item.PlotReference(axis[0], "Slip", filtering=True) for item in RefList]
#[item.PlotReference(axis[1], "SlipRate", filtering=True) for item in RefList]

Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":0})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":2000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":4000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":6000})
#format_axes(fig)


Path = "/home/nico/Documents/TEAR/Codes_TEAR/se2dr/Runs/PlasticMultiplier2/"
DataObj = SlipDataObject(Path + "SlipAtReceiver.txt")


FilteringSpecs = {"FaultX":"FaultX", "FaultXValue":2000,
                  "FaultY":"FaultY", "FaultYValue":100, 
                  "q":0}

Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":0})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":2000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":4000})
Plottings(fig, axis, DataObj, {**FilteringSpecs, "FaultXValue":6000})


#format_axes(fig)<jupyter_output><empty_output>
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