ClustTraj

https://hmcezar.github.io/clusttraj/
Admin
ClustTraj is a Python package for clustering similar configurations and analyzing trajectories from...
Tokens:15,827
Snippets:121
Trust Score:9.7
Update:1 month ago
Show doc for...
Tokens:
Raw
### Manually install QML for troubleshooting

Source: https://hmcezar.github.io/clusttraj/install.html

Workaround for installation failures related to the qml package by installing it separately with specific setuptools versions.

```bash
pip install "setuptools<60"
pip install "qml @ git+https://github.com/hmcezar/qml@develop"
```

--------------------------------

### Install ClustTraj with QML support

Source: https://hmcezar.github.io/clusttraj/install.html

Installs ClustTraj with the optional qmllib dependency.

```bash
pip install "clusttraj[qml]"
```

--------------------------------

### Install ClustTraj with Conda

Source: https://hmcezar.github.io/clusttraj/install.html

Recommended installation sequence when using Conda to manage Open Babel.

```bash
conda install -c conda-forge openbabel
pip install clusttraj
```

--------------------------------

### Install ClustTraj via pip

Source: https://hmcezar.github.io/clusttraj/install.html

Standard installation command for ClustTraj and its core dependencies.

```bash
pip install clusttraj
```

--------------------------------

### Install ClustTraj with Open Babel support

Source: https://hmcezar.github.io/clusttraj/install.html

Installs ClustTraj along with the openbabel-wheel package for pip-only environments.

```bash
pip install "clusttraj[openbabel]"
```

--------------------------------

### Clustering output with reordering

Source: https://hmcezar.github.io/clusttraj/examples.html

Example output showing the impact of atom reordering on clustering statistics.

```text
$ python -m clusttraj h2o_traj.xyz -ss -p -m average -e -f
2024-12-10 20:44:05,214 INFO     [distmat.py:34] <get_distmat> Calculating RMSD matrix using 4 threads

2024-12-10 20:44:07,216 INFO     [distmat.py:38] <get_distmat> Saving condensed RMSD matrix to distmat.npy

2024-12-10 20:44:07,217 INFO     [classify.py:27] <classify_structures_silhouette> Clustering using 'average' method to join the clusters

2024-12-10 20:44:07,229 INFO     [classify.py:61] <classify_structures_silhouette> Highest silhouette score: 0.11873407875769022

2024-12-10 20:44:07,229 INFO     [classify.py:71] <classify_structures_silhouette> Optimal RMSD threshold value: 1.2370133377873964

2024-12-10 20:44:07,229 INFO     [classify.py:76] <classify_structures_silhouette> Saving clustering classification to clusters.dat

2024-12-10 20:44:09,279 INFO     [main.py:102] <main> A total 100 snapshots were read and 35 cluster(s) was(were) found.
The cluster sizes are:
Cluster Size
1       2
2       4
3       3
4       1
5       1
6       1
7       2
8       2
9       3
10      2
11      7
12      3
13      7
14      7
15      3
16      5
17      4
18      3
19      2
20      4
21      2
22      3
23      3
24      1
25      2
26      3
27      2
28      1
29      2
30      2
31      5
32      4
33      2
34      1
35      1

2024-12-10 20:44:09,280 INFO     [main.py:126] <main> Total wall time: 4.066500 s
```

--------------------------------

### Display Help Options

Source: https://hmcezar.github.io/clusttraj/usage.html

View available command-line arguments and options.

```bash
clusttraj -h
```

```bash
python -m clusttraj -h
```

--------------------------------

### View simulation details

Source: https://hmcezar.github.io/clusttraj/examples.html

Display the contents of the clusters.out file to see simulation parameters and cluster sizes.

```bash
$ cat clusters.out

Full command: /Users/rafael/Documents/Física/projetos/clusttraj/clusttraj/__main__.py h2o_traj.xyz -rmsd 2.0

Clusterized from trajectory file: h2o_traj.xyz
Method: average
RMSD criterion: 2.0
Ignoring hydrogens?: False

RMSD matrix was written in: distmat.npy
The classification of each configuration was written in: clusters.dat
A total 100 snapshots were read and 3 cluster(s) was(were) found.
The cluster sizes are:
Cluster Size
1       44
2       22
3       34
```

--------------------------------

### Run clustering with Median method

Source: https://hmcezar.github.io/clusttraj/examples.html

Executes the clustering process using the median method and displays the resulting log output.

```bash
$ python -m clusttraj h2o_traj.xyz -ss -i distmat.npy -p -m median -f
2024-12-10 20:27:55,765 INFO     [distmat.py:28] <get_distmat> Reading condensed RMSD matrix from distmat.npy

2024-12-10 20:27:55,766 INFO     [classify.py:27] <classify_structures_silhouette> Clustering using 'median' method to join the clusters

2024-12-10 20:27:55,775 INFO     [classify.py:61] <classify_structures_silhouette> Highest silhouette score: 0.07527635729544939

2024-12-10 20:27:55,775 INFO     [classify.py:65] <classify_structures_silhouette> The following RMSD threshold values yielded the same optimial silhouette score: 1.8608407527454136, 1.9608407527454137, 2.060840752745414

2024-12-10 20:27:55,775 INFO     [classify.py:68] <classify_structures_silhouette> The smallest RMSD of 1.8608407527454136 has been adopted

2024-12-10 20:27:55,775 INFO     [classify.py:76] <classify_structures_silhouette> Saving clustering classification to clusters.dat

2024-12-10 20:27:58,152 INFO     [main.py:102] <main> A total 100 snapshots were read and 2 cluster(s) was(were) found.
The cluster sizes are:
Cluster Size
1       99
2       1

2024-12-10 20:27:58,153 INFO     [main.py:126] <main> Total wall time: 2.388923 s
```

--------------------------------

### Run Clustering with Final Kabsch Rotation

Source: https://hmcezar.github.io/clusttraj/_sources/examples.rst.txt

Execute the clustering process with the final Kabsch rotation enabled using the specified input file and parameters.

```console
$ clusttraj olig_solv.gro -m average -ss -p --metrics -e -ns 702 -f --final-kabsch
```

--------------------------------

### View Cluster Output Summary

Source: https://hmcezar.github.io/clusttraj/_sources/examples.rst.txt

Display the final cluster sizes and quality metrics from the output file.

```console
$ tail clusters.out
The cluster sizes are:
Cluster	Size
1	30
2	70

Silhouette score: 0.442
Calinski Harabsz score: 256.998
Davies-Bouldin score: 0.482
Cophenetic correlation coefficient: 0.845
```

```console
$ tail clusters.out
The cluster sizes are:
Cluster	Size
1	30
2	70
```

--------------------------------

### Inspect trajectory file

Source: https://hmcezar.github.io/clusttraj/examples.html

View the initial lines of the XYZ trajectory file containing molecular configurations.

```bash
$ head h2o_traj.xyz

15
Frame 1
       O     5.79224   23.34640   11.44660
       H     4.98409   23.01319   11.83659
       H     5.84046   22.91839   10.59179
       O     5.59517   22.31815    8.86907
       H     5.09795   21.51188    8.73143
       H     6.50540   22.06908    8.70880
       O     2.78349   22.26232   10.73374
       H     2.46676   23.16482   10.69619
```

--------------------------------

### Run clustering with solvent reordering

Source: https://hmcezar.github.io/clusttraj/_sources/examples.rst.txt

Includes the -e flag for molecular permutation and -ns to specify the number of oligomer atoms to ignore during reordering.

```console
$ clusttraj olig_solv.gro -m average -ss -p --metrics -e -ns 702 -f
2024-12-12 16:09:08,619 INFO     [distmat.py:34] <get_distmat> Calculating RMSD matrix using 4 threads

2024-12-12 16:12:08,573 INFO     [distmat.py:38] <get_distmat> Saving condensed RMSD matrix to distmat.npy

2024-12-12 16:12:08,576 INFO     [classify.py:27] <classify_structures_silhouette> Clustering using 'average' method to join the clusters

2024-12-12 16:12:08,675 INFO     [classify.py:61] <classify_structures_silhouette> Highest silhouette score: 0.4420374106917728
```

--------------------------------

### View execution log

Source: https://hmcezar.github.io/clusttraj/_sources/examples.rst.txt

Display the log file containing system output and processing times.

```console
$ cat clusttraj.log
2024-12-10 20:03:47,369 INFO     [distmat.py:34] <get_distmat> Calculating RMSD matrix using 4 threads

2024-12-10 20:03:49,416 INFO     [distmat.py:38] <get_distmat> Saving condensed RMSD matrix to distmat.npy

2024-12-10 20:03:49,418 INFO     [classify.py:97] <classify_structures> Clustering using 'average' method to join the clusters

2024-12-10 20:03:49,420 INFO     [classify.py:105] <classify_structures> Saving clustering classification to clusters.dat

2024-12-10 20:03:49,422 INFO     [main.py:102] <main> A total 100 snapshots were read and 3 cluster(s) was(were) found.
The cluster sizes are:
Cluster	Size
1	44
2	22
3	34

2024-12-10 20:03:49,422 INFO     [main.py:126] <main> Total wall time: 2.053868 s
```

--------------------------------

### clusttraj.io.configure_runtime

Source: https://hmcezar.github.io/clusttraj/clusttraj.html

Configures the runtime environment based on provided command-line arguments.

```APIDOC
## clusttraj.io.configure_runtime(args_in)

### Description
Configure the runtime based on command line arguments.

### Parameters
- **args_in** (List[str]) - Required - The command line arguments.

### Returns
- **argparse.Namespace** - The parsed command line arguments.
```

--------------------------------

### Run clustering with Ward method

Source: https://hmcezar.github.io/clusttraj/examples.html

Executes the clustering process using the Ward variance minimization algorithm and forces an output overwrite.

```bash
$ python -m clusttraj h2o_traj.xyz -ss -i distmat.npy -p -m ward -f
```

--------------------------------

### Display cluster output statistics

Source: https://hmcezar.github.io/clusttraj/examples.html

Shows the final cluster sizes and quality metrics by reading the output file.

```bash
$ tail clusters.out
The cluster sizes are:
Cluster Size
1       30
2       70

Silhouette score: 0.442
Calinski Harabsz score: 256.998
Davies-Bouldin score: 0.482
Cophenetic correlation coefficient: 0.845
```

--------------------------------

### Display clustering performance metrics

Source: https://hmcezar.github.io/clusttraj/examples.html

Displays the final cluster sizes and quantitative performance scores from the output file.

```bash
$ tail clusters.out
The cluster sizes are:
Cluster Size
1       99
2       1

Silhouette score: 0.139
Calinski Harabsz score: 2.476
Davies-Bouldin score: 0.619
Cophenetic correlation coefficient: 0.908
```

--------------------------------

### Display clustering results

Source: https://hmcezar.github.io/clusttraj/examples.html

Shows the contents of the clusters.out file, providing a summary of cluster sizes and quality metrics.

```bash
$ tail clusters.out
The cluster sizes are:
Cluster Size
1       30
2       70

Silhouette score: 0.451
Calinski Harabsz score: 268.899
Davies-Bouldin score: 0.463
Cophenetic correlation coefficient: 0.845
```

--------------------------------

### clusttraj.main.main

Source: https://hmcezar.github.io/clusttraj/clusttraj.html

The main entry point for the clusttraj library, used to perform clustering and generate output.

```APIDOC
## clusttraj.main.main(args: List[str] | None = None) -> None

### Description
Performs clustering and generates output based on the provided arguments.

### Parameters
- **args** (List[str]) - Optional - List of command-line arguments.
```

--------------------------------

### Display clustering metrics

Source: https://hmcezar.github.io/clusttraj/_sources/examples.rst.txt

Shows the output metrics for the clustering performance.

```console
$ tail clusters.out
The cluster sizes are:
Cluster	Size
1	99
2	1

Silhouette score: 0.139
Calinski Harabsz score: 2.476
Davies-Bouldin score: 0.619
Cophenetic correlation coefficient: 0.908
```

--------------------------------

### Run ClustTraj with Median linkage

Source: https://hmcezar.github.io/clusttraj/_sources/examples.rst.txt

Executes the clustering process using the median linkage method and displays the resulting log output.

```console
$ python -m clusttraj h2o_traj.xyz -ss -i distmat.npy -p -m median -f 
2024-12-10 20:27:55,765 INFO     [distmat.py:28] <get_distmat> Reading condensed RMSD matrix from distmat.npy

2024-12-10 20:27:55,766 INFO     [classify.py:27] <classify_structures_silhouette> Clustering using 'median' method to join the clusters

2024-12-10 20:27:55,775 INFO     [classify.py:61] <classify_structures_silhouette> Highest silhouette score: 0.07527635729544939

2024-12-10 20:27:55,775 INFO     [classify.py:65] <classify_structures_silhouette> The following RMSD threshold values yielded the same optimial silhouette score: 1.8608407527454136, 1.9608407527454137, 2.060840752745414

2024-12-10 20:27:55,775 INFO     [classify.py:68] <classify_structures_silhouette> The smallest RMSD of 1.8608407527454136 has been adopted

2024-12-10 20:27:55,775 INFO     [classify.py:76] <classify_structures_silhouette> Saving clustering classification to clusters.dat
```

--------------------------------

### Run clusttraj with solvent reordering

Source: https://hmcezar.github.io/clusttraj/examples.html

Executes the clustering process with the -e flag for molecular permutation and -ns to specify the number of oligomer atoms to ignore.

```bash
$ clusttraj olig_solv.gro -m average -ss -p --metrics -e -ns 702 -f
2024-12-12 16:09:08,619 INFO     [distmat.py:34] <get_distmat> Calculating RMSD matrix using 4 threads

2024-12-12 16:12:08,573 INFO     [distmat.py:38] <get_distmat> Saving condensed RMSD matrix to distmat.npy

2024-12-12 16:12:08,576 INFO     [classify.py:27] <classify_structures_silhouette> Clustering using 'average' method to join the clusters

2024-12-12 16:12:08,675 INFO     [classify.py:61] <classify_structures_silhouette> Highest silhouette score: 0.4420374106917728

2024-12-12 16:12:08,676 INFO     [classify.py:65] <classify_structures_silhouette> The following RMSD threshold values yielded the same optimial silhouette score: 11.532116467337541, 11.632116467337543, 11.73211646733754, 11.832116467337542, 11.93211646733754, 12.032116467337541, 12.13211646733754, 12.23211646733754, 12.332116467337539, 12.43211646733754, 12.532116467337538, 12.63211646733754, 12.732116467337537, 12.832116467337539, 12.932116467337536, 13.032116467337538, 13.132116467337536, 13.232116467337537, 13.332116467337535, 13.432116467337536, 13.532116467337534, 13.632116467337536, 13.732116467337534, 13.832116467337535, 13.932116467337533, 14.032116467337534, 14.132116467337532, 14.232116467337534, 14.332116467337531, 14.432116467337533, 14.53211646733753, 14.632116467337532, 14.73211646733753, 14.832116467337531, 14.93211646733753, 15.03211646733753, 15.132116467337529, 15.23211646733753, 15.332116467337528, 15.43211646733753, 15.532116467337527, 15.632116467337529, 15.732116467337526, 15.832116467337528, 15.932116467337526, 16.032116467337527, 16.132116467337525, 16.232116467337526, 16.332116467337524, 16.432116467337526, 16.532116467337524

2024-12-12 16:12:08,676 INFO     [classify.py:68] <classify_structures_silhouette> The smallest RMSD of 11.532116467337541 has been adopted

2024-12-12 16:12:08,676 INFO     [classify.py:76] <classify_structures_silhouette> Saving clustering classification to clusters.dat

2024-12-12 16:12:11,256 INFO     [main.py:102] <main> A total 100 snapshots were read and 2 cluster(s) was(were) found.
The cluster sizes are:
Cluster Size
1       30
2       70

2024-12-12 16:12:11,262 INFO     [main.py:126] <main> Total wall time: 182.642790 s
```

--------------------------------

### Run standard hierarchical clustering

Source: https://hmcezar.github.io/clusttraj/examples.html

Executes the clustering process on a trajectory file using the average linkage method and calculates performance metrics.

```bash
$ clusttraj olig_solv.gro -m average -ss -p --metrics
2024-12-12 16:13:01,490 INFO     [distmat.py:34] <get_distmat> Calculating RMSD matrix using 4 threads

2024-12-12 16:13:43,838 INFO     [distmat.py:38] <get_distmat> Saving condensed RMSD matrix to distmat.npy

2024-12-12 16:13:43,840 INFO     [classify.py:27] <classify_structures_silhouette> Clustering using 'average' method to join the clusters

2024-12-12 16:13:43,923 INFO     [classify.py:61] <classify_structures_silhouette> Highest silhouette score: 0.13900364227503081

2024-12-12 16:13:43,923 INFO     [classify.py:65] <classify_structures_silhouette> The following RMSD threshold values yielded the same optimial silhouette score: 25.157769211396136, 25.257769211396134

2024-12-12 16:13:43,923 INFO     [classify.py:68] <classify_structures_silhouette> The smallest RMSD of 25.157769211396136 has been adopted

2024-12-12 16:13:43,924 INFO     [classify.py:76] <classify_structures_silhouette> Saving clustering classification to clusters.dat

2024-12-12 16:13:46,184 INFO     [main.py:102] <main> A total 100 snapshots were read and 2 cluster(s) was(were) found.
The cluster sizes are:
Cluster Size
1       99
2       1

2024-12-12 16:13:46,189 INFO     [main.py:126] <main> Total wall time: 44.698860 s
```

--------------------------------

### Run ClustTraj with Ward linkage

Source: https://hmcezar.github.io/clusttraj/_sources/examples.rst.txt

Executes the clustering process using the Ward variance minimization algorithm and displays the corresponding log output.

```console
$ python -m clusttraj h2o_traj.xyz -ss -i distmat.npy -p -m ward -f
```

```console
$ tail -n 22 clusttraj.log
2024-12-10 20:23:31,014 INFO     [main.py:126] <main> Total wall time: 2.051024 s

2024-12-10 20:24:58,651 INFO     [distmat.py:28] <get_distmat> Reading condensed RMSD matrix from distmat.npy

2024-12-10 20:24:58,652 INFO     [classify.py:27] <classify_structures_silhouette> Clustering using 'ward' method to join the clusters

2024-12-10 20:24:58,712 INFO     [classify.py:61] <classify_structures_silhouette> Highest silhouette score: 0.23037242401157287

2024-12-10 20:24:58,712 INFO     [classify.py:65] <classify_structures_silhouette> The following RMSD threshold values yielded the same optimial silhouette score: 6.0608407527454125, 6.160840752745413, 6.260840752745413, 6.360840752745412, 6.460840752745413, 6.5608407527454125, 6.660840752745413, 6.760840752745413, 6.860840752745412, 6.960840752745413, 7.0608407527454125, 7.160840752745413, 7.260840752745413, 7.360840752745412, 7.460840752745413, 7.5608407527454125, 7.660840752745412, 7.760840752745413, 7.860840752745412, 7.960840752745412, 8.060840752745412, 8.160840752745413, 8.260840752745413, 8.360840752745412, 8.460840752745412, 8.560840752745412, 8.660840752745413, 8.760840752745413, 8.860840752745412, 8.960840752745412, 9.060840752745412, 9.160840752745411, 9.260840752745413, 9.360840752745412, 9.460840752745412, 9.560840752745412, 9.660840752745411, 9.760840752745413, 9.860840752745412, 9.960840752745412, 10.060840752745412, 10.160840752745411, 10.260840752745413, 10.360840752745412, 10.460840752745412, 10.560840752745412, 10.660840752745411, 10.760840752745413

2024-12-10 20:24:58,712 INFO     [classify.py:68] <classify_structures_silhouette> The smallest RMSD of 6.0608407527454125 has been adopted

2024-12-10 20:24:58,712 INFO     [classify.py:76] <classify_structures_silhouette> Saving clustering classification to clusters.dat

2024-12-10 20:25:00,661 INFO     [main.py:102] <main> A total 100 snapshots were read and 2 cluster(s) was(were) found.
The cluster sizes are:
Cluster	Size
1	46
2	54

2024-12-10 20:25:00,661 INFO     [main.py:126] <main> Total wall time: 2.011472 s
```

--------------------------------

### Inspect cluster labels

Source: https://hmcezar.github.io/clusttraj/examples.html

View the generated cluster labels for each configuration in the trajectory.

```bash
$ head clusters.dat
3
3
1
2
1
1
2
1
1
3
```

--------------------------------

### Run Clusttraj with automatic threshold detection

Source: https://hmcezar.github.io/clusttraj/examples.html

Executes the clustering process using the -ss flag to maximize the silhouette coefficient, with -i for input matrix and -p for visualization outputs.

```bash
$ python -m clusttraj h2o_traj.xyz -ss -i distmat.npy -p
```

--------------------------------

### Clustering with solute-solvent separation

Source: https://hmcezar.github.io/clusttraj/examples.html

Use the -ns flag to specify the number of solvent atoms for improved clustering in solvated systems.

```bash
$ python -m clusttraj h2o_traj.xyz -ss -p -m average -e -f -ns 3
2024-12-10 20:46:41,192 INFO     [distmat.py:34] <get_distmat> Calculating RMSD matrix using 4 threads

2024-12-10 20:46:43,383 INFO     [distmat.py:38] <get_distmat> Saving condensed RMSD matrix to distmat.npy

2024-12-10 20:46:43,385 INFO     [classify.py:27] <classify_structures_silhouette> Clustering using 'average' method to join the clusters

2024-12-10 20:46:43,407 INFO     [classify.py:61] <classify_structures_silhouette> Highest silhouette score: 0.24735123044958363

2024-12-10 20:46:43,407 INFO     [classify.py:65] <classify_structures_silhouette> The following RMSD threshold values yielded the same optimial silhouette score: 3.035586843407412, 3.135586843407412, 3.235586843407412, 3.335586843407412

2024-12-10 20:46:43,407 INFO     [classify.py:68] <classify_structures_silhouette> The smallest RMSD of 3.035586843407412 has been adopted

2024-12-10 20:46:43,407 INFO     [classify.py:76] <classify_structures_silhouette> Saving clustering classification to clusters.dat

2024-12-10 20:46:45,206 INFO     [main.py:102] <main> A total 100 snapshots were read and 2 cluster(s) was(were) found.
The cluster sizes are:
Cluster Size
1       3
2       97

2024-12-10 20:46:45,206 INFO     [main.py:126] <main> Total wall time: 4.015671 s
```

--------------------------------

### Apply final Kabsch rotation

Source: https://hmcezar.github.io/clusttraj/examples.html

Use the --final-kabsch flag to minimize RMSD after reordering solvent atoms.

```bash
$ python -m clusttraj h2o_traj.xyz -ss -p -m average -e -f -ns 3 --final-kabsch
```

--------------------------------

### View execution logs

Source: https://hmcezar.github.io/clusttraj/examples.html

Display the contents of the clusttraj.log file for detailed execution information and timing.

```bash
$ cat clusttraj.log
2024-12-10 20:03:47,369 INFO     [distmat.py:34] <get_distmat> Calculating RMSD matrix using 4 threads

2024-12-10 20:03:49,416 INFO     [distmat.py:38] <get_distmat> Saving condensed RMSD matrix to distmat.npy

2024-12-10 20:03:49,418 INFO     [classify.py:97] <classify_structures> Clustering using 'average' method to join the clusters

2024-12-10 20:03:49,420 INFO     [classify.py:105] <classify_structures> Saving clustering classification to clusters.dat

2024-12-10 20:03:49,422 INFO     [main.py:102] <main> A total 100 snapshots were read and 3 cluster(s) was(were) found.
The cluster sizes are:
Cluster Size
1       44
2       22
3       34

2024-12-10 20:03:49,422 INFO     [main.py:126] <main> Total wall time: 2.053868 s
```

--------------------------------

### View silhouette clustering log

Source: https://hmcezar.github.io/clusttraj/_sources/examples.rst.txt

Display the log file showing the highest silhouette score and optimal RMSD threshold values.

```console
$ cat clusttraj.log
2024-12-10 20:06:50,323 INFO     [distmat.py:28] <get_distmat> Reading condensed RMSD matrix from distmat.npy

2024-12-10 20:06:50,324 INFO     [classify.py:27] <classify_structures_silhouette> Clustering using 'average' method to join the clusters

2024-12-10 20:06:50,338 INFO     [classify.py:61] <classify_structures_silhouette> Highest silhouette score: 0.21741836027295453

2024-12-10 20:06:50,338 INFO     [classify.py:65] <classify_structures_silhouette> The following RMSD threshold values yielded the same optimial silhouette score: 2.160840752745414, 2.2608407527454135
```

--------------------------------

### Cluster solvated systems

Source: https://hmcezar.github.io/clusttraj/_sources/examples.rst.txt

Specify the number of solvent atoms using the -ns flag to treat specific molecules as solute and others as solvent.

```console
$ python -m clusttraj h2o_traj.xyz -ss -p -m average -e -f -ns 3
2024-12-10 20:46:41,192 INFO     [distmat.py:34] <get_distmat> Calculating RMSD matrix using 4 threads

2024-12-10 20:46:43,383 INFO     [distmat.py:38] <get_distmat> Saving condensed RMSD matrix to distmat.npy

2024-12-10 20:46:43,385 INFO     [classify.py:27] <classify_structures_silhouette> Clustering using 'average' method to join the clusters

2024-12-10 20:46:43,407 INFO     [classify.py:61] <classify_structures_silhouette> Highest silhouette score: 0.24735123044958363

2024-12-10 20:46:43,407 INFO     [classify.py:65] <classify_structures_silhouette> The following RMSD threshold values yielded the same optimial silhouette score: 3.035586843407412, 3.135586843407412, 3.235586843407412, 3.335586843407412

2024-12-10 20:46:43,407 INFO     [classify.py:68] <classify_structures_silhouette> The smallest RMSD of 3.035586843407412 has been adopted

2024-12-10 20:46:43,407 INFO     [classify.py:76] <classify_structures_silhouette> Saving clustering classification to clusters.dat

2024-12-10 20:46:45,206 INFO     [main.py:102] <main> A total 100 snapshots were read and 2 cluster(s) was(were) found.
The cluster sizes are:
Cluster	Size
1	3
2	97

2024-12-10 20:46:45,206 INFO     [main.py:126] <main> Total wall time: 4.015671 s
```

--------------------------------

### Run standard RMSD clustering

Source: https://hmcezar.github.io/clusttraj/_sources/examples.rst.txt

Executes the hierarchical clustering scheme without accounting for solvent permutation.

```console
$ clusttraj olig_solv.gro -m average -ss -p --metrics
2024-12-12 16:13:01,490 INFO     [distmat.py:34] <get_distmat> Calculating RMSD matrix using 4 threads

2024-12-12 16:13:43,838 INFO     [distmat.py:38] <get_distmat> Saving condensed RMSD matrix to distmat.npy

2024-12-12 16:13:43,840 INFO     [classify.py:27] <classify_structures_silhouette> Clustering using 'average' method to join the clusters

2024-12-12 16:13:43,923 INFO     [classify.py:61] <classify_structures_silhouette> Highest silhouette score: 0.13900364227503081

2024-12-12 16:13:43,923 INFO     [classify.py:65] <classify_structures_silhouette> The following RMSD threshold values yielded the same optimial silhouette score: 25.157769211396136, 25.257769211396134

2024-12-12 16:13:43,923 INFO     [classify.py:68] <classify_structures_silhouette> The smallest RMSD of 25.157769211396136 has been adopted

2024-12-12 16:13:43,924 INFO     [classify.py:76] <classify_structures_silhouette> Saving clustering classification to clusters.dat

2024-12-12 16:13:46,184 INFO     [main.py:102] <main> A total 100 snapshots were read and 2 cluster(s) was(were) found.
The cluster sizes are:
Cluster	Size
1	99
2	1

2024-12-12 16:13:46,189 INFO     [main.py:126] <main> Total wall time: 44.698860 s
```

--------------------------------

### Run clusttraj with final Kabsch rotation

Source: https://hmcezar.github.io/clusttraj/examples.html

Executes the clusttraj command with specific flags for solvent reordering and Kabsch rotation, including the resulting log output.

```bash
$ clusttraj olig_solv.gro -m average -ss -p --metrics -e -ns 702 -f --final-kabsch
2024-12-12 16:35:25,405 INFO     [distmat.py:34] <get_distmat> Calculating RMSD matrix using 4 threads

2024-12-12 16:38:24,715 INFO     [distmat.py:38] <get_distmat> Saving condensed RMSD matrix to distmat.npy

2024-12-12 16:38:24,718 INFO     [classify.py:27] <classify_structures_silhouette> Clustering using 'average' method to join the clusters

2024-12-12 16:38:24,798 INFO     [classify.py:61] <classify_structures_silhouette> Highest silhouette score: 0.4505111680708198

2024-12-12 16:38:24,798 INFO     [classify.py:65] <classify_structures_silhouette> The following RMSD threshold values yielded the same optimial silhouette score: 11.504201293638701, 11.6042012936387, 11.7042012936387, 11.8042012936387, 11.9042012936387, 12.0042012936387, 12.104201293638699, 12.204201293638699, 12.304201293638698, 12.404201293638698, 12.504201293638697, 12.604201293638697, 12.704201293638697, 12.804201293638696, 12.904201293638696, 13.004201293638696, 13.104201293638695, 13.204201293638695, 13.304201293638695, 13.404201293638694, 13.504201293638694, 13.604201293638694, 13.704201293638693, 13.804201293638693, 13.904201293638693, 14.004201293638692, 14.104201293638692, 14.204201293638691, 14.304201293638691, 14.40420129363869, 14.50420129363869, 14.60420129363869, 14.70420129363869, 14.80420129363869, 14.904201293638689, 15.004201293638689, 15.104201293638688, 15.204201293638688, 15.304201293638688, 15.404201293638687, 15.504201293638687, 15.604201293638686, 15.704201293638686, 15.804201293638686, 15.904201293638685, 16.004201293638687, 16.104201293638685, 16.204201293638683, 16.304201293638684, 16.404201293638685, 16.504201293638683

2024-12-12 16:38:24,798 INFO     [classify.py:68] <classify_structures_silhouette> The smallest RMSD of 11.504201293638701 has been adopted

2024-12-12 16:38:24,798 INFO     [classify.py:76] <classify_structures_silhouette> Saving clustering classification to clusters.dat

2024-12-12 16:38:26,979 INFO     [main.py:102] <main> A total 100 snapshots were read and 2 cluster(s) was(were) found.
The cluster sizes are:
Cluster Size
1       30
2       70

2024-12-12 16:38:26,981 INFO     [main.py:126] <main> Total wall time: 181.576293 s
```

--------------------------------

### Run clustering with manual RMSD threshold

Source: https://hmcezar.github.io/clusttraj/examples.html

Execute the clustering procedure by specifying the trajectory file and a fixed RMSD cutoff distance.

```bash
$ python -m clusttraj h2o_traj.xyz -rmsd 2.0
```

--------------------------------

### Cluster by Silhouette Coefficient

Source: https://hmcezar.github.io/clusttraj/usage.html

Determine the RMSD threshold automatically by maximizing the silhouette coefficient.

```bash
clusttraj trajectory.xyz -ss
```

--------------------------------

### Reorder atoms with molecule permutation flag

Source: https://hmcezar.github.io/clusttraj/examples.html

Use the -e flag to reorder atoms to account for identical molecule permutations.

```bash
$ python -m clusttraj h2o_traj.xyz -ss -p -m average -e -f
```

--------------------------------

### Perform Trajectory Clustering

Source: https://hmcezar.github.io/clusttraj/usage.html

Basic command to cluster a trajectory file using an RMSD threshold.

```bash
clusttraj trajectory.xyz -rmsd <threshold>
```

--------------------------------

### clusttraj.io.save_medoids_config

Source: https://hmcezar.github.io/clusttraj/clusttraj.html

Saves the best superpositioned medoids configurations to a single file.

```APIDOC
## clusttraj.io.save_medoids_config(trajfile, medoids, noh, reorder, reorder_solvent_only, nsatoms, weight_solute, outbasename, outfmt, reorderexcl, final_kabsch, overwrite)

### Description
Save best superpositioned medoids configurations to a single file. First medoid is the reference.

### Parameters
- **trajfile** (str) - Required - The trajectory file path.
- **medoids** (ndarray) - Required - An array containing medoid indices.
- **noh** (bool) - Required - Flag indicating whether to exclude hydrogen atoms.
- **reorder** (Callable) - Optional - A function to reorder the atoms, if necessary.
- **nsatoms** (int) - Required - The number of atoms in the solute.
- **weight_solute** (float) - Required - The weight of the solute atoms in the RMSD calculation.
- **outbasename** (str) - Required - The base name for the output file.
- **outfmt** (str) - Required - The output file format.
- **reorderexcl** (ndarray) - Required - An array of atom indices to exclude during reordering.
- **final_kabsch** (bool) - Required - Flag indicating whether to perform a final Kabsch rotation.
- **overwrite** (bool) - Required - Flag indicating whether to overwrite existing output files.
```

--------------------------------

### View clustering log output

Source: https://hmcezar.github.io/clusttraj/examples.html

Displays the final lines of the clusttraj log file to verify the clustering results.

```bash
$ tail -n 22 clusttraj.log
2024-12-10 20:23:31,014 INFO     [main.py:126] <main> Total wall time: 2.051024 s

2024-12-10 20:24:58,651 INFO     [distmat.py:28] <get_distmat> Reading condensed RMSD matrix from distmat.npy

2024-12-10 20:24:58,652 INFO     [classify.py:27] <classify_structures_silhouette> Clustering using 'ward' method to join the clusters

2024-12-10 20:24:58,712 INFO     [classify.py:61] <classify_structures_silhouette> Highest silhouette score: 0.23037242401157287

2024-12-10 20:24:58,712 INFO     [classify.py:65] <classify_structures_silhouette> The following RMSD threshold values yielded the same optimial silhouette score: 6.0608407527454125, 6.160840752745413, 6.260840752745413, 6.360840752745412, 6.460840752745413, 6.5608407527454125, 6.660840752745413, 6.760840752745413, 6.860840752745412, 6.960840752745413, 7.0608407527454125, 7.160840752745413, 7.260840752745413, 7.360840752745412, 7.460840752745413, 7.5608407527454125, 7.660840752745412, 7.760840752745413, 7.860840752745412, 7.960840752745412, 8.060840752745412, 8.160840752745413, 8.260840752745413, 8.360840752745412, 8.460840752745412, 8.560840752745412, 8.660840752745413, 8.760840752745413, 8.860840752745412, 8.960840752745412, 9.060840752745412, 9.160840752745411, 9.260840752745413, 9.360840752745412, 9.460840752745412, 9.560840752745412, 9.660840752745411, 9.760840752745413, 9.860840752745412, 9.960840752745412, 10.060840752745412, 10.160840752745411, 10.260840752745413, 10.360840752745412, 10.460840752745412, 10.560840752745412, 10.660840752745411, 10.760840752745413

2024-12-10 20:24:58,712 INFO     [classify.py:68] <classify_structures_silhouette> The smallest RMSD of 6.0608407527454125 has been adopted

2024-12-10 20:24:58,712 INFO     [classify.py:76] <classify_structures_silhouette> Saving clustering classification to clusters.dat

2024-12-10 20:25:00,661 INFO     [main.py:102] <main> A total 100 snapshots were read and 2 cluster(s) was(were) found.
The cluster sizes are:
Cluster Size
1       46
2       54

2024-12-10 20:25:00,661 INFO     [main.py:126] <main> Total wall time: 2.011472 s
```

--------------------------------

### Configure NumPy Threading

Source: https://hmcezar.github.io/clusttraj/usage.html

Set environment variables to restrict NumPy threading when using multiprocessing.

```bash
export OMP_NUM_THREADS=1
export OPENBLAS_NUM_THREADS=1
export MKL_NUM_THREADS=1
export VECLIB_MAXIMUM_THREADS=1
export NUMEXPR_NUM_THREADS=1
```
Tokens:
Raw