Subsections of Optional data

Energy step data

Energy step data is saved in energy_step_data.pkl if you set energy_step_flag = True in [option] section of cryspy.in. NumPy library is required to analyze this data file.

Warning

energy_step_flag = True is currently available only with VASP, QE, and soiap.

Info

In soiap, energy_step_data is collected only if loopa == 1. This is because other data (struc, force, and stress) are output only when loopa == 1. See, https://github.com/nbsato/soiap/blob/master/doc/instructions.md

Data format

  • type: dict
    • key: structure ID
    • value: list of energy step data in each stage
  • string form
    • {0: [array([-3.4439912 , -3.55040935, -3.66697038, ..]), array([-4.0613393 , -4.05445631, -4.06159641, …]), …],
      1: [array([-2.68209823, -2.69012487, -2.68364907, ..]), array([-2.79140967, -2.79183827, -2.79206508, …]), …],
      …}
  • unit of energy
    • eV/atom

How to access

import pickle
with open('energy_step_data.pkl', 'rb') as f:
    energy_step_data = pickle.load(f)

# energy_step_data[ID][stage][step]
# energy_step_data[ID][0] <-- stage 1
# energy_step_data[ID][1] <-- stage 2
#
# in LAQA
# energy_step_data[ID][selection][step]
# energy_step_data[ID][0] <-- 1st selection
# energy_step_data[ID][1] <-- 2nd selection

# ---------- energy step data of ID 3, stage 1
cid = 3      # ID
stage = 1    # stage
energy_step_data[cid][stage-1][:10]    # show only 10 enegies in jupyter

array([-3.4439912 , -3.55040935, -3.66697038, -3.77192063, -3.84320717,
       -3.80679245, -3.84633935, -3.87374706, -3.89123193, -3.90422926])

Structure step data

Structure step data is saved in struc_step_data.pkl if you set struc_step_flag = True in [option] section of cryspy.in. pymatgen library is required to analyze this data file.

Warning

struc_step_flag = True is currently available only with VASP, QE, and soiap.

Info

struc_step_data includes initial structures. For example, struc_step_data[cid][0][0] is the initial structure of ID = cid.

Data format

  • type: dict
    • key: structure ID
    • value: list of structure step data in each stage
  • string form
    • {0: [[Structure Summary …, Structure Summary, …], […], …],
      1: [[Structure Summary …, Structure Summary, …], […], …],
      …}
  • structure data format

How to access

import pickle
with open('struc_step_data.pkl', 'rb') as f:
    struc_step_data = pickle.load(f)

# struc_step_data[ID][stage][step]
# struc_step_data[ID][0] <-- stage 1
# struc_step_data[ID][1] <-- stage 2
#
#
# in LAQA
# struc_step_data[ID][selection][step]
# struc_step_data[ID][0] <-- 1st selection
# struc_step_data[ID][1] <-- 2nd selection

# ---------- structure step data of ID 3, stage 1, step 4
cid = 0      # ID
stage = 1    # stage
step = 0     # step index (start from 0)
struc_step_data[cid][stage-1][step]    # to show initial structure of ID 0 at stage 1 in jupyter

Structure Summary
Lattice
    abc : 5.727301 5.727301 4.405757
 angles : 90.0 90.0 90.0
 volume : 144.5175386563631
      A : 5.727301 0.0 0.0
      B : 0.0 5.727301 0.0
      C : 0.0 0.0 4.405757
PeriodicSite: Si (0.2506, 5.4767, 1.1014) [0.0438, 0.9562, 0.2500]
PeriodicSite: Si (2.6130, 3.1143, 1.1014) [0.4562, 0.5438, 0.2500]
PeriodicSite: Si (3.1143, 0.2506, 1.1014) [0.5438, 0.0438, 0.2500]
PeriodicSite: Si (5.4767, 2.6130, 1.1014) [0.9562, 0.4562, 0.2500]
PeriodicSite: Si (5.4767, 0.2506, 3.3043) [0.9562, 0.0438, 0.7500]
PeriodicSite: Si (3.1143, 2.6130, 3.3043) [0.5438, 0.4562, 0.7500]
PeriodicSite: Si (2.6130, 5.4767, 3.3043) [0.4562, 0.9562, 0.7500]
PeriodicSite: Si (0.2506, 3.1143, 3.3043) [0.0438, 0.5438, 0.7500]

Force step data

Force step data is saved in force_step_data.pkl if you set force_step_flag = True in [option] section of cryspy.in. NumPy library is required to analyze this data file.

Warning

force_step_flag = True is currently available only with VASP, QE, and soiap.

Data format

  • type: dict
    • key: structure ID
    • value: list of force step data in each stage
  • string form
    • {0: [array([[ 0.26314927, -0.26314927, -0. ], […], …[…]]), array([[…], …, […]]), …],
      1: [array([[ 0. , 0. , 0. ], […], …[…]]), array([[…], …, […]]), …],
      …}
  • unit of force
    • eV/Å

How to access

import pickle
with open('force_step_data.pkl', 'rb') as f:
    force_step_data = pickle.load(f)

# force_step_data[ID][stage][step][atom]
# force_step_data[ID][0] <-- stage 1
# force_step_data[ID][1] <-- stage 2
#
# in LAQA
# force_step_data[ID][selection][step][atom]
# force_step_data[ID][0] <-- 1st selection
# force_step_data[ID][1] <-- 2nd selection

# ---------- force step data of ID 3, stage 1
cid = 0      # ID
stage = 1    # stage
force_step_data[cid][stage-1][:3]    # to show only 3 steps in jupyter 

[array([[ 0.26314927, -0.26314927, -0.        ],
        [-0.26314927,  0.26314927, -0.        ],
        [ 0.26314927,  0.26314927,  0.        ],
        [-0.26314927, -0.26314927, -0.        ],
        [-0.26314927,  0.26314927, -0.        ],
        [ 0.26314927, -0.26314927,  0.        ],
        [-0.26314927, -0.26314927, -0.        ],
        [ 0.26314927,  0.26314927,  0.        ]]),
 array([[-0.12103692,  0.12103692,  0.        ],
        [ 0.12103692, -0.12103692, -0.        ],
        [-0.12103692, -0.12103692, -0.        ],
        [ 0.12103692,  0.12103692,  0.        ],
        [ 0.12103692, -0.12103692, -0.        ],
        [-0.12103692,  0.12103692,  0.        ],
        [ 0.12103692,  0.12103692,  0.        ],
        [-0.12103692, -0.12103692, -0.        ]]),
 array([[-0.29801618,  0.29801618,  0.        ],
        [ 0.29801618, -0.29801618, -0.        ],
        [-0.29801618, -0.29801618, -0.        ],
        [ 0.29801618,  0.29801618,  0.        ],
        [ 0.29801618, -0.29801618, -0.        ],
        [-0.29801618,  0.29801618,  0.        ],
        [ 0.29801618,  0.29801618,  0.        ],
        [-0.29801618, -0.29801618, -0.        ]])]

step = 0     # step index (start from 0)
atom = 2     # atom index (start from 0)
force_step_data[cid][stage-1][step][atom]

array([0.26314927, 0.26314927, 0.        ])

Stress step data

Stress step data is saved in stress_step_data.pkl if you set stress_step_flag = True in [option] section of cryspy.in. NumPy library is required to analyze this data file.

Warning

stress_step_flag = True is currently available only with VASP, QE, and soiap.

Data format

  • type: dict
    • key: structure ID
    • value: list of stress step data in each stage
  • string form
    • {0: [array([[-0.16770062, 0. , 0. ], […], […]]), array([[…], ]…], […]]), …],
      1: [array([[ 0.39260083, -0. , -0. ], […], […]]), array([[…], […], […]]), …],
      …}
  • unit of stress
    • eV/(Å**3)

How to access

import pickle
with open('stress_step_data.pkl', 'rb') as f:
    stress_step_data = pickle.load(f)

# stress_step_data[ID][stage][step][atom]
# stress_step_data[ID][0] <-- stage 1
# stress_step_data[ID][1] <-- stage 2
#
# in LAQA
# stress_step_data[ID][selection][step][atom]
# stress_step_data[ID][0] <-- 1st selection
# stress_step_data[ID][1] <-- 2nd selection

# ---------- stress step data of ID 3, stage 1
cid = 0      # ID
stage = 1    # stage
stress_step_data[cid][stage-1][:3]    # to show only 3 steps in jupyter 

[array([[-0.16770062,  0.        ,  0.        ],
        [ 0.        , -0.16770062, -0.        ],
        [ 0.        ,  0.        ,  0.21823358]]),
 array([[-0.16020785, -0.        , -0.        ],
        [-0.        , -0.16020785,  0.        ],
        [-0.        ,  0.        ,  0.18646321]]),
 array([[-0.13572003, -0.        ,  0.        ],
        [-0.        , -0.13572003,  0.        ],
        [-0.        ,  0.        ,  0.15953926]])]