Coverage for examples/calc_rdf_from_h5.py: 86%

1""" Minimal example for calculing rdf from existing data """ 

2 

3import os 

4 

5import gamdpy as gp 

6 

7file_to_read = "LJ_T0.70.h5" 

8 

9if not os.path.isfile(file_to_read): 

10 print("This example needs a the file LJ_T0.70.h5 to be present") 

11 print(f"{file_to_read} can be generated using minimal.py example") 

12 exit() 

13 

14# Load existing data 

15output = gp.tools.TrajectoryIO(file_to_read).get_h5() 

16# Read number of particles N and dimensions from data 

17nblocks, nconfs, N, D = output['trajectory_saver/positions'].shape 

18 

19# Create configuration object 

20configuration = gp.Configuration(D=D, N=N) 

21configuration.simbox = gp.Orthorhombic(D, output['initial_configuration'].attrs['simbox_data']) 

22configuration.ptype = output['initial_configuration/ptype'] 

23configuration.copy_to_device() 

24# Call the rdf calculator 

25calc_rdf = gp.CalculatorRadialDistribution(configuration, bins=1000) 

26 

27# NOTE: the structure of the block is (outer_block, inner_steps, pos&img, npart, dimensions) 

28# the zero is to select the position array and discard images 

29positions = output['trajectory_saver/positions'][:,:,:,:] 

30positions = positions.reshape(nblocks*nconfs,N,D) 

31# Loop over saved configurations 

32for pos in positions[nconfs-1::nconfs]: 

33 configuration['r'] = pos 

34 configuration.copy_to_device() 

35 calc_rdf.update() 

36 

37# Save rdf 

38calc_rdf.save_average() 

39