#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Jan 22 18:19:27 2019

@author: kantundpeterpan
"""

import os
import pandas as pd
import mapply
#from .Species.Species_class import Species

from .helper_functions import *
from .MS_data_class import *
from .MS_analysis_class import *
from .mzml_Parser import *
from .test_file_dialog import *

from . import fastmzml
from . IsoDB import IsoDB

mapply.init(n_workers = -1, chunk_size = 100, max_chunks_per_worker = 8, progressbar = True)

class MSanalyzer(object):
    '''Kind of superclass containing analysis and data modules'''
    
    module_path = os.path.dirname(os.path.abspath(__file__))

    #https://physics.nist.gov/cgi-bin/Compositions/stand_alone.pl
    IsoPath = os.path.join(module_path, 'data', 'IsotopeDef')
    isotope_masses = pd.read_csv(IsoPath + '/isotopes_atomic_masses_processed.csv',
                                 index_col = 0)
    #isotope_masses.set_index('element_symbol', inplace = True)
    isotope_masses.dropna(inplace = True)
    
    ResPath = os.path.join(module_path, 'data', 'ResidueDef')
    residues = pd.read_csv(ResPath + '/residues.csv')
    residues.set_index('Residue', inplace = True)
    
    #additional databases for different labelings?
    #dictionary of dataframes with labeling as keys?
    SpecPath = os.path.join(module_path, 'data', 'SpeciesDef')
    mol_db = pd.read_csv(SpecPath + '/species_coli_lac.csv')
    
    #mol_db.set_index('Species')
    
    m_h = IsoDB.H[1]    #1.0078250322 
    m_na = IsoDB.Na[23] #22.98976928
    m_k_39 = IsoDB.K[39] #38.96370649

    @classmethod
    def add_species_obj(self):
        from .Species.Species_class import Species

        self.mol_db['species_obj'] = self.mol_db.mapply(lambda x: Species(name = x.Species,
                   residue_string = x.sequence, msanalyzer = self, labeling_variants = eval(x.labeling_variants)), axis = 1)
        self.mol_db = self.mol_db.set_index('Species')

    def find_labelings_variants(self, mass, precision_in_ppm, df_to_search):
        
        ll = mass * (1 - precision_in_ppm * 1e-06)
        ul = mass * (1 + precision_in_ppm * 1e-06)
        
        try:
            assert hasattr(df_to_search, 'monoisotopic_mass')
        except:
            print('database not correctly formatted')
            return
        
        ind = (df_to_search.monoisotopic_mass>ll) & (df_to_search.monoisotopic_mass<ul) 
        
        search = df_to_search[ind]
        
        return search
        
    def __init__(self, filename='filedialog', plot_tic=True,
                 fast=False, fast_stream = False):
        
        #self.add_species_obj()
        
        if filename == 'filedialog':
            fd = FileDialog()
            filename = fd.openFileNameDialog()
        
        if filename != '':
            self.path = os.path.abspath(filename)
            self.name = filename[:-5]
            
            if '.txt' in self.path:
                self.raw_data = load_mz_txt(filename)
                self.data = MS_data(self)
                self.analysis = MS_analysis(self)
            
            if '.csv' in self.path:
                self.raw_data = pd.read_csv(filename, header = 0)
                if self.raw_data.shape[1] == 3:
                    self.raw_data = self.raw_data.iloc[:,1:3]
                self.raw_data.columns = ['x', 'y']
                self.data = MS_data(self)
                self.analysis = MS_analysis(self) 
                
            if '.mzml' in self.path or '.mzML' in self.path:
                self.data = MS_data(self)
                if fast:
                    self.mzml_parser = fastmzml.FastMZml(filename, self, stream = fast_stream)
                else:
                    self.mzml_parser = mzML_parser(filename, self)
                self.analysis = MS_analysis(self)
                if plot_tic:
                    self.analysis.plot_tic()
    
    def preparePickle(self):
        for attribute in ('fig', 'ax', 'root',
                          'data_line', 'peak_label_dialog',
                          'cursor'):
            setattr(self.analysis, attribute, None)