xdatbus.fun_mtd
===============

.. py:module:: xdatbus.fun_mtd


Functions
---------

.. autoapisummary::

   xdatbus.fun_mtd.fes_1d
   xdatbus.fun_mtd.fes_2d
   xdatbus.fun_mtd.fes_3d
   xdatbus.fun_mtd.hillspot2hills
   xdatbus.fun_mtd.report_loader
   xdatbus.fun_mtd.xdc2xtc
   xdatbus.fun_mtd.reweight
   xdatbus.fun_mtd.pmf_321
   xdatbus.fun_mtd.neb_2d
   xdatbus.fun_mtd.local_minima


Module Contents
---------------

.. py:function:: fes_1d(hillspot_path, hills_count, cv_range, resolution=100)

   Calculate the 1D free energy profile from a HILLSPOT file.

       Parameters
       ----------
       hillspot_path : str
           The path of the HILLSPOT file
       hills_count : int
           The number of hills to be read
       cv_range : list
           The range of the collective variable
       resolution : int (optional)
           The resolution of the free energy profile


.. py:function:: fes_2d(hillspot_path, hills_count, cv_1_range, cv_2_range, resolution=100)

   Calculate the 2D free energy profile from a HILLSPOT file.

       Parameters
       ----------
       hillspot_path : str
           The path of the HILLSPOT file
       hills_count : int
           The number of hills to be read
       cv_1_range : list
           The range of the first collective variable
       cv_2_range : list
           The range of the second collective variable
       resolution : int (optional)
           The resolution of the free energy profile


.. py:function:: fes_3d(hillspot_path, hills_count, cv_1_range, cv_2_range, cv_3_range, resolution=100)

   Calculate the 2D free energy profile from a HILLSPOT file.

       Parameters
       ----------
       hillspot_path : str
           The path of the HILLSPOT file
       hills_count : int
           The number of hills to be read
       cv_1_range : list
           The range of the first collective variable
       cv_2_range : list
           The range of the second collective variable
       cv_3_range : list
           The range of the third collective variable
       resolution : int (optional)
           The resolution of the free energy profile


.. py:function:: hillspot2hills(hillspot_dir, hills_dir, cv, height_conversion=1, sigma_conversion=1, del_inter=False)

   Convert HILLSPOT file to HILLS file
       Parameters
       ----------
       hillspot_dir : str
           Path to HILLSPOT file
       hills_dir : str
           Path to the directory where the HILLS file will be created
       cv : str or list
           Name of the collective variable(s)
       height_conversion : float(optional)
           Conversion factor to convert the unit of the height from eV to kJ/mol
       sigma_conversion : float(optional)
           Conversion factor to convert the unit of the sigma based on the lattice in Angstrom
       del_inter : bool(optional)
           Delete the intermediate files created by this function.


.. py:function:: report_loader(aimd_path, load_pre_report=True, load_last_report=False, delete_intermediate_folders=True)

   Initialize a trajectory writer instance for *filename*.

       Parameters
       ----------
       aimd_path : str
           Output filename of the trajectory; the extension determines the format.
       load_pre_report : bool (optional)
           If ``True``, the trajectory will contain the previous frames (before the current run)
       load_last_report : bool (optional)
           If ``True``, the trajectory will contain the last frame
       delete_intermediate_folders : bool (optional)
           If ``True``, the intermediate folders will be deleted


.. py:function:: xdc2xtc(xdc_path)

   Convert a VASP XDATCAR file to an XTC trajectory file.

   Parameters
   ----------
   xdc_path : str
       Path to the XDATCAR file


.. py:function:: reweight(fes, cv, nv, kb, t, grid_min, grid_max, grid_num)

   Reweight a metadynamics simulation to the unbiased ensemble using histogram reweighting.

   In many cases you might decide which variable should be analyzed after having performed a metadynamics simulation.
   For example, you might want to calculate the free energy as a function of CVs other than those biased during the
   metadynamics simulation. At variance with standard MD simulations, you cannot simply calculate histograms of other
   variables directly from your metadynamics trajectory, because the presence of the metadynamics bias potential has
   altered the statistical weight of each frame. To remove the effect of this bias and thus be able to calculate properties
   of the system in the unbiased ensemble, you must reweight (unbias) your simulation.

       Parameters
       ----------
       fes : np.ndarray
           The free energy surface calculated from the metadynamics simulation.
       cv : np.ndarray
           The collective variable used in the metadynamics simulation.
       nv : np.ndarray
           The new collective variable for which the potential of mean force will be calculated.
       kb : float
           The Boltzmann constant.
       t : float
           The temperature of the simulation.
       grid_min : float
           The minimum value of the collective variable.
       grid_max : float
           The maximum value of the collective variable.
       grid_num : int
           The number of bins in the histogram.

   Returns
   -------
   np.ndarray
       The unbiased free energy surface.


.. py:function:: pmf_321(fes3d, axis1, axis2)

   project 3d free energy surface to 1d

   Parameters
   ----------
   fes3d : np.ndarray
       The 3d free energy surface.
   axis1 : int
       The axis to be projected.
   axis2 : int
       The axis to be projected.

   Returns
   -------
   np.ndarray
       The 2d free energy surface.


.. py:function:: neb_2d(fes, minima_1, minima_2, n_images, n_steps, spring_constant)

.. py:function:: local_minima(data, size=3)