import os
import h5py
import numpy as np
def recursively_load_dict_contents_from_group(h5file, path):
        """..."""
        import h5py
        ans = {}
        for key, item in h5file[path].items():
            if isinstance(item, h5py._hl.dataset.Dataset):
                ans[key] = item.value
            elif isinstance(item, h5py._hl.group.Group):
                ans[key] = recursively_load_dict_contents_from_group(h5file, path + key + '/')
        return ans

def read_hdf5(filename):
    '''
    this program is to read from a HDF5 file and write the data to an python dictionary 
    '''
    import h5py 
    dic={}
    with h5py.File(filename, 'r') as h5file:
         for key, item in h5file['/'].items():
            if isinstance(item, h5py._hl.dataset.Dataset):
                dic[key] = item.value
            elif isinstance(item, h5py._hl.group.Group):
                dic[key] = recursively_load_dict_contents_from_group(h5file, '/' + key + '/')
    return dic

def rname(dic,labels_in=None,labels_out=None):
    '''
    this programming is to rename the variable from labels_in into labels_out
    '''
    import numpy as np
    dic_new={}
    for i in np.arange(np.size(labels_in)):
        dic_new[labels_out[i]]=dic[labels_in[i]]
    return dic_new


def redic(dic):
    '''
    this programing is to convert the nest dictionary into a regular dictionary.
    like dict={'A':{'B':2}} => dict['A_B']=2
    '''  
    import numpy as np 
    dic_new={}
    for key in dic.keys():
        if isinstance(dic[key],dict):
           for subkey in dic[key].keys():
               if isinstance(dic[key][subkey],dict):
                    for subkey2 in dic[key][subkey].keys():
                        if isinstance(dic[key][subkey][subkey2],np.ndarray):
                           key_new=key+'_'+subkey+'_'+subkey2
                           dic_new[key_new]=dic[key][subkey][subkey2]
               elif isinstance(dic[key][subkey],np.ndarray):
                    key_new=key+'_'+subkey
                    dic_new[key_new]=dic[key][subkey]    
        elif isinstance(dic[key],np.ndarray):
           key_new=key
           dic_new[key_new]=dic[key]  
                
    return dic_new

def write_hdf5(dic,filename,path):
        """..."""
        if os.path.exists(filename):
            os.remove(filename)
        with h5py.File(filename, 'w') as h5file:
            recursively_save_dict_contents_to_group(h5file, path, dic)
def recursively_save_dict_contents_to_group(h5file, path, dic):
        """..."""
        # argument type checking
        if not isinstance(dic, dict):
            raise ValueError("must provide a dictionary")
        if not isinstance(path, str):
            raise ValueError("path must be a string")
        if not isinstance(h5file, h5py._hl.files.File):
            raise ValueError("must be an open h5py file")
        # save items to the hdf5 file
        for key, item in dic.items():
            if not isinstance(key, str):
                 key=str(key)
            #    raise ValueError("dict keys must be strings to save to hdf5")
            # save strings, numpy.int64, and numpy.float64 types
            if isinstance(item, (np.int64,np.int32,np.float32, np.float64, str)):
                h5file[path + key] = item
                if not h5file[path + key].value == item:
                    raise ValueError('The data representation in the HDF5 file does not match the original dict.')
            # save numpy arrays
            elif isinstance(item, np.ndarray):
                 dset=h5file.create_dataset(key,data=item,compression='gzip',compression_opts=9)
            #    h5file[path + key] = item
            #    if not np.array_equal(h5file[path + key].value, item):
            #        raise ValueError('The data representation in the HDF5 file does not match the original dict.')
            # save dictionaries
            elif isinstance(item, dict):
                recursively_save_dict_contents_to_group(h5file, path + key + '/', item)
            # other types cannot be saved and will result in an error
            else:
                raise ValueError('Cannot save %s type.' % type(item))