import os

import dpdata
import numpy as np
import scipy.constants as pc


class NBandsEsti:
    def __init__(self, test_list):
        if isinstance(test_list, list):
            ele_t = []
            vol = []
            d_nbd = []
            nbd = []
            for ii in test_list:
                res = NBandsEsti._get_res(ii)
                ele_t.append(res["ele_temp"])
                vol.append(res["vol"])
                d_nbd.append(NBandsEsti._get_default_nbands(res))
                nbd.append(res["nbands"])
            ele_t = np.array(ele_t)
            vol = np.array(vol)
            d_nbd = np.array(d_nbd)
            nbd = np.array(nbd)
            alpha = (nbd - d_nbd) / vol / ele_t**1.5
            self.err = np.std(alpha)
            self.pref = np.average(alpha)
            # print(np.average(alpha), np.std(alpha), self.err/self.pref)
            # print((ele_t), vol, d_nbd, nbd, alpha)
        elif isinstance(test_list, str):
            with open(test_list) as fp:
                self.pref = float(fp.readline())
                self.err = float(fp.readline())
        else:
            raise RuntimeError("unknown input type " + type(test_list))

    def save(self, fname):
        with open(fname, "w") as fp:
            fp.write(str(self.pref) + "\n")
            fp.write(str(self.err) + "\n")

    def predict(self, target_dir, tolerance=0.5):
        res = NBandsEsti._get_res(target_dir)
        ele_t = res["ele_temp"]
        vol = res["vol"]
        d_nbd = NBandsEsti._get_default_nbands(res)
        nbd = res["nbands"]
        esti = (self.pref + tolerance * self.err) * ele_t**1.5 * vol + d_nbd
        return int(esti) + 1

    @classmethod
    def _get_res(self, res_dir):
        res = {}
        sys = dpdata.System(os.path.join(res_dir, "POSCAR"))
        res["natoms"] = sys["atom_numbs"]
        res["vol"] = np.linalg.det(sys["cells"][0])
        res["nvalence"] = self._get_potcar_nvalence(os.path.join(res_dir, "POTCAR"))
        res["ele_temp"] = (
            self._get_incar_ele_temp(os.path.join(res_dir, "INCAR"))
            * pc.electron_volt
            / pc.Boltzmann
        )
        res["nbands"] = self._get_incar_nbands(os.path.join(res_dir, "INCAR"))
        return res

    @classmethod
    def _get_default_nbands(self, res):
        ret = 0
        for ii, jj in zip(res["natoms"], res["nvalence"]):
            ret += ii * jj // 2 + ii // 2 + 2
        return ret

    @classmethod
    def _get_potcar_nvalence(self, fname):
        with open(fname) as fp:
            pot_str = fp.read().split("\n")
        head_idx = []
        for idx, ii in enumerate(pot_str):
            if ("PAW_" in ii) and ("TITEL" not in ii):
                head_idx.append(idx)
        res = []
        for ii in head_idx:
            res.append(float(pot_str[ii + 1]))
        return res

    @classmethod
    def _get_incar_ele_temp(self, fname):
        from pymatgen.io.vasp.inputs import Incar

        incar = Incar.from_file(fname)
        return incar["SIGMA"]

    @classmethod
    def _get_incar_nbands(self, fname):
        from pymatgen.io.vasp.inputs import Incar

        incar = Incar.from_file(fname)
        return incar.get("NBANDS")
