import sys
# sys.path.append(r'C:\Users\adabbate\Python_modules')
sys.path.append(r"C:\IPMBOLT\Toolbox\BOLT\toolbox")
sys.path.append(r"C:\IPMBOLT\Platform\oct-dist\install\Python")


import pandas as pd

class NodeExtractor:
    def __init__(self, filename, sheetname, Closed_system=True):
        self.filename = filename
        self.sheetname = sheetname
        self.Closed_system = Closed_system
        self.nodes, self.streamID, self.stream_ori, self.conditions = self.Extract_node_res()

    def Extract_node_res(self):
        #Read MultiRun Sheet
        xls = pd.read_excel(self.filename, sheet_name = self.sheetname, engine="openpyxl")
        conditions =  xls.iloc[0]
        conditions = conditions.reset_index()
        conditions = conditions[conditions.columns[1]]
        conditions = conditions.drop(labels=[0,1,2,5,6,7,8,9,10,11,12])
        xls = xls.drop(xls.index[0], axis = 0)
        xls.columns = xls.iloc[1]
        xls= xls.drop([2,3],axis=0)

        nodes = xls[xls['Variable'].str.contains("Sub_node.summary.h|Sub_node.summary.x|Sub_node.summary.p|Sub_node.summary.T|Sub_node.summary.isOff", na=False)]
        nodes   = nodes.drop(nodes.columns[[0,1,2,5,6,7,8,9,10,11,12]],axis = 1) 
        ritemTransormed = pd.DataFrame()
        replaceBlank = ritemTransormed#.dropna() 
        replaceBlank['Status'] = nodes.columns
        replaceBlank.index = nodes.columns
        replaceBlank['Conditions'] = conditions.values
        nodes = pd.concat([replaceBlank.transpose(),nodes], axis=0)
        nodes.columns = [*nodes.columns[0:2],*replaceBlank['Conditions'][2:].values]

        nodes['Variable'] = nodes['Variable'][2:].apply(lambda x: x[::-1])
        nodes['Name'] = nodes['Name'][2:].apply(lambda x: x[::-1])
        nodes['Name.Variable'] = nodes['Variable']+'.'+nodes['Name']

        S=nodes['Variable'].str.split('.')[2:]

        nodes['Variable_name'] = nodes['Name.Variable'][2:].apply(lambda x: '.'.join(x.split('.')[:3])[::-1])

        if len(S.min())>3:
            nodes['Node_name'] = nodes['Name.Variable'][2:].apply(lambda x: '.'.join((x.split('.')[3:-1]))[::-1])
            nodes['Module_name'] = nodes['Name.Variable'][2:].apply(lambda x: (x.split('.')[-1])[::-1])
        else:
            nodes['Node_name'] = nodes['Name.Variable'][2:].apply(lambda x: '.'.join((x.split('.')[3:]))[::-1])
            nodes['Module_name'] = 'equipment'

        nodes['Variable'] = nodes['Node_name']+'.'+nodes['Variable_name']
        cols = list(nodes.columns)
        cols = cols[-1:-4:-1] + cols[:-4]
        nodes = nodes[cols].drop(['Name'], axis=1)

        #Get Stream ID of each nodes
        StreamID = xls[xls['Variable'].str.contains("streamID", na=False)]

    #     StreamID = StreamID.drop(StreamID.columns[16:],axis = 1)
        StreamID = StreamID.drop(StreamID.columns[[0,1,2,5,6,7,8,9,10,11,12]],axis = 1)
        Stream_ori = StreamID
        nodes_lst = nodes['Node_name'].drop_duplicates().dropna()
    #     if Closed_system:
    #         StreamID = StreamID[StreamID['Variable'].str.contains('|'.join(nodes_lst[1:]))]
    #     else:
    #         StreamID = StreamID[StreamID['Name'].str.contains('|'.join(nodes_lst[1:]))]

        StreamID = StreamID.loc[:,~StreamID.columns.duplicated()].copy()
        if not self.Closed_system:
            StreamID['Variable'] = StreamID['Name']+'.'+StreamID['Variable']

        return nodes, StreamID, Stream_ori,conditions

    def get_single_point(self, nodes, condition, use = 'Quality'):

        nodes_trans = pd.DataFrame(columns=['Node','Pressure', 'Quality', 'Temperature','Enthalpy'])
        nodes_trans['Node'] = nodes['Node_name'].drop_duplicates().dropna()
        nodes_trans = nodes_trans.set_index('Node')
        for node in nodes_trans.index:  
            df = nodes[nodes['Node_name']==node]

            if df[condition][df['Variable_name'].str.contains('isOff')].values == 0  and nodes.at['Status',condition]=='Solved': 
                nodes_trans.at[node,'Pressure'] = float(df[condition][df['Variable'].str.endswith('summary.p')].values)
                nodes_trans.at[node,'Quality'] = float(df[condition][df['Variable'].str.endswith('summary.x')].values)
                nodes_trans.at[node,'Temperature'] = float(df[condition][df['Variable'].str.endswith('summary.T')].values)
                nodes_trans.at[node,'Enthalpy'] = (df[condition][df['Variable'].str.endswith('summary.h')].values).astype(float)

        return nodes_trans
    def get_circuits(self, condition):
        # Create a list of nodes for circuit B
        streamID_2 = list(self.streamID['Variable'][self.streamID[self.streamID.columns[-1]]==2].str.split('.', expand=True)[0])
        # Create a list of nodes for circuit A
        streamID_1 = list(self.streamID['Variable'][self.streamID[self.streamID.columns[-1]]==1].str.split('.', expand=True)[0])

        # Create a DataFrame of nodes for circuit B
        cycle_eqA = pd.concat([self.nodes[self.nodes.index == 'Status'],self.nodes[self.nodes['Node_name'].isin(streamID_1)][self.nodes['Module_name'] == 'equipment']])
        cycle_eqB = pd.concat([self.nodes[self.nodes.index == 'Status'],self.nodes[self.nodes['Node_name'].isin(streamID_2)][self.nodes['Module_name'] == 'equipment']])
        CircuitA = self.get_single_point(cycle_eqA, condition).dropna()
        CircuitB = self.get_single_point(cycle_eqB, condition).dropna()
        CircuitA["Enthalpy"] = CircuitA["Enthalpy"].apply(lambda x: x[0])
        CircuitB["Enthalpy"] = CircuitB["Enthalpy"].apply(lambda x: x[0])

        return CircuitA, CircuitB