Code Documentation¶
diffiqult.Task¶
-
class
diffiqult.Task.Tasks(mol, name, verbose=False)[source]¶ This class manage the implemented tasks over a system included in DiffiQult.
Attributes:
- sys : System_mol object
- Contains the basis functions, geometry and information of the a molecular system.
- name : string
- An id of the task, it is used as prefix for outputs.
- verbose: bool
It defines the output and screen options.
True it prints in screen all details and a file “name.out”.
- status: bool
Keep track of the success of the different task.
True the SCF and/or the optimization converged.
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__init__(mol, name, verbose=False)[source]¶ Initialize task object that contains the inital parameters.
Parameters:
- mol : System_mol object
- Contains the basis functions, geometry and information of the a molecular system.
- name : string
- An id of the task, it is used as prefix for outputs.
- Options:
- verbose : bool
It defines the output and screen options
True it prints in screen all details and a file “name.out”
- status: bool
Keep track of the success of the different task.
True the SCF and/or the optimization converged.
-
energy(max_scf=30, max_d=300, printguess=None, output=False, **kwargs)[source]¶ This function handdles the single point calculations
Options:
- max_scf : integer
- Maximum number of scf steps, default 30.
printguess : str
File path if it is requiered to prepare an inital guess for the molecular orbital coefficients.output : bool
True if it will print a molden file in case of success.
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optimization(max_scf=100, log=True, scf=True, name='Output', readguess=None, output=False, argnum=[0], **kwargs)[source]¶ This function handdles the optimization procedure
Options:
- argnum : list of integers
Parameter to optimize
0 widths
1 contraction coefficients
2 Gaussian centers
e.g. [0,1] to optimized widhts and contraction coefficients
- max_scf : integer
- Maximum number of scf steps, default 30
- log : bool
- If we are not optimizing the log of exponent, we highly recoment leave it as True, the default.
- name : str
- Output file name default Output
- readguess : str
- File path to a npy file in case on predefined initial guess of the density matrix
- output : bool
- True if it will print a molden file in case of success
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runtask(task, **kwargs)[source]¶ This method run a given task and if it has success, it uptates system with the most recent energy value and basis function
Parameters:
- task : str
- If defines the task:
‘Energy’ is a single point calculation.
‘Opt’ an optimization of a given parameter.
- Options:
- Check documentation for each task
Returns:
- success : bool
- True if task ended successfully.
diffiqult.Molecule¶
-
class
diffiqult.Molecule.Getbasis(molecule, basis, shifted=False)[source]¶ This class loads the basis function for a given molecule Attributes:
- alpha : array
- Gaussian withds
- coef : array
- Contraction coefficients
- xyz : array
- Gaussian centers
- list_contr : list
- List of integers with contractions, eg. [3,3] are two AO with three primitives each
- l : list of tuples
- List of tuple of integers with angular momentums eg. [(0,0,0),(0,1,0)] one s orbital and one p_x
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__init__(molecule, basis, shifted=False)[source]¶ - Parameters:
- molecule : list
It contains spects of geometry [( atomic_number_atom_1,(x,y,z),
atomic_number_atom_1,(x,y,z), atomic_number_atom_1,(x,y,z)]eg. water
(8,(0.0, 0.0, 0.091685801102911746)), (1,(1.4229678834888837, 0.0, -0.98120954931681137)), (1,(-1.4229678834888837, 0.0, -0.98120954931681137))]- basis : dict
- {atomic_number: [(‘type’,[(exp,coef),
- (exp,coef)]),
- (‘type’,[(exp,coef),
- (exp,coef)])],
- atomic_number: [(‘type’,[(exp,coef),
- (exp,coef)]),
- (‘type’,[(exp,coef),
- (exp,coef)])]}
-
class
diffiqult.Molecule.Getgeom(molecule)[source]¶ - This class loads the geometry in xyz coordinates
- Parameters:
- molecule : list
It contains spects of geometry [( atomic_number_atom_1,(x,y,z),
atomic_number_atom_1,(x,y,z), atomic_number_atom_1,(x,y,z)]
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class
diffiqult.Molecule.System_mol(mol, basis_set, ne, mol_name='molecule', angs=False, shifted=False)[source]¶ This class contains all the information of the system extracted from mol and basis
Parameters:
- alpha : array
- Gaussian withds
- coef : array
- Contraction coefficients
- xyz : array
- Gaussian centers
- list_contr : list
- List of integers with contractions, eg. [3,3] are two AO with three primitives each
- l : list of tuples
- List of tuple of integers with angular momentums eg. [(0,0,0),(0,1,0)] one s orbital and one p_x
-
__init__(mol, basis_set, ne, mol_name='molecule', angs=False, shifted=False)[source]¶ This function starts an object System_mol
- Parameters:
- mol : list
- It contains spects of geometry
- [( atomic_number_atom_1,(x,y,z),
- atomic_number_atom_1,(x,y,z), atomic_number_atom_1,(x,y,z)]
- basis: dict
- {atomic_number: [(‘type’,[(exp,coef),
- (exp,coef)]),
- (‘type’,[(exp,coef),
- (exp,coef)])],
- atomic_number: [(‘type’,[(exp,coef),
- (exp,coef)]),
- (‘type’,[(exp,coef),
- (exp,coef)])]}
- ne : int
- Number of electron
- mol_name : str
- An id
- shifted : bool
False in case standard basis functions
True in case costumized basis functions
- angs : bool
False is atomic units
True if lenght units are angstroms
diffiqult.Energy¶
-
diffiqult.Energy.rhfenergy(alpha_old, coef2, xyz, l, charges, xyz_atom, natoms, nbasis, contr_list, ne, max_scf, max_d, log, eigen, printguess, readguess, name, write, dtype)[source]¶ This function returns the rhf function
- Parameters:
- alpha_old : array
- Gaussian exponents
- coef2 : array
- Contraction coeffients
- xyz : array 3N
- Gaussian centers
- l : array 3N
- Angular momentum each entry is a vector eg. s orbital (0,0,0) or pz (1,0,0)
- charges : array
- Atom charges
- nbasis : int
- Number of basis
- contr_list: list of integers
- Specify the number of orbitals in each atom
- ne : int
- Number of electrons
- max_scf : int
- maximum number of scf cycles
- log : bool
- The exponents are given in log
- printguess: str or None
- File to print coeff matrix initial guess
- readguess : str or None
- File that contains coeff matrix initial guess
- name : str
- Output file name
- write : bool
- True if printing
- dtype : type of output
- This is the directive to know if algopy will be used or not np.float64(1.0) if it is a single point calculation otherwise, it specify the size of the UTMP, autodifferentiation
- Returns:
- energy : float
- RHF energy
diffiqult.Optimize¶
This routine was orginally taken from scipy
This module was taken from scipy and modified to optimize several parameters at a time with the BFGS Minimization
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diffiqult.Optimize.algopy_wrapper(function)[source]¶ Returnfunction to obtain the gradient of the function Parameters ———- f : callable
The function of which to determine the gradient (partial derivatives). Should take xk as first argument, other arguments to f can be supplied in*args. Should return a scalar, the value of the function at xk.- grad_function : function
- The partial derivatives of f to xk.
-
diffiqult.Optimize.fmin_bfgs(f, x0, fprime=None, args=(), argnum=None, gtol=1e-05, norm=inf, epsilon=1.4901161193847656e-08, maxiter=None, full_output=0, disp=1, retall=0, callback=None)[source]¶ Minimize a function using the BFGS algorithm.
- f : callable f(x,*args)
- Objective function to be minimized.
- x0 : ndarray
- Initial guess.
- fprime : callable f’(x,*args), optional
- Gradient of f.
- args : tuple, optional
- Extra arguments passed to f and fprime.
- gtol : float, optional
- Gradient norm must be less than gtol before successful termination.
- norm : float, optional
- Order of norm (Inf is max, -Inf is min)
- epsilon : int or ndarray, optional
- If fprime is approximated, use this value for the step size.
- callback : callable, optional
- An optional user-supplied function to call after each iteration. Called as callback(xk), where xk is the current parameter vector.
- maxiter : int, optional
- Maximum number of iterations to perform.
- full_output : bool, optional
- If True,return fopt, func_calls, grad_calls, and warnflag in addition to xopt.
- disp : bool, optional
- Print convergence message if True.
- retall : bool, optional
- Return a list of results at each iteration if True.
- xopt : ndarray
- Parameters which minimize f, i.e. f(xopt) == fopt.
- fopt : float
- Minimum value.
- gopt : ndarray
- Value of gradient at minimum, f’(xopt), which should be near 0.
- Bopt : ndarray
- Value of 1/f’‘(xopt), i.e. the inverse hessian matrix.
- func_calls : int
- Number of function_calls made.
- grad_calls : int
- Number of gradient calls made.
- warnflag : integer
- 1 : Maximum number of iterations exceeded. 2 : Gradient and/or function calls not changing.
- allvecs : list
- OptimizeResult at each iteration. Only returned if retall is True.
- minimize: Interface to minimization algorithms for multivariate
- functions. See the ‘BFGS’ method in particular.
Optimize the function, f, whose gradient is given by fprime using the quasi-Newton method of Broyden, Fletcher, Goldfarb, and Shanno (BFGS)
Wright, and Nocedal ‘Numerical Optimization’, 1999, pg. 198. This function was originally taken and modified from scipy