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‎.github/workflows/build.yml

+1-1
Original file line numberDiff line numberDiff line change
@@ -21,4 +21,4 @@ jobs:
2121
env:
2222
SANDBOX_TOKEN: ${{ secrets.SANDBOX_TOKEN }}
2323
with:
24-
showyourwork-spec: git+https://github.com/thomasckng/showyourwork
24+
showyourwork-spec: git+https://github.com/showyourwork/showyourwork

‎Snakefile

+29-48
Original file line numberDiff line numberDiff line change
@@ -49,7 +49,7 @@ rule:
4949
[f'src/data/random_walks/kinisi/rw_1_{atoms}_128_s512.npz' for atoms in [16, 32, 64, 128, 256, 512, 1024]],
5050
[f'src/data/random_walks/weighted/rw_1_{atoms}_128_s512.npz' for atoms in [16, 32, 64, 128, 256, 512, 1024]],
5151
[f'src/data/random_walks/ordinary/rw_1_{atoms}_128_s512.npz' for atoms in [16, 32, 64, 128, 256, 512, 1024]],
52-
[f'src/data/random_walks/numerical/D_1_{atoms}_128.npz' for atoms in [16, 32, 64, 128, 256, 512, 1024]]
52+
[f'src/data/random_walks/numerical/D_1_{atoms}_128.npz' for atoms in [16, 32, 64, 128, 256, 512, 1024]],
5353
output:
5454
f'src/data/random_walks/stat_eff.npz'
5555
conda:
@@ -58,7 +58,6 @@ rule:
5858
True
5959
params:
6060
correlation='true'
61-
priority: 50
6261
script:
6362
"src/code/random_walks/stat_eff.py"
6463

@@ -124,26 +123,6 @@ rule rw_4096_pyblock_true_128:
124123
script:
125124
f'src/code/random_walks/kinisi_pyblock_rw.py'
126125

127-
# Random walks simulations
128-
rule rw_4096_pyblock_modelfree_true_128:
129-
input:
130-
f'src/code/random_walks/kinisi_pyblock_modelfree_rw.py',
131-
'src/code/random_walks/random_walk.py'
132-
output:
133-
f'src/data/random_walks/pyblock_modelfree/rw_1_128_128_s4096.npz'
134-
conda:
135-
'environment.yml'
136-
cache:
137-
True
138-
params:
139-
jump=2.4494897428,
140-
atoms=128,
141-
length=128,
142-
correlation='true',
143-
n=4096
144-
script:
145-
f'src/code/random_walks/kinisi_pyblock_modelfree_rw.py'
146-
147126
# Length variation random walks
148127
for length in [16, 32, 64, 128, 256, 512, 1024]:
149128
rule:
@@ -389,58 +368,60 @@ rule rw_4096_true_cov_true_128:
389368
script:
390369
f'src/code/random_walks/truecov_rw.py'
391370

392-
for start_diff in [0, 2, 4, 6, 8, 10, 15, 20]:
371+
for l in [10000]:
393372
for n in range(0, 6, 1):
394373
rule:
395374
name:
396-
f"llzo_many_{n}_{start_diff}"
375+
f"llzo_many_{n}_10_{l}"
397376
input:
398377
'src/code/llzo/many_runs.py',
399-
# f'src/data/llzo/traj{n}.xyz'
378+
f'src/data/llzo/traj{n}.out'
400379
output:
401-
f'src/data/llzo/diffusion_{n}_{start_diff}.npz'
380+
f'src/data/llzo/diffusion_{n}_10_{l}.npz'
402381

403382
conda:
404383
'environment.yml'
405384
cache:
406385
True
407386
params:
408387
n=n,
409-
start_diff=start_diff
388+
start_diff=10,
389+
length=l
410390
script:
411391
"src/code/llzo/many_runs.py"
412392

413393
rule:
414394
name:
415-
f"true_D_llzo_{start_diff}"
395+
f"true_D_llzo_10_{l}"
416396
input:
417397
'src/code/llzo/true_ls.py',
418-
[f'src/data/llzo/diffusion_{n}_{start_diff}.npz' for n in range(0, 6, 1)]
398+
[f'src/data/llzo/diffusion_{n}_10_{l}.npz' for n in range(0, 6, 1)]
419399
output:
420-
f'src/data/llzo/true_{start_diff}.npz'
400+
f'src/data/llzo/true_10_{l}.npz'
421401
conda:
422402
'environment.yml'
423403
cache:
424404
True
425405
params:
426-
start_diff=start_diff
406+
start_diff=10,
407+
length=l
427408
script:
428409
"src/code/llzo/true_ls.py"
429410

430-
rule:
431-
name:
432-
f"glswlsols_D_llzo_{start_diff}"
433-
input:
434-
'src/code/llzo/glswlsols.py',
435-
[f'src/data/llzo/diffusion_{n}_{start_diff}.npz' for n in range(0, 6, 1)]
436-
output:
437-
f'src/data/llzo/glswlsols_{start_diff}.npz'
438-
conda:
439-
'environment.yml'
440-
cache:
441-
True
442-
params:
443-
start_diff=start_diff
444-
script:
445-
"src/code/llzo/glswlsols.py"
446-
411+
rule:
412+
name:
413+
f"glswlsols_D_llzo_10_10000"
414+
input:
415+
'src/code/llzo/glswlsols.py',
416+
[f'src/data/llzo/diffusion_{n}_10_10000.npz' for n in range(0, 6, 1)]
417+
output:
418+
f'src/data/llzo/glswlsols_10_10000.npz'
419+
conda:
420+
'environment.yml'
421+
cache:
422+
True
423+
params:
424+
start_diff=10,
425+
length=10000
426+
script:
427+
"src/code/llzo/glswlsols.py"

‎environment.yml

+4-3
Original file line numberDiff line numberDiff line change
@@ -2,13 +2,14 @@ channels:
22
- defaults
33
- conda-forge
44
dependencies:
5-
- numpy=1.23.1
5+
- numpy=1.26.4
66
- pip=21.3.1
77
- python=3.10
8-
- scipy=1.9.3
8+
- scipy=1.12.0
99
- scikit-learn=1.1.3
1010
- mdanalysis=2.6.1
1111
- pip:
1212
- matplotlib==3.8.2
13+
- seaborn==0.13.2
1314
- pyblock==0.6
14-
- git+https://github.com/bjmorgan/kinisi.git@with-f
15+
- git+https://github.com/bjmorgan/kinisi.git

‎showyourwork.yml

+4-5
Original file line numberDiff line numberDiff line change
@@ -34,9 +34,9 @@ dependencies:
3434
- src/data/random_walks/kinisi/rw_1_128_128_s4096.npz
3535
- src/data/random_walks/numerical/D_1_128_128.npz
3636
src/scripts/diffusion.py:
37-
- src/data/llzo/true_10.npz
37+
- src/data/llzo/true_10_10000.npz
3838
{% for n in range(0, 6, 1) %}
39-
- src/data/llzo/diffusion_{{n}}_10.npz
39+
- src/data/llzo/diffusion_{{n}}_10_10000.npz
4040
{% endfor %}
4141
- src/scripts/utils/_fig_params.py
4242
src/scripts/covariances.py:
@@ -45,16 +45,15 @@ dependencies:
4545
- src/scripts/utils/_fig_params.py
4646
src/scripts/true_cov.py:
4747
- src/data/random_walks/numerical/D_1_128_128.npz
48-
- src/data/random_walks/numerical/D_1_128_1024.npz
4948
- src/data/random_walks/true_cov/rw_1_128_128_s4096.npz
5049
- src/scripts/utils/_fig_params.py
5150
src/scripts/stat_eff.py:
5251
- src/data/random_walks/stat_eff.npz
5352
- src/scripts/utils/_fig_params.py
5453
src/scripts/glswlsols_llzo.py:
55-
- src/data/llzo/glswlsols_10.npz
54+
- src/data/llzo/glswlsols_10_10000.npz
55+
- src/data/llzo/true_10_10000.npz
5656
src/scripts/pyblock.py:
5757
- src/data/random_walks/numerical/D_1_128_128.npz
5858
- src/data/random_walks/kinisi/rw_1_128_128_s4096.npz
5959
- src/data/random_walks/pyblock/rw_1_128_128_s4096.npz
60-
- src/data/random_walks/pyblock_modelfree/rw_1_128_128_s4096.npz

‎src/code/llzo/glswlsols.py

+6-6
Original file line numberDiff line numberDiff line change
@@ -13,15 +13,15 @@
1313
np.random.seed(1)
1414

1515
start_diff = snakemake.params['start_diff']
16+
length = snakemake.params['length']
1617

17-
timestep = np.load(f'src/data/llzo/diffusion_0_{start_diff}.npz')['dt'][0, 0]
18-
length = 2000
18+
timestep = np.load(f'src/data/llzo/diffusion_0_{start_diff}_{length}.npz')['dt'][0, 0]
1919
ll = len([i + length for i in range(0, 20001 - length, length)])
2020
# length = 500
2121
# ll = len([i + length for i in range(0, 2000, length)])
22-
d = np.zeros((6, 8, ll, timestep.size))
23-
for i in range(0, 6, 1):
24-
d[i] = np.load(f'src/data/llzo/diffusion_{i}_{start_diff}.npz')['msd_true']
22+
d = np.zeros((5, 16, ll, timestep.size))
23+
for i in range(1, 6, 1):
24+
d[i-1] = np.load(f'src/data/llzo/diffusion_{i}_{start_diff}_{length}.npz')['msd_true']
2525

2626
max_ngp = np.argwhere(timestep > start_diff)[0][0]
2727
true_msd = d.reshape(-1, d.shape[-1])[:, max_ngp:]
@@ -45,7 +45,7 @@
4545
for i in true_msd:
4646
c3.append(linregress(timestep, i).stderr / 6e4)
4747

48-
np.savez(f'src/data/llzo/glswlsols_{start_diff}.npz',
48+
np.savez(f'src/data/llzo/glswlsols_{start_diff}_{length}.npz',
4949
gls_pop=g1,
5050
wls_pop=g2,
5151
ols_pop=g3,

‎src/code/llzo/many_runs.py

+18-18
Original file line numberDiff line numberDiff line change
@@ -1,12 +1,20 @@
11
import MDAnalysis as mda
22
import numpy as np
33
from kinisi.parser import MDAnalysisParser
4-
from kinisi.diffusion import MSDDiffusion
4+
from kinisi.diffusion import MSDBootstrap
55

66
n = snakemake.params['n']
77
start_diff = snakemake.params['start_diff']
8+
length = snakemake.params['length']
89

9-
step = 8
10+
step = 16
11+
n_atoms_drift = int((1536-448) / step)
12+
n_atoms_li = int(448 / step)
13+
rng = np.random.RandomState(n*42)
14+
np.random.seed(n*42)
15+
choice_drift = rng.choice(np.arange(0, 1536-448, dtype=int), size=(step, n_atoms_drift), replace=False)
16+
choice_li = rng.choice(np.arange(1536-448, 1536, dtype=int), size=(step, n_atoms_li), replace=False)
17+
choice = np.concatenate([choice_drift, choice_li], axis=-1)
1018

1119
def universe_slice(data: str, slice_start: int, slice_end: int, m: int) -> mda.Universe:
1220
"""
@@ -18,18 +26,17 @@ def universe_slice(data: str, slice_start: int, slice_end: int, m: int) -> mda.U
1826
:return: A single flattened Universe
1927
"""
2028
data_reshape = np.copy(data).reshape(-1, 1536, 3)
21-
data_subset = data_reshape[slice_start:slice_end, m::step]
29+
data_subset = data_reshape[slice_start:slice_end, choice_li[m]]
2230
data_subset *= 0.52917721067
2331
u = mda.Universe.empty(data_subset.shape[1], 1, n_frames=data_subset.shape[0], trajectory=True)
24-
list_type = ['A'] * (1536-448) + ['Li'] * 448
25-
u.add_TopologyAttr('type', list_type[m::step])
32+
list_type = np.array(['Li'] * n_atoms_li)
33+
u.add_TopologyAttr('type', list(list_type))
2634
for i, t in enumerate(u.trajectory):
2735
t.positions = data_subset[i]
2836
t.dimensions = np.array([26.30938114, 26.30938114, 26.30938114, 90, 90, 90])
2937
return u
3038

3139
data = np.loadtxt(f'src/data/llzo/traj{n}.out', usecols=[0, 1, 2])
32-
length = 2000
3340
uu = universe_slice(data, 0, length, 0)
3441
step_skip = 100 # sampling rate
3542
timestep = 5.079648e-4 # ps
@@ -45,21 +52,16 @@ def universe_slice(data: str, slice_start: int, slice_end: int, m: int) -> mda.U
4552
cov = np.zeros((step, ll, p.delta_t[np.where(p.delta_t > start_diff)].size, p.delta_t[np.where(p.delta_t > start_diff)].size))
4653
d = np.zeros((step, ll, 3200))
4754
g = np.zeros((step, ll, 3200))
48-
f = np.zeros((step, ll, p.delta_t.size))
4955
intercept = np.zeros((step, ll, 3200))
5056

5157
for m in range(0, step, 1):
5258
for i, slice in enumerate(range(0, 20001 - length, length)):
5359
uu = universe_slice(data, slice, slice+length, m)
5460

55-
rng = np.random.RandomState(42)
56-
np.random.seed(42)
57-
58-
da_params = {'specie': 'Li', 'time_step': timestep, 'step_skip': step_skip}
61+
da_params = {'specie': 'Li', 'time_step': timestep, 'step_skip': step_skip, 'progress': False}
5962
p = MDAnalysisParser(uu, **da_params)
60-
b = MSDDiffusion(p.delta_t, p.disp_3d, p._n_o)
61-
b.diffusion(start_diff, random_state=rng)
62-
# print(b._popt)
63+
b = MSDBootstrap(p.delta_t, p.disp_3d, p._n_o, progress=False)
64+
b.diffusion(start_diff, random_state=rng, progress=False)
6365
dt[m, i] = b.dt
6466
msd[m, i] = b.n
6567
msd_true[m, i] = b.n
@@ -68,10 +70,9 @@ def universe_slice(data: str, slice_start: int, slice_end: int, m: int) -> mda.U
6870
cov[m, i] = b.covariance_matrix
6971
d[m, i] = b.D.samples
7072
g[m, i] = b.gradient.samples
71-
f[m, i] = b._hr
7273
intercept[m, i] = b.intercept.samples
73-
74-
np.savez(f'src/data/llzo/diffusion_{n}_{start_diff}.npz',
74+
75+
np.savez(f'src/data/llzo/diffusion_{n}_{start_diff}_{length}.npz',
7576
dt=dt,
7677
msd_true=msd_true,
7778
msd=msd,
@@ -80,5 +81,4 @@ def universe_slice(data: str, slice_start: int, slice_end: int, m: int) -> mda.U
8081
cov=cov,
8182
d=d,
8283
g=g,
83-
f=f,
8484
intercept=intercept)

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