def run_timestep_experiment_low_gamma_high_particles():
timesteps = np.logspace(start=0, stop=-4, num=15)
test_params = {
"particle_count": 20 * [501],
"gamma": [0.01],
"G": ["Smooth"],
"scaling": ["Local"],
"D": [0.25],
"phi": ["Gamma"],
"initial_dist_x": ["two_clusters_2N_N"],
"initial_dist_v": ["2N_N_cluster_const"],
"T_end": [200.0],
"dt": timesteps.tolist(),
"option": ["numba"],
}
os.chdir("E:/")
history = processing.get_master_yaml(yaml_path="timestep_experiments")
fn = "LowGammaLoweringTimestepHighParticles"
processing.run_experiment(test_params, history, experiment_name=fn)
print(
"Running reduced timestep with gamma =0.01 and N=500 --- does non-uniformity persist?"
)
def run_timestep_experiment_phi_uniform():
timesteps = np.logspace(start=0, stop=-4, num=15)
test_params = {
"particle_count":
10 * [99, 501], # (3 * np.arange(8, 150, 16)).tolist(),
"G": ["Smooth"],
"scaling": ["Local"],
"D": [0.25],
"phi": ["Uniform"],
"initial_dist_x": ["two_clusters_2N_N"],
"initial_dist_v": ["2N_N_cluster_const"],
"T_end": [200.0],
"dt": timesteps.tolist(),
"option": ["numba"],
}
os.chdir("E:/")
history = processing.get_master_yaml(yaml_path="timestep_experiments")
fn = "UniformInteractionLoweringTimestep"
processing.run_experiment(test_params, history, experiment_name=fn)
print(
"Running reduced timestep with phi=1 --- post-process to check against gamma =0.5"
)
import particle.processing as processing
particles = 100
test_params = {
"particle_count":
100 * [particles], # (3 * np.arange(8, 150, 16)).tolist(),
# "gamma": (np.arange(0.2, 0.5, 0.05)).tolist(),
"G": ["Smooth"],
"scaling": ["Local"],
"D": [1.0],
"phi": ["Gamma"],
"gamma": [0.1],
"initial_dist_x": ["uniform_dn"],
"initial_dist_v": ["pos_normal_dn"],
"T_end": [2000.0],
"dt": [0.01],
"option": ["numba"],
}
history = processing.get_master_yaml(yaml_path="experiments_ran")
# fn = (
# f"""{test_params["initial_dist_v"][0]}_"""
# f"""vel_{test_params["scaling"][0]}_G{test_params["G"][0]}_"""
# f"""T{int(test_params["T_end"][0])}_noise_report_Galpha"""
# )
fn = f"""PSMean0"""
processing.run_experiment(test_params, history, experiment_name=fn)
# sim_parameters = {
# "particle_count": [2000],
# "D": [0.25],
# "G": ["Garnier"],
# "alpha": [8],
# "scaling": ["Global"],
# "phi": ["Normalised Gamma"],
# "gamma": [0.1],
# "initial_dist_x": ["one_cluster"],
# "initial_dist_v": ["pos_normal_dn"],
# "T_end": [200.0],
# "dt": [0.005],
# "option": ["numba"],
# "record_time": [0.25],
# }
# history = processing.get_master_yaml(yaml_path="experiments_ran")
# fn = (
# f"""{test_params["initial_dist_v"][0]}_"""
# f"""vel_{test_params["scaling"][0]}_G{test_params["G"][0]}_"""
# f"""T{int(test_params["T_end"][0])}_noise_report_Galpha"""
# )
os.chdir("D:/InteractingParticleSystems/noisysystem_temp")
# os.chdir("/exports/eddie/scratch/s1415551")
fn = "OneClusterVaryNormalisedGammaLocalHigherNoise"
processing.run_experiment(sim_parameters, experiment_name=fn)
print(
"Ran for Local Scaling", sim_parameters,
)