import h5py
import numpy as np
import WebAppSettings as settings


class GEMSearcher:


    def __init__(self):
        #self.dataset = h5py.File(settings.dataset_file, 'r')['rmac'][...]

        #np.save('/media/Data/data/beni_culturali/deploy/dataset', self.dataset)
        self.descs = np.load(settings.DATASET_GEM)
        #self.desc1 = np.load(settings.DATASET1)
        #self.desc2 = np.load(settings.DATASET2)

        #self.descs = (self.desc1 + self.desc2) / 2
        #self.descs /= np.linalg.norm(self.descs, axis=1, keepdims=True)
        self.ids = np.loadtxt(settings.DATASET_IDS, dtype=str).tolist()


    def get_id(self, idx):
        return self.ids[idx]


    def add(self, desc, id):
        self.ids.append(id)
        self.descs = np.vstack((self.descs, desc))
        self.save()


    def remove(self, id):
        idx = self.ids.index(id)
        del self.ids[idx]
        self.descs = np.delete(self.descs, idx, axis=0)


    def search_by_id(self, query_id, k=10):
        query_idx = self.ids.index(query_id)
        return self.search_by_img(self.descs[query_idx], k)

    def search_by_img(self, query, k=10):
       # print('----------query features-------')
        #print(query)
        dot_product = np.dot(self.descs, query[0])
        idx = dot_product.argsort()[::-1][:k]
        res = []
        for i in idx:
            res.append((self.ids[i], round(float(dot_product[i]), 3)))
        return res

    def save(self, is_backup=False):
        descs_file = settings.DATASET
        ids_file = settings.DATASET_IDS

        if is_backup:
            descs_file += '.bak'
            ids_file += '.bak'

        np.save(descs_file, self.descs)
        np.savetxt(ids_file, self.ids, fmt='%s')