### Install ASE with Docs Dependencies

Source: https://gitlab.com/ase/ase/-/blob/master/doc/development/addingexamples.rst

Install the 'docs' dependency group for ASE, which includes necessary packages for documentation and example building.

```console
$ pip install ase[docs]
```

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

### Install Sphinx and Dependencies

Source: https://gitlab.com/ase/ase/-/blob/master/doc/development/writing_documentation_ase.rst

Installs Sphinx and the book theme using pip. Ensure ~/.local/bin is in your PATH.

```console
$ pip install sphinx_book_theme --user
```

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

### Setting VASP Pseudopotential Setups

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/vasp.rst

Configure the pseudopotential setup for VASP calculations. Use 'recommended' for standard setups or a dictionary to specify custom setups for elements or positions.

```python
from ase.calculators.vasp import Vasp
calc = Vasp(setups='recommended')
```

```python
calc = Vasp(xc='PBE', setups={'Li': '_sv'})
```

```python
calc = Vasp(xc='PBE', setups={3: 'Ga_d'})
```

```python
calc = Vasp(xc='PBE', setups={'base': 'recommended', 'Li': '', 4: 'H.5'})
```

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

### Install Ruff Linter

Source: https://gitlab.com/ase/ase/-/blob/master/doc/development/addingexamples.rst

Install the Ruff linter, used for checking code quality in ASE examples.

```console
$ pip install ruff
```

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

### User-level installation with pip

Source: https://gitlab.com/ase/ase/-/blob/master/doc/install.rst

When system-wide installation is not possible or desired, use the --user flag to install ASE into a local user directory. Ensure this directory is in your PATH.

```bash
pip install --upgrade --user ase
```

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

### Gaussian Calculator Setup

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/gaussian.rst

Instantiate the Gaussian calculator with various parameters. Ensure necessary imports are present.

```python
from ase.calculators.gaussian import Gaussian
atoms = ...
calc = Gaussian(basis='sto-3g', charge=0, mult=1, 
                basisfile='mybasis.gbs', basis_set='mybasis.gbs', 
                extra='Extra line', addsec='\nOpt\n', 
                ioplist=[1, 2], spinlist=[1, 2], 
                zefflist=[1, 2], qmomlist=[1, 2], 
                nmagmlist=[1, 2], znuclist=[1, 2], 
                radnuclearlist=[1, 2])
```

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

### Example Configuration File

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/calculators.rst

This is an example of the `config.ini` file used by ASE to configure external codes. It specifies the command to run and pseudopotential paths for different calculators.

```ini
[abinit]
command = mpiexec /usr/bin/abinit
pp_paths = /usr/share/abinit/pseudopotentials

[espresso]
command = mpiexec pw.x
pseudo_path = /home/ase/upf_pseudos
```

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

### Abinit Example

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/socketio/socketio.rst

Example of using SocketIOCalculator with Abinit. It is recommended to use the 'with' statement for proper connection management.

```APIDOC
## Abinit Example

### Description
This example demonstrates how to use the `SocketIOCalculator` with Abinit. It is best practice to use the `with` statement to ensure the socket connection is closed properly.

### Method
```python
from ase.calculators.socketio import SocketIOCalculator
from ase.io import read

# 'atoms' is an ASE Atoms object, and 'calc_params' contains Abinit settings.
# with SocketIOCalculator(atoms, **calc_params) as calc:
#     energy = calc.get_potential_energy()
#     forces = calc.get_forces()
```

### Endpoint
N/A (SDK usage example)

### Parameters
- `atoms` (ase.Atoms): The atomic structure.
- `**calc_params`: Additional parameters for the Abinit calculator.

### Request Example
```python
# Conceptual example; actual parameters depend on Abinit configuration.
# calc_params = {
#     'command': 'abinit',
#     'input_params': {
#         'xc': 'LDA',
#         'ecut': 100.0
#     }
# }
# atoms = read('abinit_structure.xyz')
# with SocketIOCalculator(atoms, **calc_params) as calc:
#     energy = calc.get_potential_energy()
```

### Response
#### Success Response
- `energy` (float): The calculated potential energy.
- `forces` (numpy.ndarray): Forces on each atom.

#### Response Example
```json
{
  "energy": -30.5,
  "forces": [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]]
}
```
```

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

### Install ASE test dependencies

Source: https://gitlab.com/ase/ase/-/blob/master/doc/development/tests.rst

Install pytest, pytest-mock, and pytest-xdist to run ASE tests. This command installs the necessary testing tools.

```bash
pip install ase[test]
```

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

### Browse Built Gallery

Source: https://gitlab.com/ase/ase/-/blob/master/doc/development/addingexamples.rst

Open the locally built example gallery in a web browser after running 'make html'.

```console
$ make browse
```

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

### Quantum Espresso Example

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/socketio/socketio.rst

Example of using the SocketIOCalculator with Quantum Espresso. It is recommended to use the 'with' statement for smooth termination of the connection.

```APIDOC
## Quantum Espresso Example

### Description
This example demonstrates how to use the `SocketIOCalculator` with Quantum Espresso. It is crucial to ensure smooth termination of the connection, preferably by using the `with` statement.

### Method
```python
from ase.calculators.socketio import SocketIOCalculator
from ase.io import read

# Assuming 'calc_params' contains necessary parameters for Quantum Espresso
# and 'atoms' is an ASE Atoms object.
# calc = SocketIOCalculator(atoms, **calc_params)

# Example usage within a 'with' statement for proper resource management:
# with SocketIOCalculator(atoms, **calc_params) as calc:
#     energy = calc.get_potential_energy()
#     forces = calc.get_forces()
```

### Endpoint
N/A (This is an SDK usage example, not an HTTP endpoint)

### Parameters
- `atoms` (ase.Atoms): The atomic structure to be used.
- `**calc_params`: Arbitrary keyword arguments passed to the underlying calculator.

### Request Example
```python
# This is a conceptual example. Actual parameters depend on Quantum Espresso setup.
# from ase.calculators.espresso import Espresso
# calc_params = {
#     'input_params': {
#         'calculation': 'scf',
#         'pseudo_dir': '/path/to/pseudos',
#         'outdir': '/path/to/output'
#     },
#     'pseudos': {'O': 'O.pbe-dn-rrkjus_PBE.UPF'}
# }
# atoms = read('structure.xyz')
# with SocketIOCalculator(atoms, **calc_params) as calc:
#     energy = calc.get_potential_energy()
```

### Response
#### Success Response
- `energy` (float): The calculated potential energy.
- `forces` (numpy.ndarray): The calculated forces on each atom.

#### Response Example
```json
{
  "energy": -100.5,
  "forces": [[0.1, 0.2, 0.3], [-0.1, -0.2, -0.3]]
}
```
```

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

### Build HTML Documentation

Source: https://gitlab.com/ase/ase/-/blob/master/doc/development/addingexamples.rst

Build the HTML version of the documentation, including rendering the examples, from the 'doc' directory.

```console
$ make html
```

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

### Install and Secure MySQL Server

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/db/db.rst

Commands to install the MySQL server and run the security script on Ubuntu systems.

```bash
$ sudo apt-get install mysql-server
$ sudo mysql_secure_installation
```

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

### Quantum Espresso Socket I/O Example

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/socketio/socketio.rst

Example of using the SocketIOCalculator with Quantum Espresso. Ensure smooth termination by using the 'with' statement.

```python
from ase.calculators.espresso import Espresso
from ase.optimize import BFGS
from ase.build import fcc111

# Make a small slab
slab = fcc111('Cu', size=(2, 2, 4), vacuum=10.0)

# Use SocketIOCalculator with Espresso
calc = Espresso(
    pseudopotentials='Cu.pbe-sp-van_bm',
    tstress=True,
    tprnfor=True,
    # Use socket I/O
    socket=True,
    # Specify port if needed
    # socket_port=5000,
    # Specify host if needed
    # socket_host='localhost',
)
s রাসায়নিক_formula = slab.get_chemical_formula()
slab.calc = calc

# Optimize geometry
opt = BFGS(slab)
opt.run(fmax=0.05)

# Close the calculator connection
calc.close()

```

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

### DMol3 Calculator Example

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/dmol.rst

An example demonstrating how to set up and use the DMol3 calculator with an Atoms object.

```APIDOC
## Example

.. code-block:: python

   from ase.build import molecule
   from ase.calculators.dmol import DMol3

   atoms = molecule('H2O')
   calc = DMol3(symmetry='auto',
                spin_polarization='unrestricted',
                charge=0,
                basis='dnp',
                pseudopotential='none',
                functional='pbe',
                scf_density_convergence=1.0e-7)
   atoms.calc = calc
   atoms.get_potential_energy()
```

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

### Install scriv

Source: https://gitlab.com/ase/ase/-/blob/master/doc/development/writing_changelog.rst

Install the scriv tool using pip. This is a prerequisite for managing changelog entries.

```console
$ pip install scriv
```

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

### Install ASE with test dependencies

Source: https://gitlab.com/ase/ase/-/blob/master/doc/install.rst

If you plan to run the tests, install ASE with the test extra, which includes necessary testing dependencies.

```bash
pip install --upgrade ase[test]
```

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

### Abinit Socket I/O Example

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/socketio/socketio.rst

Example for using SocketIOCalculator with Abinit. Ensure proper connection closure by using the 'with' statement.

```python
from ase.calculators.abinit import Abinit
from ase.optimize import BFGS
from ase.build import molecule

# Make a molecule
molecule = molecule('H2')

# Use SocketIOCalculator with Abinit
calc = Abinit(
    # Use socket I/O
    socket=True,
    # Specify port if needed
    # socket_port=5000,
    # Specify host if needed
    # socket_host='localhost',
)
molecule.calc = calc

# Optimize geometry
opt = BFGS(molecule)
opt.run(fmax=0.05)

# Close the calculator connection
calc.close()

```

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

### GULP Single-Point and Optimization Example

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/gulp.rst

Example demonstrating a single-point calculation followed by an optimization using GULP's internal optimizer via ASE. Requires the 'opti' keyword to be set for the GULP calculator.

```python
from ase.calculators.gulp import GULP
from ase.optimize import Optimizer
from ase.build import fcc111

atoms = fcc111('Cu', size=(2,2,1), vacuum=10.0)

calc = GULP(keywords='opti', 
            options=['xtol 1e-5'],
            library='ff sioh.lib')

atoms.calc = calc

# Single point calculation
energy = atoms.get_potential_energy()

# Optimization
optimizer = Optimizer(atoms)
optimizer.run(fmax=0.01)

print(f'Final energy: {atoms.get_potential_energy()}')
```

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

### Siesta Example

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/socketio/socketio.rst

Example demonstrating the use of SocketIOCalculator with Siesta. The 'with' statement is recommended for managing the connection.

```APIDOC
## Siesta Example

### Description
This example illustrates how to use the `SocketIOCalculator` with the Siesta code. Employing the `with` statement is advised for robust connection handling.

### Method
```python
from ase.calculators.socketio import SocketIOCalculator
from ase.io import read

# 'atoms' should be an ASE Atoms object, and 'calc_params' should contain Siesta settings.
# with SocketIOCalculator(atoms, **calc_params) as calc:
#     energy = calc.get_potential_energy()
#     forces = calc.get_forces()
```

### Endpoint
N/A (SDK usage example)

### Parameters
- `atoms` (ase.Atoms): The atomic structure.
- `**calc_params`: Additional parameters for the Siesta calculator.

### Request Example
```python
# Conceptual example; actual parameters depend on Siesta configuration.
# calc_params = {
#     'command': 'siesta',
#     'input_params': {
#         'mesh-cutoff': '200 Ry',
#         'basis': 'DZP'
#     }
# }
# atoms = read('siesta_structure.xyz')
# with SocketIOCalculator(atoms, **calc_params) as calc:
#     energy = calc.get_potential_energy()
```

### Response
#### Success Response
- `energy` (float): The calculated potential energy.
- `forces` (numpy.ndarray): Forces on each atom.

#### Response Example
```json
{
  "energy": -75.8,
  "forces": [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]]
}
```
```

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

### Socket Server Example

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/socketio/socketio.rst

Example of launching a socket server without necessarily launching a client. This server can then be controlled by an external client.

```APIDOC
## Socket Server Example

### Description
This example demonstrates how to launch a socket server using `ase.calculators.socketio.SocketServer`. This server can then be connected to by a separate client application.

### Method
```python
from ase.calculators.socketio import SocketServer

# Create and start the server
# server = SocketServer(port=12345) # Specify a port if needed
# server.run()
```

### Endpoint
N/A (This is a server-side script, not an API endpoint)

### Parameters
- `port` (int, optional): The port number on which the server will listen. Defaults to a system-chosen available port.

### Request Example
```python
# To run the server:
# python your_script_name.py
```

### Response
#### Success Response
The server starts listening for incoming connections on the specified or default port.

#### Response Example
```
Server started on port 12345
```
```

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

### Connect to MySQL from Python

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/db/db.rst

Example of a MySQL connection URI and a Python function call to connect to the database.

```python
>>> mysql_url = 'mysql://ase:strongPassword@localhost:3306/my_awesome_project'
>>> connect(mysql_url)  # doctest: +SKIP
```

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

### PLUMED Setup Configuration

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/plumed.rst

Define the PLUMED simulation setup using a list of strings, specifying units, collective variables, and output files.

```python
setup = [f"UNITS LENGTH=A TIME={1/(1000 * units.fs)} ENERGY={units.mol/units.kJ}",
         "d: DISTANCE ATOMS=1,2",
         "PRINT ARG=d STRIDE=10 FILE=COLVAR"]
```

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

### Install ASE from PyPI using pip

Source: https://gitlab.com/ase/ase/-/blob/master/doc/install.rst

The recommended method for installing ASE is using pip, which fetches the latest stable version from PyPI. Use the --upgrade flag to ensure you have the latest version.

```bash
pip install --upgrade ase
```

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

### Exciting Ground State Input XML Example

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/exciting.rst

An example of an input XML file generated by the ExcitingGroundStateCalculator for a ground state calculation. This structure can be used directly or as a template.

```xml
<?xml version='1.0' encoding='UTF-8'?>
<input xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:noNamespaceSchemaLocation="http://xml.exciting-code.org/excitinginput.xsd">
  <title>N3O</title>
  <structure speciespath="$EXCITINGROOT/species/" autormt="false">
    <crystal>
      <basevect>1.88972595820018 0.00000000000000 0.00000000000000</basevect>
      <basevect>0.00000000000000 1.88972595820018 0.00000000000000</basevect>
      <basevect>0.00000000000000 0.00000000000000 1.88972595820018</basevect>
    </crystal>
    <species chemicalSymbol="N" speciesfile="N.xml">
      <atom coord="0.00000000000000 0.00000000000000 0.00000000000000"/>
      <atom coord="0.00000000000000 0.00000000000000 0.00000000000000"/>
      <atom coord="0.00000000000000 0.00000000000000 0.00000000000000"/>
    </species>
    <species chemicalSymbol="O" speciesfile="O.xml">
      <atom coord="0.50000000000000 0.50000000000000 0.50000000000000"/>
    </species>
  </structure>
  <relax/>
  <groundstate tforce="true" ngridk="1 2 3"/>
  <properties>
    <dos/>
    <bandstructure>
      <plot1d>
        <path steps="100">
          <point coord="0.75000   0.50000   0.25000" label="W"/>
          <point coord="0.50000   0.50000   0.50000" label="L"/>
          <point coord="0.00000   0.00000   0.00000" label="G"/>
          <point coord="0.50000   0.50000   0.00000" label="X"/>
          <point coord="0.75000   0.50000   0.25000" label="W"/>
          <point coord="0.75000   0.37500   0.37500" label="K"/>
        </path>
      </plot1d>
    </bandstructure>
  </properties>
</input>
```

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

### Geometry Optimization with ASE and deMon-Nano

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/demonnano.rst

Example demonstrating how to perform a geometry optimization using the deMon-Nano calculator within ASE.

```python
from ase.calculators.demonnano import DemonNano
from ase.optimize import BFGS
from ase.build import fcc111

# Build a surface
slab = fcc111('Cu', size=(2,2,3), vacuum=10.0)

# Set up the calculator
# Make sure to set DEMONNANO_BASIS_PATH and ASE_DEMONNANO_COMMAND
# environment variables
calc = DemonNano()
slab.set_calculator(calc)

# Optimize geometry
opt = BFGS(slab)
opt.run(fmax=0.05)

# Print final energy
print(slab.get_potential_energy())
```

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

### Socket Client Example (GPAW)

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/socketio/socketio.rst

Example of running a socket client, specifically demonstrating its use with GPAW. This client connects to a running socket server.

```APIDOC
## Socket Client Example (GPAW)

### Description
This example shows how to run a socket client using `ase.calculators.socketio.SocketClient`. It specifically demonstrates its application with GPAW, connecting to a pre-running socket server.

### Method
```python
from ase.calculators.socketio import SocketClient
from ase.io import read

# Assuming a server is already running and accessible.
# client = SocketClient(host='localhost', port=12345)
# atoms = read('structure.xyz')
# client.run(atoms)
```

### Endpoint
N/A (This is an SDK usage example, not an HTTP endpoint)

### Parameters
- `host` (str): The hostname or IP address of the server.
- `port` (int): The port number the server is listening on.
- `atoms` (ase.Atoms): The atomic structure to send to the server.

### Request Example
```python
# Assuming a server is running on localhost:12345
# from ase.calculators.gpaw import GPAW
# from ase.optimize import BFGS
# 
# # Setup GPAW calculator (this part might vary)
# calc = GPAW(mode='lcao', basis='dzp', xc='PBE', txt='gpaw.txt')
# atoms = read('initial_structure.xyz')
# atoms.calc = calc
# 
# # Run the client to connect to the server
# client = SocketClient(host='localhost', port=12345)
# # The client will send the atoms object to the server and potentially receive results.
# # The exact interaction depends on the server's implementation.
# # For example, if the server is expecting coordinates to calculate energy/forces:
# # client.run(atoms)
```

### Response
#### Success Response
The client successfully connects to the server and may exchange data (e.g., atomic coordinates, energy, forces) depending on the server's implementation.

#### Response Example
```json
{
  "status": "connected",
  "message": "Data exchanged successfully"
}
```
```

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

### Setup ACE Geometry Optimization

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/ace.rst

Sets up and runs a geometry optimization using ACE and the BFGS algorithm. Requires pseudopotential setup and a label.

```python
import sys
from ase.io import read
from ase.calculators.acemolecule import ACE
from ase.optimize import BFGS

basic_list = {'Cell' : 12.0, 'Pseudopotential' : {'Pseudopotential' : 1, 'Format' : 'upf', 'PSFilePath' : '/PATH/TO/UPF/FILES', 'PSFileSuffix' : '.pbe-theos.UPF'} }
label = sys.argv[1]    
mol= read('H2.xyz')
order_list = ["BasicInformation", "Guess", "Scf", "Force"]
ace = ACE(label=label, BasicInformation = basic_list, order = order_list)
mol.calc = ace
g_opt = BFGS(mol)
g_opt.run(fmax=0.05)
print ("OPT is end")
```

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

### Install ASE from Local Source

Source: https://gitlab.com/ase/ase/-/blob/master/doc/install.rst

Install ASE using pip from a local source directory. This method manages dependencies automatically. Ensure you have the source code cloned or extracted.

```bash
pip install /path/to/source
```

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

### Build HTML Documentation

Source: https://gitlab.com/ase/ase/-/blob/master/doc/development/writing_documentation_ase.rst

Navigate to the doc directory and run 'make' to build the HTML documentation. This may take time on the first run.

```console
cd ~/ase/doc
make
```

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

### MM-only Geometry Optimization Example

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/gromacs.rst

This Python script demonstrates an MM-only geometry optimization using Gromacs via ASE. It is intended as a basic example and not a production-ready simulation setup.

```python
from ase.calculators.gromacs import Gromacs
from ase.optimize import QuasiNewton
from ase.io import read, write

calc = Gromacs(charge_groups=None, 
               force_field='oplsaa', 
               water_model='tip3p', 
               clean=True, 
               gromacs_executable='gmx')

# Use a simple structure
# For a real simulation, you would need to prepare a topology and coordinates
# using gromacs tools like pdb2gmx and editconf.
# Here we assume 'his.pdb' and 'gromacs_example_mm_relax.py' are available.

# Example of setting up the calculator for MM-only relaxation
# Note: This is a simplified example and may require further setup for a real simulation.
# The actual relaxation would be performed by an ASE optimizer.

# For demonstration, let's assume we have a structure loaded
# atoms = read('his.pdb')
# atoms.calc = calc

# Example of how to use an ASE optimizer (e.g., QuasiNewton)
# dyn = QuasiNewton(atoms)
# dyn.run(fmax=0.05)

# The provided example file 'gromacs_example_mm_relax.py' likely contains the full setup.
# The following is a placeholder to indicate where the actual script content would go.
# The actual script content is in the 'gromacs_example_mm_relax.py' file.

print('This is a placeholder for the actual relaxation script.')
print('Refer to gromacs_example_mm_relax.py for the full example.')
```

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

### Upload to PyPI

Source: https://gitlab.com/ase/ase/-/blob/master/doc/development/newrelease.rst

Builds source and wheel distributions and uploads them to the Python Package Index. Ensure 'twine' is installed.

```bash
python3 setup.py sdist
python3 setup.py bdist_wheel
twine upload dist/*
```

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

### Get Slab Atom Tags

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/build/surface.rst

Retrieves the tags associated with atoms in a slab. Layer atoms are tagged by their layer number (starting from 1), and adsorbates are tagged with 0. This is useful for applying constraints.

```python
print(atoms.get_tags())
```

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

### Basic NEB Setup and Optimization

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/neb.rst

This snippet shows how to set up a NEB calculation by reading initial and final states, creating a band of images, interpolating positions, assigning calculators to intermediate images, and running the optimization.

```python
from ase.optimize import MDMin
from ase.calculators.calculator import Calculator
from ase.neb import NEB
from ase import io

# Assume MyCalculator is defined elsewhere
class MyCalculator(Calculator):
    def __init__(self, **kwargs):
        pass # Placeholder for actual calculator implementation
    def calculate(self, atoms, properties=['energy', 'forces'], system=None, available_properties=None):
        pass # Placeholder for actual calculation logic

# Read initial and final states:
initial = io.read('A.traj')
final = io.read('B.traj')

# Make a band consisting of 5 images:
images = [initial]
images += [initial.copy() for i in range(3)]
images += [final]

neb = NEB(images)

# Interpolate linearly the positions of the three middle images:
neb.interpolate()

# Set calculators:
for image in images[1:4]:
    image.calc = MyCalculator(...)

# Optimize:
optimizer = MDMin(neb, trajectory='A2B.traj')
optimizer.run(fmax=0.04)
```

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

### Calculate Phonon Dispersion for Bulk Aluminum

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/phonons.rst

Example demonstrating the calculation of phonon dispersion for bulk aluminum using a supercell and effective medium theory. This snippet requires prior setup of the system and calculator.

```python
from ase.calculators.emt import EMT
from ase.md.phonons import Phonons
from ase.build import fcc111

# Create a 7x7x7 supercell of fcc aluminum
a = 4.03
cell = [[0, a, a], [a, 0, a], [a, a, 0]]
atoms = fcc111('Al', size=(3, 3, 3), a=a)

# Set the calculator
atoms.calc = EMT()

# Calculate phonons
ph = Phonons(atoms, """""""
              # Parameters for the Phonons calculator
              # This section is typically configured based on the system and desired calculations
              """""""
              )

# Calculate and get the phonon dispersion
ph.run()
dispersion = ph.get_band_structure()

# Plot the dispersion
dispersion.plot()

```

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

### Build Documentation

Source: https://gitlab.com/ase/ase/-/blob/master/doc/development/newrelease.rst

Builds the project documentation and checks generated images. Navigate to the 'doc' directory before running.

```bash
cd doc
make clean
make
```

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

### Install Python Tkinter with Homebrew

Source: https://gitlab.com/ase/ase/-/blob/master/doc/install.rst

On macOS, install Python and Tkinter using Homebrew before installing ASE with pip. Note that Homebrew pip installs only to virtual environments.

```bash
$ brew install python-tk
```

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

### MinimaHopping Optional Parameters

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/optimize.rst

Demonstrates initializing MinimaHopping with various optional parameters to control temperature, energy thresholds, MD simulation, and logging.

```python
from ase.optimize.minimahopping import MinimaHopping
from ase.optimize import QuasiNewton

opt = MinimaHopping(atoms=system,
                    T0=1000.,
                    beta1=1.1,
                    beta2=1.1,
                    beta3=1. / 1.1,
                    Ediff0=0.5,
                    alpha1=0.98,
                    alpha2=1. / 0.98,
                    mdmin=2,
                    logfile='hop.log',
                    minima_threshold=0.5,
                    timestep=1.0,
                    optimizer=QuasiNewton,
                    minima_traj='minima.traj',
                    fmax=0.05
                    )
opt()
```

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

### Install ASE datafiles for calculator tests

Source: https://gitlab.com/ase/ase/-/blob/master/doc/development/tests.rst

Enable tests for calculators that require data files by installing the ase-datafiles package. This command installs the package for the current user.

```bash
pip install --user --upgrade git+https://gitlab.com/ase/ase-datafiles.git
```

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

### Berendsen NPT Dynamics Simulation Setup

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/md.rst

Sets up Berendsen NPT dynamics for a room temperature simulation. Adjust taut and taup for better sampling.

```python
dyn = NPTBerendsen(atoms, timestep=0.1 * units.fs, temperature_K=300,
                   taut=100 * units.fs, pressure_au=1.01325 * units.bar,
                   taup=1000 * units.fs, compressibility_au=4.57e-5 / units.bar)
```

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

### Test PLUMED Installation

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/plumed.rst

Verify the installation of the py-plumed package by creating a Plumed object.

```python
from plumed import Plumed
Plumed()
```

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

### Setup Basic ACE Calculation

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/ace.rst

Sets up a basic ground-state DFT calculation using the ACE calculator. Requires a label and an input XYZ file.

```python
import sys
from ase.io import read
from ase.calculators.acemolecule import ACE

label = sys.argv[1]    
mol= read('H2.xyz')
basic_list = {'Cell' : 12.0}
ace = ACE(label=label, BasicInformation = basic_list)
mol.calc = ace
print (mol.get_potential_energy())
```

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

### Show all details for a single row in a database

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/db/db.rst

This command-line example shows how to retrieve and display all details for a specific row within a database. The exact file and row identifier would be specified in the actual command.

```bash
ase db abc.db --rowid=1
```

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

### Install ASE Directly from Git Repository

Source: https://gitlab.com/ase/ase/-/blob/master/doc/install.rst

Install the latest development version of ASE directly from the master branch of its Git repository using pip. The --upgrade flag ensures the latest version is installed.

```bash
pip install --upgrade git+https://gitlab.com/ase/ase.git@master
```

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

### Basic ORCA calculator setup

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/orca.rst

Instantiate the ORCA calculator with a profile, specifying the simple input and ORCA blocks for parallel processing.

```python
from ase.calculators.orca import ORCA

calc = ORCA(profile=MyOrcaProfile,
              orcasimpleinput='B3LYP def2-TZVP',
              orcablocks='%pal nprocs 16 end')
```

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

### Configure Espresso Input Parameters

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/espresso.rst

Demonstrates how to pass Quantum ESPRESSO input parameters using the `input_data` dictionary. This allows for both flat and nested configuration of QE settings.

```python
input_data = {
    'system': {'ecutwfc': 60, 'ecutrho': 480},
    'disk_io': 'low',  # Automatically put into the 'control' section
}

calc = Espresso(
    profile=profile,
    pseudopotentials=pseudopotentials,
    tstress=True,  # deprecated, put in input_data
    tprnfor=True,  # deprecated, put in input_data
    input_data=input_data,
)
```

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

### Espresso Calculator Setup and Usage

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/calculators.rst

Demonstrates how to instantiate and use the Espresso calculator in ASE. It shows setting input parameters, pseudopotentials, and assigning the calculator to an Atoms object.

```python
>>> from ase.build import bulk
>>> from ase.calculators.espresso import Espresso
>>> espresso = Espresso(
                       input_data = {
                            'system': {
                               'ecutwfc': 60,
                            }},
                       pseudopotentials = {'Si': 'si_lda_v1.uspp.F.UPF'},
                       )
>>> si = bulk('Si')
>>> si.calc = espresso
>>> si.get_potential_energy()
-244.76638508140397
```

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

### Install ASE using pip

Source: https://gitlab.com/ase/ase/-/blob/master/README.rst

Installs the latest release of ASE. Ensure you have Python 3.10 or later.

```bash
pip install ase
```

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

### CASTEP Calculator Usage Example

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/castep.rst

Demonstrates basic usage of the CASTEP calculator with ASE, including setting up the calculator and running a calculation.

```python
from ase.calculators.castep import Castep
from ase.build import fcc111

# Create a simple surface
slab = fcc111('Cu', size=(2, 2, 2), vacuum=10.0)

# Set up the CASTEP calculator
calc = Castep(
    label='cu_fcc111',  # Output file label
    xc='PBE',           # Exchange-correlation functional
    kpts=(2, 2, 1),     # k-point grid
    spinpol=False,      # Spin-polarised calculation
    mode='lcao',        # Basis set mode
    basis='dzp',        # Basis set
    cut_off_energy=300, # Energy cutoff (eV)
    # Add other CASTEP parameters as needed
)

# Attach the calculator to the atoms object
slab.calc = calc

# Calculate the energy
energy = slab.get_potential_energy()

print(f'The energy of the slab is: {energy} eV')

# You can also access other properties like forces
# forces = slab.get_forces()
# print(f'Forces: {forces}')

# To write CASTEP input files:
# calc.write_input(slab)

# To read CASTEP output files:
# from ase.io import read
# output_atoms = read('cu_fcc111.cell')

```

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

### Configure Amber Simulation Input

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/amber.rst

Create an 'mm.in' file to define simulation parameters for Amber. This example sets up a single-step minimization to obtain energy and forces without performing dynamics.

```text
zero step md to get energy and force
&cntrl
  imin=0, nstlim=0,  ntx=1 !0 step md
  cut=100, ntb=0,          !non-periodic
  ntpr=1,ntwf=1,ntwe=1,ntwx=1 ! (output frequencies)
&end
END
```

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

### Install Development Version of ASE

Source: https://gitlab.com/ase/ase/-/blob/master/README.rst

Installs the latest development version directly from the GitLab repository. Requires Git.

```bash
pip install git+https://gitlab.com/ase/ase.git
```

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

### NWChem Example

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/socketio/socketio.rst

Example of using SocketIOCalculator with NWChem. It is recommended to use the 'with' statement for proper connection management.

```APIDOC
## NWChem Example

### Description
This example demonstrates how to integrate ASE with NWChem using the `SocketIOCalculator`. Using the `with` statement is the preferred method for ensuring the socket connection is handled correctly.

### Method
```python
from ase.calculators.socketio import SocketIOCalculator
from ase.io import read

# 'atoms' is an ASE Atoms object, and 'calc_params' contains NWChem settings.
# with SocketIOCalculator(atoms, **calc_params) as calc:
#     energy = calc.get_potential_energy()
#     forces = calc.get_forces()
```

### Endpoint
N/A (SDK usage example)

### Parameters
- `atoms` (ase.Atoms): The atomic structure.
- `**calc_params`: Additional parameters for the NWChem calculator.

### Request Example
```python
# Conceptual example; actual parameters depend on NWChem configuration.
# calc_params = {
#     'command': 'nwchem',
#     'input_params': {
#         'xc': 'b3lyp',
#         'basis': '6-31G*'
#     }
# }
# atoms = read('nwchem_structure.xyz')
# with SocketIOCalculator(atoms, **calc_params) as calc:
#     energy = calc.get_potential_energy()
```

### Response
#### Success Response
- `energy` (float): The calculated potential energy.
- `forces` (numpy.ndarray): Forces on each atom.

#### Response Example
```json
{
  "energy": -90.3,
  "forces": [[-0.03, 0.01, 0.02], [0.03, -0.01, -0.02]]
}
```
```

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

### Show all rows of SQLite database abc.db

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/db/db.rst

This command-line example demonstrates how to display all entries from an SQLite database file named 'abc.db'.

```bash
ase db abc.db
```

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

### Loading and Creating Systems from s22 Database

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/data.rst

Demonstrates how to load a system from the s22 database and create an Atoms object.

```APIDOC
## Loading and Creating Systems from s22 Database

### Description
This section shows how to access systems from the s22 database and create corresponding ASE Atoms objects.

### Usage
```python
from ase.data.s22 import s22, create_s22_system

sys = s22[0]  # Get the identifier for the first system
print(sys)  # Output: Ammonia_dimer

atoms = create_s22_system(sys) # Create an Atoms object for the system
print(atoms.get_chemical_symbols()) # Output: ['N', 'H', 'H', 'H', 'N', 'H', 'H', 'H']
```
```

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

### FHI-aims Example

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/socketio/socketio.rst

Example of using the SocketIOCalculator with FHI-aims. Using the 'with' statement is recommended for proper connection management.

```APIDOC
## FHI-aims Example

### Description
This example demonstrates the usage of the `SocketIOCalculator` with the FHI-aims code. It is best practice to use the `with` statement to ensure the socket connection is closed properly.

### Method
```python
from ase.calculators.socketio import SocketIOCalculator
from ase.io import read

# Assuming 'atoms' is an ASE Atoms object and 'calc_params' contains FHI-aims specific settings.
# with SocketIOCalculator(atoms, **calc_params) as calc:
#     energy = calc.get_potential_energy()
#     forces = calc.get_forces()
```

### Endpoint
N/A (SDK usage example)

### Parameters
- `atoms` (ase.Atoms): The atomic configuration.
- `**calc_params`: Additional keyword arguments for the FHI-aims calculator.

### Request Example
```python
# Conceptual example; actual parameters depend on FHI-aims configuration.
# calc_params = {
#     'command': 'aims.sh',
#     'input_params': {
#         'xc': 'PBE',
#         'basis_set': 'def-Boeck'
#     }
# }
# atoms = read('fhi_aims_structure.xyz')
# with SocketIOCalculator(atoms, **calc_params) as calc:
#     energy = calc.get_potential_energy()
```

### Response
#### Success Response
- `energy` (float): The calculated potential energy.
- `forces` (numpy.ndarray): Forces acting on each atom.

#### Response Example
```json
{
  "energy": -50.2,
  "forces": [[-0.05, 0.1, 0.0], [0.05, -0.1, 0.0]]
}
```
```

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

### Install Psi4 using Conda

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/psi4.rst

Install the Psi4 package and update it using conda. This is the recommended method for obtaining Psi4.

```bash
conda install psi4 -c psi4; conda update psi4 -c psi4
```

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

### DFTB+ Example

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/socketio/socketio.rst

Example for using SocketIOCalculator with DFTB+. Note that INET sockets might not work, and `Driver_Socket_Port` might be relevant.

```APIDOC
## DFTB+ Example

### Description
This example shows how to use the `SocketIOCalculator` with DFTB+. A note indicates that INET sockets may not function correctly, and the `Driver_Socket_Port` keyword might be necessary for testing.

### Method
```python
from ase.calculators.socketio import SocketIOCalculator
from ase.io import read

# 'atoms' is an ASE Atoms object, and 'calc_params' contains DFTB+ settings.
# Note: INET sockets might not work. Consider using `Driver_Socket_Port`.
# with SocketIOCalculator(atoms, **calc_params) as calc:
#     energy = calc.get_potential_energy()
#     forces = calc.get_forces()
```

### Endpoint
N/A (SDK usage example)

### Parameters
- `atoms` (ase.Atoms): The atomic structure.
- `**calc_params`: Additional parameters for the DFTB+ calculator.

### Request Example
```python
# Conceptual example; actual parameters depend on DFTB+ configuration.
# calc_params = {
#     'command': 'dftb+',
#     'input_params': {
#         'Driver_Socket_Port': 12345  # Example port number
#     }
# }
# atoms = read('dftb_structure.xyz')
# with SocketIOCalculator(atoms, **calc_params) as calc:
#     energy = calc.get_potential_energy()
```

### Response
#### Success Response
- `energy` (float): The calculated potential energy.
- `forces` (numpy.ndarray): Forces on each atom.

#### Response Example
```json
{
  "energy": -20.1,
  "forces": [[0.01, -0.02, 0.0], [-0.01, 0.02, 0.0]]
}
```
```

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

### EAM Calculator Example

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/eam.rst

Example demonstrating the usage of the EAM calculator. This snippet is part of the test suite for the EAM calculator.

```python
from ase.calculators.eam import EAM
from ase.build import bulk

# Create a bulk structure (e.g., FCC Cu)
cu = bulk('Cu', 'fcc', a=3.6, cubic=True)

# Instantiate the EAM calculator
# Specify the potential file path
# Example: Using a potential file for Copper
# Make sure 'Cu_pot.txt' is a valid EAM potential file for Copper
calculator = EAM(potential='Cu_pot.txt')

# Set the calculator for the atoms object
cu.calc = calculator

# Calculate energy and forces
energy = cu.get_potential_energy()
forces = cu.get_forces()

print(f'Energy: {energy:.4f} eV')
print('Forces:\n', forces)
```

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

### Configure ONETEP Pseudopotentials

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/onetep.rst

Demonstrates how to explicitly provide pseudopotential paths, use a pseudopotential directory, or rely on ASE's guessing mechanism.

```python
# Explicitly providing each path
calc = Onetep(pseudopotentials = {'H': '/path/to/pseudos/H.usp', 'O': '/path/to/pseudos/O.usp'})
# Using pseudo_path
calc = Onetep(pseudo_path = '/path/to/pseudos', pseudopotentials = {'H': 'H.usp', 'O': 'O.usp'})
# ASE will try to guess them
calc = Onetep(pseudo_path = '/path/to/pseudos')
```

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

### Install avconv and related libraries on Ubuntu

Source: https://gitlab.com/ase/ase/-/blob/master/doc/development/making_movies.rst

This command installs the avconv tool and necessary libraries for video processing on Ubuntu systems.

```bash
sudo apt-get install libav-tools libavcodec-extra-53 libavdevice-extra-53 libavformat-extra-53 libavutil-extra-51 libpostproc-extra-52 libswscale-extra-2
```

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

### Writing different file formats

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/io/io.rst

Examples demonstrating how to write atomic configurations to various file formats, including PNG images, animated GIFs, and POV-Ray files.

```APIDOC
## Writing Examples

### Write PNG image
```python
from ase import Atoms
from ase.build import fcc111, add_adsorbate, bulk
from ase.io import write

adsorbate = Atoms('CO')
adsorbate[1].z = 1.1
a = 3.61
slab = fcc111('Cu', (2, 2, 3), a=a, vacuum=7.0)
add_adsorbate(slab, adsorbate, 1.8, 'ontop')

write('slab.png', slab * (3, 3, 1), rotation='10z,-80x')
```

### Write animation with 500 ms duration per frame
```python
from ase.io import write
from ase.build import bulk

write('movie.gif', [bulk(s) for s in ['Cu', 'Ag', 'Au']], interval=500)
```

### Write POVRAY file
```python
from ase.io import write
from ase.build import fcc111, add_adsorbate, bulk

a = 3.61
slab = fcc111('Cu', (2, 2, 3), a=a, vacuum=7.0)

# Basic POVRAY output
write('slab.pov', slab * (3, 3, 1), generic_projection_settings = dict(rotation='10z,-80x'))

# POVRAY with bounding box and render method
d = a / 2**0.5
write('slab.pov', slab * (2, 2, 1),
      generic_projection_settings = dict(
      bbox=(d, 0, 3 * d, d * 3**0.5))).render()
```

### Extended XYZ format with unit cell
```python
from ase.io import write, read

# Assuming 'slab' is an ase.Atoms object
write('slab.xyz', slab)
a = read('slab.xyz')

# Write unit cell vectors at the end of the file
write('slab.xyz', vec_cell=True)
```

### ASE native format (.traj)
```python
from ase.io import write, read

# Assuming 'slab' is an ase.Atoms object
write('slab.traj', slab)
b = read('slab.traj')
```
```

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

### NWChem Socket I/O Example

Source: https://gitlab.com/ase/ase/-/blob/master/doc/ase/calculators/socketio/socketio.rst

Example of using SocketIOCalculator with NWChem. Using the 'with' statement is recommended for proper connection handling.

```python
from ase.calculators.nwchem import NWChem
from ase.optimize import BFGS
from ase.build import molecule

# Make a molecule
molecule = molecule('H2')

# Use SocketIOCalculator with NWChem
calc = NWChem(
    # Use socket I/O
    socket=True,
    # Specify port if needed
    # socket_port=5000,
    # Specify host if needed
    # socket_host='localhost',
)
molecule.calc = calc

# Optimize geometry
opt = BFGS(molecule)
opt.run(fmax=0.05)

# Close the calculator connection
calc.close()

```