# Copyright (C) University of Tennessee Health Science Center, Memphis, TN.
#
# This program is free software: you can redistribute it and/or modify it
# under the terms of the GNU Affero General Public License
# as published by the Free Software Foundation, either version 3 of the
# License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
# See the GNU Affero General Public License for more details.
#
# This program is available from Source Forge: at GeneNetwork Project
# (sourceforge.net/projects/genenetwork/).
#
# Contact Drs. Robert W. Williams and Xiaodong Zhou (2010)
# at rwilliams@uthsc.edu and xzhou15@uthsc.edu
#
#
#
# This module is used by GeneNetwork project (www.genenetwork.org)
#
# Created by GeneNetwork Core Team 2010/08/10


from gn2.base.mrna_assay_tissue_data import MrnaAssayTissueData
from gn3.computations.correlations import compute_corr_coeff_p_value
from gn2.wqflask.database import database_connection
from gn2.utility.tools import get_setting

#####################################################################################
# Input: primaryValue(list): one list of expression values of one probeSet,
#       targetValue(list): one list of expression values of one probeSet,
#               method(string): indicate correlation method ('pearson' or 'spearman')
# Output: corr_result(list): first item is Correlation Value, second item is tissue number,
#                           third item is PValue
# Function: get correlation value,Tissue quantity ,p value result by using R;
# Note : This function is special case since both primaryValue and targetValue are from
# the same dataset. So the length of these two parameters is the same. They are pairs.
# Also, in the datatable TissueProbeSetData, all Tissue values are loaded based on
# the same tissue order
#####################################################################################


def cal_zero_order_corr_for_tiss(primary_values, target_values, method="pearson"):
    """function use calls gn3 to compute corr,p_val"""

    (corr_coeff, p_val) = compute_corr_coeff_p_value(
        primary_values=primary_values, target_values=target_values, corr_method=method)

    return (corr_coeff, len(primary_values), p_val)

########################################################################################################
# input: cursor, symbolList (list), dataIdDict(Dict): key is symbol
# output: SymbolValuePairDict(dictionary):one dictionary of Symbol and Value Pair.
#        key is symbol, value is one list of expression values of one probeSet.
# function: wrapper function for getSymbolValuePairDict function
#          build gene symbol list if necessary, cut it into small lists if necessary,
#          then call getSymbolValuePairDict function and merge the results.
########################################################################################################


def get_trait_symbol_and_tissue_values(symbol_list=None):
    with database_connection(get_setting("SQL_URI")) as conn:
        tissue_data = MrnaAssayTissueData(gene_symbols=symbol_list, conn=conn)
        if len(tissue_data.gene_symbols) > 0:
            results = tissue_data.get_symbol_values_pairs()
            return results