"""The cnapy yield optimization dialog"""

import io
import re
import traceback

from qtpy.QtCore import Qt, Signal
from qtpy.QtWidgets import (QCompleter, QDialog, QHBoxLayout, QLabel,
                            QLineEdit, QMessageBox, QPushButton, QVBoxLayout)

from cnapy.appdata import AppData
from cnapy.gui_elements.central_widget import CentralWidget
import cnapy.utils as utils


class CompleterLineEdit(QLineEdit):
    '''does new completion after Plus '+' '''

    def __init__(self, wordlist, *args):
        QLineEdit.__init__(self, *args)
        self.mycompleter = QCompleter(wordlist)
        self.mycompleter.setCaseSensitivity(Qt.CaseInsensitive)
        self.mycompleter.setWidget(self)
        self.textChanged.connect(self.text_changed)
        self.mycompleter.activated.connect(self.complete_text)

    def text_changed(self, text):
        all_text = text
        text = all_text[:self.cursorPosition()]
        prefix = text.split('+')[-1].strip()
        prefix = prefix.split(' ')[-1].strip()
        self.mycompleter.setCompletionPrefix(prefix)
        if prefix != '':
            self.mycompleter.complete()
        self.textChangedX.emit(self.text())

    def complete_text(self, text):
        cursor_pos = self.cursorPosition()
        before_text = self.text()[:cursor_pos]
        after_text = self.text()[cursor_pos:]
        prefix = before_text.split('+')[-1]
        prefix = prefix.split(' ')[-1]
        prefix_len = len(prefix.strip())
        self.setText(before_text[:cursor_pos - prefix_len] + text + after_text)
        self.setCursorPosition(cursor_pos - prefix_len + len(text))

    textChangedX = Signal(str)


class YieldOptimizationDialog(QDialog):
    """A dialog to perform yield optimization"""

    def __init__(self, appdata: AppData, central_widget: CentralWidget):
        QDialog.__init__(self)
        self.setWindowTitle("Yield optimization")

        self.appdata = appdata
        self.central_widget = central_widget
        self.eng = appdata.engine

        self.linear_re = re.compile(
            r'([ ]*(?P<factor1>[-]?\d*)[ ]*[*]?[ ]*(?P<reac_id>[abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVW]+\w*)[ ]*[*]?[ ]*(?P<factor2>[-]?\d*)[ ]*)')
        completer = QCompleter(
            self.appdata.project.cobra_py_model.reactions.list_attr("id"), self)
        completer.setCaseSensitivity(Qt.CaseInsensitive)

        self.layout = QVBoxLayout()
        l = QLabel("Define the yield function Y=c*r/d*r by providing c and d as linear expression of form: \n \
                   id_1 * w_1 + ... id_n * w_n\n \
                   Where id_x are reaction ids and w_x optional weighting factor\n")
        self.layout.addWidget(l)
        t1 = QLabel(
            "Define c")
        self.layout.addWidget(t1)
        self.c = CompleterLineEdit(
            self.appdata.project.cobra_py_model.reactions.list_attr("id"), "")
        self.c.setCompleter(completer)
        self.c.setPlaceholderText("EX_etoh")
        self.layout.addWidget(self.c)
        t2 = QLabel(
            "Define d")
        self.layout.addWidget(t2)
        self.d = CompleterLineEdit(
            self.appdata.project.cobra_py_model.reactions.list_attr("id"), "")
        self.d.setPlaceholderText("- EX_glc")
        self.d.setCompleter(completer)
        self.layout.addWidget(self.d)

        l3 = QHBoxLayout()
        self.button = QPushButton("Compute")
        self.cancel = QPushButton("Close")
        l3.addWidget(self.button)
        l3.addWidget(self.cancel)
        self.layout.addItem(l3)
        self.setLayout(self.layout)

        # Connecting the signal
        self.c.textChangedX.connect(self.validate_dialog)
        self.d.textChangedX.connect(self.validate_dialog)
        self.cancel.clicked.connect(self.reject)
        self.button.clicked.connect(self.compute)

        self.validate_dialog()

    def validate_dialog(self):

        valid_c = self.validate_linear_expression(self.c.text())
        valid_d = self.validate_linear_expression(self.d.text())
        if valid_c and valid_d:
            self.button.setEnabled(True)
        else:
            self.button.setEnabled(False)

    def validate_linear_expression(self, text: str):
        ''' Return True if text is a valid polynom else False'''
        texts = text.split('+')
        valid = True
        for elem in texts:
            match = self.linear_re.fullmatch(elem)
            if match is None:
                valid = False
            else:
                if match.groupdict()['reac_id'] not in self.appdata.project.cobra_py_model.reactions.list_attr("id"):
                    valid = False
        return valid

    def compute(self):

        self.setCursor(Qt.BusyCursor)
        with self.appdata.project.cobra_py_model as model:
            self.appdata.project.load_scenario_into_model(model)
            # create CobraModel for matlab
            self.appdata.create_cobra_model()

            self.eng.eval("load('cobra_model.mat')",
                          nargout=0)
            self.eng.eval("cnap = CNAcobra2cna(cbmodel);",
                          nargout=0)

            # get some data
            self.eng.eval("reac_id = cellstr(cnap.reacID)';",
                          nargout=0)
            reac_id = []
            if self.appdata.is_matlab_set():
                reac_id = self.eng.workspace['reac_id']
            elif self.appdata.is_octave_ready():
                reac_id = self.eng.pull('reac_id')
                reac_id = reac_id.tolist()[0]
            else:
                print("Error: Neither matlab nor octave found")

            c = []
            c_elements = self.c.text().split('+')
            for elem in c_elements:
                match = self.linear_re.fullmatch(elem)
                reaction = match.groupdict()['reac_id']
                factor1 = match.groupdict()['factor1']
                factor2 = match.groupdict()['factor2']

                if factor1 == '':
                    factor1 = 1
                elif factor1 == '-':
                    factor1 = -1
                else:
                    factor1 = int(factor1)
                if factor2 == '':
                    factor2 = 1
                elif factor2 == '-':
                    factor2 = -1
                else:
                    factor2 = int(factor2)

                factor = factor1*factor2
                c.append((factor, reaction))
            res = []
            idx = 0
            for r1 in reac_id:
                res.append(0)
                for (factor, r2) in c:
                    if r1 == r2:
                        if factor == "":
                            res[idx] = 1
                        else:
                            res[idx] = int(factor)
                        break
                idx = idx+1
            code = "c =" + str(res)+";"
            self.eng.eval(code, nargout=0)

            d = []
            d_elements = self.d.text().split('+')
            for elem in d_elements:
                match = self.linear_re.fullmatch(elem)
                reaction = match.groupdict()['reac_id']
                factor1 = match.groupdict()['factor1']
                factor2 = match.groupdict()['factor2']
                if factor1 == '':
                    factor1 = 1
                elif factor1 == '-':
                    factor1 = -1
                else:
                    factor1 = int(factor1)
                if factor2 == '':
                    factor2 = 1
                elif factor2 == '-':
                    factor2 = -1
                else:
                    factor2 = int(factor2)
                factor = factor1*factor2
                d.append((factor, reaction))
            res = []
            idx = 0
            for r1 in reac_id:
                res.append(0)
                for (factor, r2) in d:
                    if r1 == r2:
                        if factor == "":
                            res[idx] = 1
                        else:
                            res[idx] = int(factor)
                        break
                idx = idx+1
            code = "d =" + str(res)+";"
            self.eng.eval(code, nargout=0)

            self.eng.eval("fixedFluxes =[];", nargout=0)
            self.eng.eval("c_macro =[];", nargout=0)
            # solver: selects the LP solver
            # 0: GLPK (glpklp)
            # 1: Matlab Optimization Toolbox (linprog)
            # 2: CPLEX (cplexlp)
            # -1: (default) Either the solver CPLEX or GLPK or MATLAB (linprog) is used
            # (in this order), depending on availability.
            self.eng.eval("solver =1;", nargout=0)

            # verbose: controls the output printed to the command line
            # -1: suppress all output, even warnings
            #  0: no solver output, but warnings and information on final result will be shown
            #  1: as option '0' but with additional solver output
            #  (default: 0)
            self.eng.eval("verbose = 0;", nargout=0)
            if self.appdata.is_matlab_set():
                try:
                    self.eng.eval(
                        "[maxyield,flux_vec,success, status]= CNAoptimizeYield(cnap, c, d, fixedFluxes, c_macro, solver, verbose);",
                        nargout=0)

                except Exception:
                    output = io.StringIO()
                    traceback.print_exc(file=output)
                    exstr = output.getvalue()
                    print(exstr)
                    utils.show_unknown_error_box(exstr)
                    return
                else:
                    success = self.eng.workspace['success']
                    status = self.eng.workspace['status']
                    maxyield = self.eng.workspace['maxyield']
                    flux_vec = self.eng.workspace['flux_vec']

                    if success == 0.0:
                        QMessageBox.warning(self, 'No Solution!',
                                            'No solution found! Maybe unbound.\nStatus:'+str(status))
                    else:
                        QMessageBox.warning(self, 'Solution!',
                                            'Maximum yield: '+str(maxyield))
                        # write results into comp_values
                        idx = 0
                        for r in reac_id:
                            val = flux_vec[idx][0]
                            self.appdata.project.comp_values[r] = (
                                float(val), float(val))
                            idx = idx+1
                        self.appdata.project.comp_values_type = 0
                        self.central_widget.update()

            elif self.appdata.is_octave_ready():
                a = self.eng.eval(
                    "[maxyield,flux_vec,success, status]= CNAoptimizeYield(cnap, c, d, fixedFluxes, c_macro, solver, verbose);", nargout=0)

                success = self.eng.pull('success')
                status = self.eng.pull('status')
                maxyield = self.eng.pull('maxyield')
                flux_vec = self.eng.pull('flux_vec')

                if success == 0.0:
                    QMessageBox.warning(self, 'No Solution!',
                                              'No solution found! Maybe unbound.\nStatus:'+str(status))
                else:
                    QMessageBox.warning(self, 'Solution!',
                                        'Maximum yield: '+str(maxyield))

                    # write results into comp_values
                    idx = 0
                    for r in reac_id:
                        val = flux_vec[idx][0]
                        self.appdata.project.comp_values[r] = (
                            float(val), float(val))
                        idx = idx+1
                    self.appdata.project.comp_values_type = 0
                    self.central_widget.update()

        self.setCursor(Qt.ArrowCursor)

"""The cnapy yield optimization dialog"""

import io
import re
import traceback

from qtpy.QtCore import Qt, Signal
from qtpy.QtWidgets import (QCompleter, QDialog, QHBoxLayout, QLabel,
                            QLineEdit, QMessageBox, QPushButton, QVBoxLayout)

from cnapy.appdata import AppData
from cnapy.gui_elements.central_widget import CentralWidget
import cnapy.utils as utils


class CompleterLineEdit(QLineEdit):
    '''does new completion after Plus '+' '''

    def __init__(self, wordlist, *args):
        QLineEdit.__init__(self, *args)
        self.mycompleter = QCompleter(wordlist)
        self.mycompleter.setCaseSensitivity(Qt.CaseInsensitive)
        self.mycompleter.setWidget(self)
        self.textChanged.connect(self.text_changed)
        self.mycompleter.activated.connect(self.complete_text)

    def text_changed(self, text):
        all_text = text
        text = all_text[:self.cursorPosition()]
        prefix = text.split('+')[-1].strip()
        prefix = prefix.split(' ')[-1].strip()
        self.mycompleter.setCompletionPrefix(prefix)
        if prefix != '':
            self.mycompleter.complete()
        self.textChangedX.emit(self.text())

    def complete_text(self, text):
        cursor_pos = self.cursorPosition()
        before_text = self.text()[:cursor_pos]
        after_text = self.text()[cursor_pos:]
        prefix = before_text.split('+')[-1]
        prefix = prefix.split(' ')[-1]
        prefix_len = len(prefix.strip())
        self.setText(before_text[:cursor_pos - prefix_len] + text + after_text)
        self.setCursorPosition(cursor_pos - prefix_len + len(text))

    textChangedX = Signal(str)


class YieldOptimizationDialog(QDialog):
    """A dialog to perform yield optimization"""

    def __init__(self, appdata: AppData, central_widget: CentralWidget):
        QDialog.__init__(self)
        self.setWindowTitle("Yield optimization")

        self.appdata = appdata
        self.central_widget = central_widget
        self.eng = appdata.engine

        self.linear_re = re.compile(
            r'([ ]*(?P<factor1>[-]?\d*)[ ]*[*]?[ ]*(?P<reac_id>[abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVW]+\w*)[ ]*[*]?[ ]*(?P<factor2>[-]?\d*)[ ]*)')
        completer = QCompleter(
            self.appdata.project.cobra_py_model.reactions.list_attr("id"), self)
        completer.setCaseSensitivity(Qt.CaseInsensitive)

        self.layout = QVBoxLayout()
        l = QLabel("Define the yield function Y=c*r/d*r by providing c and d as linear expression of form: \n \
                   id_1 * w_1 + ... id_n * w_n\n \
                   Where id_x are reaction ids and w_x optional weighting factor\n")
        self.layout.addWidget(l)
        t1 = QLabel(
            "Define c")
        self.layout.addWidget(t1)
        self.c = CompleterLineEdit(
            self.appdata.project.cobra_py_model.reactions.list_attr("id"), "")
        self.c.setCompleter(completer)
        self.c.setPlaceholderText("EX_etoh")
        self.layout.addWidget(self.c)
        t2 = QLabel(
            "Define d")
        self.layout.addWidget(t2)
        self.d = CompleterLineEdit(
            self.appdata.project.cobra_py_model.reactions.list_attr("id"), "")
        self.d.setPlaceholderText("- EX_glc")
        self.d.setCompleter(completer)
        self.layout.addWidget(self.d)

        l3 = QHBoxLayout()
        self.button = QPushButton("Compute")
        self.cancel = QPushButton("Close")
        l3.addWidget(self.button)
        l3.addWidget(self.cancel)
        self.layout.addItem(l3)
        self.setLayout(self.layout)

        # Connecting the signal
        self.c.textChangedX.connect(self.validate_dialog)
        self.d.textChangedX.connect(self.validate_dialog)
        self.cancel.clicked.connect(self.reject)
        self.button.clicked.connect(self.compute)

        self.validate_dialog()

    def validate_dialog(self):

        valid_c = self.validate_linear_expression(self.c.text())
        valid_d = self.validate_linear_expression(self.d.text())
        if valid_c and valid_d:
            self.button.setEnabled(True)
        else:
            self.button.setEnabled(False)

    def validate_linear_expression(self, text: str):
        ''' Return True if text is a valid polynom else False'''
        texts = text.split('+')
        valid = True
        for elem in texts:
            match = self.linear_re.fullmatch(elem)
            if match is None:
                valid = False
            else:
                if match.groupdict()['reac_id'] not in self.appdata.project.cobra_py_model.reactions.list_attr("id"):
                    valid = False
        return valid

    def compute(self):

        self.setCursor(Qt.BusyCursor)
        with self.appdata.project.cobra_py_model as model:
            self.appdata.project.load_scenario_into_model(model)
            # create CobraModel for matlab
            self.appdata.create_cobra_model()

            self.eng.eval("load('cobra_model.mat')",
                          nargout=0)
            self.eng.eval("cnap = CNAcobra2cna(cbmodel);",
                          nargout=0)

            # get some data
            self.eng.eval("reac_id = cellstr(cnap.reacID)';",
                          nargout=0)
            reac_id = []
            if self.appdata.is_matlab_set():
                reac_id = self.eng.workspace['reac_id']
            elif self.appdata.is_octave_ready():
                reac_id = self.eng.pull('reac_id')
                reac_id = reac_id.tolist()[0]
            else:
                print("Error: Neither matlab nor octave found")

            c = []
            c_elements = self.c.text().split('+')
            for elem in c_elements:
                match = self.linear_re.fullmatch(elem)
                reaction = match.groupdict()['reac_id']
                factor1 = match.groupdict()['factor1']
                factor2 = match.groupdict()['factor2']

                if factor1 == '':
                    factor1 = 1
                elif factor1 == '-':
                    factor1 = -1
                else:
                    factor1 = int(factor1)
                if factor2 == '':
                    factor2 = 1
                elif factor2 == '-':
                    factor2 = -1
                else:
                    factor2 = int(factor2)

                factor = factor1*factor2
                c.append((factor, reaction))
            res = []
            idx = 0
            for r1 in reac_id:
                res.append(0)
                for (factor, r2) in c:
                    if r1 == r2:
                        if factor == "":
                            res[idx] = 1
                        else:
                            res[idx] = int(factor)
                        break
                idx = idx+1
            code = "c =" + str(res)+";"
            self.eng.eval(code, nargout=0)

            d = []
            d_elements = self.d.text().split('+')
            for elem in d_elements:
                match = self.linear_re.fullmatch(elem)
                reaction = match.groupdict()['reac_id']
                factor1 = match.groupdict()['factor1']
                factor2 = match.groupdict()['factor2']
                if factor1 == '':
                    factor1 = 1
                elif factor1 == '-':
                    factor1 = -1
                else:
                    factor1 = int(factor1)
                if factor2 == '':
                    factor2 = 1
                elif factor2 == '-':
                    factor2 = -1
                else:
                    factor2 = int(factor2)
                factor = factor1*factor2
                d.append((factor, reaction))
            res = []
            idx = 0
            for r1 in reac_id:
                res.append(0)
                for (factor, r2) in d:
                    if r1 == r2:
                        if factor == "":
                            res[idx] = 1
                        else:
                            res[idx] = int(factor)
                        break
                idx = idx+1
            code = "d =" + str(res)+";"
            self.eng.eval(code, nargout=0)

            self.eng.eval("fixedFluxes =[];", nargout=0)
            self.eng.eval("c_macro =[];", nargout=0)
            # solver: selects the LP solver
            # 0: GLPK (glpklp)
            # 1: Matlab Optimization Toolbox (linprog)
            # 2: CPLEX (cplexlp)
            # -1: (default) Either the solver CPLEX or GLPK or MATLAB (linprog) is used
            # (in this order), depending on availability.
            self.eng.eval("solver =1;", nargout=0)

            # verbose: controls the output printed to the command line
            # -1: suppress all output, even warnings
            #  0: no solver output, but warnings and information on final result will be shown
            #  1: as option '0' but with additional solver output
            #  (default: 0)
            self.eng.eval("verbose = 0;", nargout=0)
            if self.appdata.is_matlab_set():
                try:
                    self.eng.eval(
                        "[maxyield,flux_vec,success, status]= CNAoptimizeYield(cnap, c, d, fixedFluxes, c_macro, solver, verbose);",
                        nargout=0)

                except Exception:
                    output = io.StringIO()
                    traceback.print_exc(file=output)
                    exstr = output.getvalue()
                    print(exstr)
                    utils.show_unknown_error_box(exstr)
                    return
                else:
                    success = self.eng.workspace['success']
                    status = self.eng.workspace['status']
                    maxyield = self.eng.workspace['maxyield']
                    flux_vec = self.eng.workspace['flux_vec']

                    if success == 0.0:
                        QMessageBox.warning(self, 'No Solution!',
                                            'No solution found! Maybe unbound.\nStatus:'+str(status))
                    else:
                        QMessageBox.warning(self, 'Solution!',
                                            'Maximum yield: '+str(maxyield))
                        # write results into comp_values
                        idx = 0
                        for r in reac_id:
                            val = flux_vec[idx][0]
                            self.appdata.project.comp_values[r] = (
                                float(val), float(val))
                            idx = idx+1
                        self.appdata.project.comp_values_type = 0
                        self.central_widget.update()

            elif self.appdata.is_octave_ready():
                a = self.eng.eval(
                    "[maxyield,flux_vec,success, status]= CNAoptimizeYield(cnap, c, d, fixedFluxes, c_macro, solver, verbose);", nargout=0)

                success = self.eng.pull('success')
                status = self.eng.pull('status')
                maxyield = self.eng.pull('maxyield')
                flux_vec = self.eng.pull('flux_vec')

                if success == 0.0:
                    QMessageBox.warning(self, 'No Solution!',
                                              'No solution found! Maybe unbound.\nStatus:'+str(status))
                else:
                    QMessageBox.warning(self, 'Solution!',
                                        'Maximum yield: '+str(maxyield))

                    # write results into comp_values
                    idx = 0
                    for r in reac_id:
                        val = flux_vec[idx][0]
                        self.appdata.project.comp_values[r] = (
                            float(val), float(val))
                        idx = idx+1
                    self.appdata.project.comp_values_type = 0
                    self.central_widget.update()

        self.setCursor(Qt.ArrowCursor)

The cnapy yield optimization dialog does new completion after Plus '+' A dialog to perform yield optimization # Connecting the signal Return True if text is a valid polynom else False # create CobraModel for matlab # get some data # solver: selects the LP solver # 0: GLPK (glpklp) # 1: Matlab Optimization Toolbox (linprog) # 2: CPLEX (cplexlp) # -1: (default) Either the solver CPLEX or GLPK or MATLAB (linprog) is used # (in this order), depending on availability. # verbose: controls the output printed to the command line # -1: suppress all output, even warnings #  0: no solver output, but warnings and information on final result will be shown #  1: as option '0' but with additional solver output #  (default: 0) # write results into comp_values # write results into comp_values