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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:
 Running on 4 cores with 30 gb RAM
Step1:  Timing individual functions
Step2:  Testing pipeline as a whole
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Python Code:
import analysis3 as a3
reload(a3)
import time
def time_function(fun, *args):
    start = time.time();
    result = fun(*args);
    run_time = time.time() - start;
    minutes = run_time / 60;
    print('RUN TIME: %f s (%f m)' % (run_time, minutes));
    return result;
Explanation: Running on 4 cores with 30 gb RAM
End of explanation
token = 's275_to_ara3'
cert_path = '../userToken.pem'
time_function(a3.get_registered, token, cert_path);
path = "img/" + token + "_regis.nii"
im = time_function(a3.apply_clahe, path);
output_ds = time_function(a3.downsample, im, 10000);
time_function(a3.save_points, output_ds, "points/" + token + ".csv");
points_path = "points/" + token + ".csv";
time_function(a3.generate_pointcloud, points_path, "output/" + token + "_pointcloud.html");
time_function(a3.get_atlas_annotate, cert_path, True, None);
time_function(a3.get_regions, points_path, "atlas/ara3_annotation.nii", "points/" + token + "_regions.csv");
points_region_path = "points/" + token + "_regions.csv";
g = time_function(a3.create_graph, points_region_path, 20, "graphml/" + token + "_graph.graphml");
time_function(a3.plot_graphml3d, g, False, "output/" + token + "_edgegraph.html");
time_function(a3.generate_region_graph, token, points_region_path, "output/" + token + "_regions.html");
time_function(a3.generate_density_graph, "graphml/" + token + "_graph.graphml", 
              "output/" + token + "_density.html", "False-Color Density of " + token);
print("Completed pipeline...!")
Explanation: Timing individual functions
End of explanation
token = 's275_to_ara3'
cert_path = '../userToken.pem'
time_function(a3.run_pipeline, token, cert_path, 5);
Explanation: Testing pipeline as a whole
End of explanation
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