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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 PyBroMo - GUI Trajectory explorer
<small><i>
This notebook is part of PyBroMo a 
python-based single-molecule Brownian motion diffusion simulator 
that simulates confocal smFRET
experiments. You can find the full list of notebooks in 
Usage Examples.
</i></small>
Overview
In this notebook implements an interactive 3-D trajectories visualizer. To visualize trajectories you need simulatte the trajectories first.
For more info see PyBroMo Homepage.
Simulation setup
Together with a few standard python libraries we import PyBroMo using the short name pbm. 
All PyBroMo functions will be available as pbm.something.
Step1:  Load trajectories
Step2:  Plotting the emission
Step3:  For simulations using radial = False (i.e. the 3D trajectories saved)
Step4:  For simulations using radial = True (i.e. the z-r 2D trajectories saved)
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Python Code:
%matplotlib inline
import numpy as np
import tables
import matplotlib.pyplot as plt
plt.rcParams['path.simplify_threshold'] = 1.0
import pybromo as pbm
print('Numpy version:', np.__version__)
print('Matplotlib version:', plt.matplotlib.__version__)
print('PyTables version:', tables.__version__)
print('PyBroMo version:', pbm.__version__)
Explanation: PyBroMo - GUI Trajectory explorer
<small><i>
This notebook is part of PyBroMo a 
python-based single-molecule Brownian motion diffusion simulator 
that simulates confocal smFRET
experiments. You can find the full list of notebooks in 
Usage Examples.
</i></small>
Overview
In this notebook implements an interactive 3-D trajectories visualizer. To visualize trajectories you need simulatte the trajectories first.
For more info see PyBroMo Homepage.
Simulation setup
Together with a few standard python libraries we import PyBroMo using the short name pbm. 
All PyBroMo functions will be available as pbm.something.
End of explanation
#SIM_DIR = r'E:\Data\pybromo'
S = pbm.ParticlesSimulation.from_datafile('016') #, path=SIM_DIR)
Explanation: Load trajectories
End of explanation
%matplotlib qt
p = pbm.plotter.EmissionPlotter(S, duration=0.1, decimate=100, color_pop=False)
Explanation: Plotting the emission
End of explanation
p = pbm.plotter.TrackEmPlotter(S, duration=0.005, decimate=20)
Explanation: For simulations using radial = False (i.e. the 3D trajectories saved):
End of explanation
p = pbm.plotter.TrackEmPlotterR(S, duration=0.01, decimate=100)
Explanation: For simulations using radial = True (i.e. the z-r 2D trajectories saved):
End of explanation
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