import numpy as np
import matplotlib.pyplot as plt
from math import log
from rsfmodel import rsf

# This is really just the Ruina realtion, but let's pretend we invented it!
# We'll inherit attributes from rsf.StateRelation, but you wouldn't have to.
# It does provide velocity contribution calcualtion for us though!


class MyStateRelation(rsf.StateRelation):
    # Need to provide a steady state calcualtion method
    def _set_steady_state(self, system):
        self.state = self.Dc/system.vref

    def evolve_state(self, system):
        if self.state is None:
            self.state = _set_steady_state(self, system)

        return -1 * (system.v * self.state / self.Dc) * log(system.v * self.state / self.Dc)

model = rsf.Model()

# Set model initial conditions
model.mu0 = 0.6  # Friction initial (at the reference velocity)
model.a = 0.01  # Empirical coefficient for the direct effect
model.k = 1e-3  # Normalized System stiffness (friction/micron)
model.v = 1.  # Initial slider velocity, generally is vlp(t=0)
model.vref = 1.  # Reference velocity, generally vlp(t=0)

state1 = MyStateRelation(model)
state1.b = 0.005  # Empirical coefficient for the evolution effect
state1.Dc = 10.  # Critical slip distance

model.state_relations = [state1]  # Which state relation we want to use

# We want to solve for 40 seconds at 100Hz
model.time = np.arange(0, 40.01, 0.01)

# We want to slide at 1 um/s for 10 s, then at 10 um/s for 31
lp_velocity = np.ones_like(model.time)
lp_velocity[10*100:] = 10.  # Velocity after 10 seconds is 10 um/s

# Set the model load point velocity, must be same shape as model.model_time
model.loadpoint_velocity = lp_velocity

# Run the model!
model.solve()

# Make the phase plot
rsf.phasePlot(model)

# Make a plot in displacement
rsf.dispPlot(model)

# Make a plot in time
rsf.timePlot(model)

import numpy as np
import matplotlib.pyplot as plt
from math import log
from rsfmodel import rsf

# This is really just the Ruina realtion, but let's pretend we invented it!
# We'll inherit attributes from rsf.StateRelation, but you wouldn't have to.
# It does provide velocity contribution calculation for us though!


class MyStateRelation(rsf.StateRelation):
    # Need to provide a steady state calcualtion method
    def _set_steady_state(self, system):
        self.state = self.Dc/system.vref

    def evolve_state(self, system):
        if self.state is None:
            self.state = _set_steady_state(self, system)

        return -1 * (system.v * self.state / self.Dc) * log(system.v * self.state / self.Dc)

model = rsf.Model()

# Set model initial conditions
model.mu0 = 0.6  # Friction initial (at the reference velocity)
model.a = 0.01  # Empirical coefficient for the direct effect
model.k = 1e-3  # Normalized System stiffness (friction/micron)
model.v = 1.  # Initial slider velocity, generally is vlp(t=0)
model.vref = 1.  # Reference velocity, generally vlp(t=0)

state1 = MyStateRelation(model)
state1.b = 0.005  # Empirical coefficient for the evolution effect
state1.Dc = 10.  # Critical slip distance

model.state_relations = [state1]  # Which state relation we want to use

# We want to solve for 40 seconds at 100Hz
model.time = np.arange(0, 40.01, 0.01)

# We want to slide at 1 um/s for 10 s, then at 10 um/s for 31
lp_velocity = np.ones_like(model.time)
lp_velocity[10*100:] = 10.  # Velocity after 10 seconds is 10 um/s

# Set the model load point velocity, must be same shape as model.model_time
model.loadpoint_velocity = lp_velocity

# Run the model!
model.solve()

# Make the phase plot
rsf.phasePlot(model)

# Make a plot in displacement
rsf.dispPlot(model)

# Make a plot in time
rsf.timePlot(model)

Fix spelling error