print """---
timestep: $(step)
pe: $(pe)
ke: $(ke)
...""" file current_state.yaml screen no

---
timestep: 250
pe: -4.7774327356321810711
ke: 2.4962152903997174569

print """{
  "timestep": $(step),
  "pe": $(pe),
  "ke": $(ke)
}""" file current_state.json screen no

{
  "timestep": 250,
  "pe": -4.7774327356321810711,
  "ke": 2.4962152903997174569
}

import yaml
try:
    from yaml import CSafeLoader as YamlLoader
except ImportError:
    from yaml import SafeLoader as YamlLoader

timesteps = []
with open("dump.yaml", "r") as f:
    data = yaml.load_all(f, Loader=YamlLoader)

    for d in data:
        print('Processing timestep %d' % d['timestep'])
        timesteps.append(d)

print('Read %d timesteps from yaml dump' % len(timesteps))
print('Second timestep: ', timesteps[1]['timestep'])
print('Box info: x: ' , timesteps[1]['box'][0], ' y:', timesteps[1]['box'][1], ' z:',timesteps[1]['box'][2])
print('First 5 per-atom columns: ', timesteps[1]['keywords'][0:5])
print('Corresponding 10th atom data: ', timesteps[1]['data'][9][0:5])

Processing timestep 0
Processing timestep 50
Processing timestep 100
Processing timestep 150
Processing timestep 200
Processing timestep 250
Read 6 timesteps from yaml dump
Second timestep:  50
Box info: x:  [0, 16.795961913825074]  y: [0, 16.795961913825074]  z: [0, 16.795961913825074]
First 5 per-atom columns:  ['id', 'type', 'x', 'y', 'z']
Corresponding 10th atom data:  [10, 1, 4.43828, 0.968481, 0.108555]

​

import re, yaml
import pandas as pd
import matplotlib.pyplot as plt

try:
    from yaml import CSafeLoader as Loader
except ImportError:
    from yaml import SafeLoader as Loader

docs = ""
with open("log.lammps") as f:
    for line in f:
        m = re.search(r"^(keywords:.*$|data:$|---$|\.\.\.$|  - \[.*\]$)", line)
        if m: docs += m.group(0) + '\n'

thermo = list(yaml.load_all(docs, Loader=Loader))

df = pd.DataFrame(data=thermo[0]['data'], columns=thermo[0]['keywords'])
fig = df.plot(x='Step', y=['E_bond', 'E_angle', 'E_dihed', 'E_impro'], ylabel='Energy in kcal/mol')
plt.savefig('thermo_bondeng.png')

import yaml
import pandas as pd

try:
    from yaml import CSafeLoader as Loader
except ImportError:
    from yaml import SafeLoader as Loader

with open("ave.yaml") as f:
    ave = yaml.load(f, Loader=Loader)

keys = ave['keywords']
df = {}
for k in ave['data'].keys():
    df[k] = pd.DataFrame(data=ave['data'][k], columns=keys)

# create multi-index data frame
df = pd.concat(df)

# output only the first 3 value for steps 200 to 300 of the column Pressure
idx = pd.IndexSlice
print(df['Pressure'].loc[idx[200:300, 0:2]])

use YAML::XS;

open(LOG, "log.lammps") or die("could not open log.lammps: $!");
my $file = "";
while(my $line = <LOG>) {
    if ($line =~ /^(keywords:.*$|data:$|---$|\.\.\.$|  - \[.*\]$)/) {
        $file .= $line;
    }
}
close(LOG);

# convert YAML to perl as nested hash and array references
my $thermo = Load $file;

# convert references to real arrays
my @keywords = @{$thermo->{'keywords'}};
my @data = @{$thermo->{'data'}};

# print first two columns
print("$keywords[0] $keywords[1]\n");
foreach (@data) {
    print("${$_}[0]  ${$_}[1]\n");
}

fix extra all print 50 """
- timestep: $(step)
  pe: $(pe)
  ke: $(ke)""" file output.yaml screen no

# Fix print output for fix extra
- timestep: 0
  pe: -6.77336805325924729
  ke: 4.4988750000000026219

- timestep: 50
  pe: -4.8082494418323200591
  ke: 2.5257981827119797558

- timestep: 100
  pe: -4.7875608875581505686
  ke: 2.5062598821985102582

- timestep: 150
  pe: -4.7471033686005483787
  ke: 2.466095925545450207

- timestep: 200
  pe: -4.7509052858544134068
  ke: 2.4701136792591693592

- timestep: 250
  pe: -4.7774327356321810711
  ke: 2.4962152903997174569

import yaml

with open("output.yaml") as f:
   data = yaml.load(f, Loader=yaml.FullLoader)

print(data)

[{'timestep': 0, 'pe': -6.773368053259247, 'ke': 4.498875000000003}, {'timestep': 50, 'pe': -4.80824944183232, 'ke': 2.5257981827119798}, {'timestep': 100, 'pe': -4.787560887558151, 'ke': 2.5062598821985103}, {'timestep': 150, 'pe': -4.747103368600548, 'ke': 2.46609592554545}, {'timestep': 200, 'pe': -4.750905285854413, 'ke': 2.4701136792591694}, {'timestep': 250, 'pe': -4.777432735632181, 'ke': 2.4962152903997175}]