namd_analyse.py

"""
==============================================================================
ANALYSIS OF THE INITIAL (DIMENSION-ADAPTIVE) STCOHASTIC COLLOCATION CAMPAIGN

Execute once.
==============================================================================
"""

import easyvvuq as uq
import os

#from custom import CustomEncoder
class SimEncoder(uq.encoders.JinjaEncoder, encoder_name='SimEncoder'):
    def encode(self, params={}, target_dir='', fixtures=None):

        simulation_time = 10**params["simulation_time_power"]
        params["n_steps"] = int( round( simulation_time / params["timestep"], -1 ) )
        # 48 as the number of cores on a node (see anaysis.sh)
        params["dcd_freq"] = min(int(params["n_steps"]/48), 5000)
        super().encode(params, target_dir, fixtures)

class Eq1Encoder(uq.encoders.JinjaEncoder, encoder_name='Eq1Encoder'):
    def encode(self, params={}, target_dir='', fixtures=None):

        simulation_time = 10**params["equilibration1_time_power"]
        params["n_steps"] = int( round( simulation_time / params["timestep"], -1 ) )
        super().encode(params, target_dir, fixtures)

class Eq2Encoder(uq.encoders.JinjaEncoder, encoder_name='Eq2Encoder'):
    def encode(self, params={}, target_dir='', fixtures=None):

        simulation_time = 10**params["equilibration2_time_power"]
        params["n_steps_loop"] = int( round( simulation_time / params["timestep"], -1 ) )
        params["n_steps"] = 15*int( round( simulation_time / params["timestep"], -1 ) )
        super().encode(params, target_dir, fixtures)

home = os.path.abspath(os.path.dirname(__file__))
#output_columns = ["drug","replica","binding_energy_avg","binding_energy_stdev"]
output_columns = ["binding_energy_avg"]
work_dir = '/hppfs/work/pn72qu/di36yax3/tmp/uq_namd2/campaigns'

campaign = uq.Campaign(state_file="namd_easyvvuq_state.json",
                       work_dir=work_dir)
print('========================================================')
print('Reloaded campaign', campaign.campaign_dir.split('/')[-1])
print('========================================================')
sampler = campaign.get_active_sampler()
sampler.load_state("namd_sampler_state.pickle")
campaign.set_sampler(sampler)

#get results
#fab.get_uq_samples(config, campaign.campaign_dir, sampler._number_of_samples,
#                   machine='eagle_vecma')
campaign.collate()

# Post-processing analysis
analysis = uq.analysis.SCAnalysis(
    sampler=campaign._active_sampler,
    qoi_cols=output_columns
)

campaign.apply_analysis(analysis)

#this is a temporary subroutine which saves the entire state of
#the analysis in a pickle file. The proper place for this is the database
analysis.save_state("namd_analysis_state.pickle")