Пример #1
0
 def init_from_args(cls, args):
     parser = cls._get_arg_parser()
     options, rest_args = parser.parse_known_args(args)
     instance = cls()
     instance.nat_tune_x = options.nat_tune_x
     instance.nat_tune_y = options.nat_tune_y
     if options.acd and options.adt:
         raise AcceleratorDefinitionError(
             "Select only one excitation type.")
     if options.acd:
         instance.excitation = LhcExcitationMode.ACD
     elif options.adt:
         instance.excitation = LhcExcitationMode.ADT
     else:
         instance.excitation = LhcExcitationMode.FREE
     if options.acd or options.adt:
         instance.drv_tune_x = options.drv_tune_x
         instance.drv_tune_y = options.drv_tune_y
     instance.dpp = options.dpp
     instance.energy = options.energy
     instance.optics_file = options.optics
     instance.fullresponse = options.fullresponse
     instance.xing = options.xing
     instance.verify_object()
     return instance, rest_args
Пример #2
0
 def get_sequence_file(cls):
     try:
         return _get_file_for_year(cls.YEAR, "main.seq")
     except AttributeError:
         raise AcceleratorDefinitionError(
             "The accelerator definition is incomplete, mode " +
             "has to be specified (--lhcmode option missing?).")
Пример #3
0
 def load_main_seq_madx(cls):
     try:
         return _get_call_main_for_year(cls.YEAR)
     except AttributeError:
         raise AcceleratorDefinitionError(
             "The accelerator definition is incomplete, mode " +
             "has to be specified (--lhcmode option missing?).")
Пример #4
0
    def init_from_model_dir(cls, model_dir):  # prints only for debugging
        
        print("Creating accelerator instance from model dir")
        instance = cls()
        
        instance.modelpath = model_dir

        if os.path.isfile(model_dir):
            model_dir = os.path.dirname(model_dir)
        instance.model_tfs = tfs_pandas.read_tfs(os.path.join(model_dir, "twiss.dat")).set_index("NAME")
        print("model path =", os.path.join(model_dir, "twiss.dat"))
            
        try:
            model_best_knowledge_path = os.path.join(model_dir, "twiss_best_knowledge.dat")
            if os.path.isfile(model_best_knowledge_path):
                instance.model_best_knowledge = tfs_pandas.read_tfs(model_best_knowledge_path).set_index("NAME")
        except IOError:
            instance.model_best_knowledge = None
            
        elements_path = os.path.join(model_dir, "twiss_elements.dat")
        if os.path.isfile(elements_path):
            instance.elements = tfs_pandas.read_tfs(elements_path).set_index("NAME")
        else:
            raise AcceleratorDefinitionError("Elements twiss not found")
        elements_path = os.path.join(model_dir, "twiss_elements_centre.dat")
        if os.path.isfile(elements_path):
            instance.elements_centre = tfs_pandas.read_tfs(elements_path).set_index("NAME")
        else:
            instance.elements_centre = instance.elements
        
        instance.nat_tune_x = float(instance.model_tfs.headers["Q1"])
        instance.nat_tune_y = float(instance.model_tfs.headers["Q2"])
        
        return instance
Пример #5
0
 def verify_object(self):  # TODO: Maybe more checks?
     try:
         self.get_beam()
     except AttributeError:
         raise AcceleratorDefinitionError(
             "The accelerator definition is incomplete, beam " +
             "has to be specified (--beam option missing?).")
     if self.optics_file is None:
         raise AcceleratorDefinitionError(
             "The accelerator definition is incomplete, optics "
             "file has not been specified.")
     if self.excitation is None:
         raise AcceleratorDefinitionError("Excitation mode not set.")
     if self.xing is None:
         raise AcceleratorDefinitionError("Crossing on or off not set.")
     if (self.excitation == LhcExcitationMode.ACD
             or self.excitation == LhcExcitationMode.ADT):
         if self.drv_tune_x is None or self.drv_tune_y is None:
             raise AcceleratorDefinitionError("Driven tunes not set.")
Пример #6
0
    def verify_object(self):  # TODO: Maybe more checks?
        try:
            self.get_beam()
        except AttributeError:
            raise AcceleratorDefinitionError(
                "The accelerator definition is incomplete, beam "
                "has to be specified (--beam option missing?).")

        if self.model_dir is None:  # is the class is used to create full response?
            if self.optics_file is None:
                raise AcceleratorDefinitionError(
                    "The accelerator definition is incomplete, optics "
                    "file or model directory has not been specified.")
            if self.xing is None:
                raise AcceleratorDefinitionError("Crossing on or off not set.")

        if self.excitation is None:
            raise AcceleratorDefinitionError("Excitation mode not set.")
        if (self.excitation == AccExcitationMode.ACD
                or self.excitation == AccExcitationMode.ADT):
            if self.drv_tune_x is None or self.drv_tune_y is None:
                raise AcceleratorDefinitionError("Driven tunes not set.")

        if self.optics_file is not None and not os.path.exists(
                self.optics_file):
            raise AcceleratorDefinitionError(
                "Optics file '{:s}' does not exist.".format(self.optics_file))
Пример #7
0
 def get_basic_seq_job(self):
     """ Return string for madx job of correting model """
     with open(self.get_basic_seq_tmpl(), "r") as template:
         madx_template = template.read()
     try:
         replace_dict = {
             "LIB": self.MACROS_NAME,
             "MAIN_SEQ": self.load_main_seq_madx(),
             "OPTICS_PATH": self.optics_file,
             "CROSSING_ON": "1" if self.xing else "0",
             "NUM_BEAM": self.get_beam(),
             "DPP": self.dpp,
             "QMX": self.nat_tune_x,
             "QMY": self.nat_tune_y,
         }
     except AttributeError:
         raise AcceleratorDefinitionError(
             "The accelerator definition is incomplete. " +
             "Needs to be an accelator instance. Also: --lhcmode or --beam option missing?"
         )
     return madx_template % replace_dict
Пример #8
0
 def verify_object(self):
     try:
         self.get_beam()
     except AttributeError:
         raise AcceleratorDefinitionError(
             "The accelerator definition is incomplete, beam "
             "has to be specified (--beam option missing?).")
     if self.optics_file is None:
         raise AcceleratorDefinitionError(
             "The accelerator definition is incomplete, optics "
             "file has not been specified.")
     if self.xing is None:
         raise AcceleratorDefinitionError("Crossing on or off not set.")
     if self.label is None:
         raise AcceleratorDefinitionError("Segment label not set.")
     if self.start is None:
         raise AcceleratorDefinitionError("Segment start not set.")
     if self.end is None:
         raise AcceleratorDefinitionError("Segment end not set.")
Пример #9
0
    def get_multi_dpp_job(self, dpp_list):
        """ Return madx job to create twisses (models) with dpps from dpp_list """
        with open(self.get_nominal_multidpp_tmpl()) as textfile:
            madx_template = textfile.read()
        try:
            output_path = self.model_dir
            use_acd = "1" if (self.excitation
                              == AccExcitationMode.ACD) else "0"
            use_adt = "1" if (self.excitation
                              == AccExcitationMode.ADT) else "0"
            crossing_on = "1" if self.xing else "0"
            beam = self.get_beam()

            replace_dict = {
                "LIB": self.MACROS_NAME,
                "MAIN_SEQ": self.load_main_seq_madx(),
                "OPTICS_PATH": self.optics_file,
                "NUM_BEAM": beam,
                "PATH": output_path,
                "QMX": self.nat_tune_x,
                "QMY": self.nat_tune_y,
                "USE_ACD": use_acd,
                "USE_ADT": use_adt,
                "CROSSING_ON": crossing_on,
                "QX": "",
                "QY": "",
                "QDX": "",
                "QDY": "",
                "DPP": "",
                "DPP_ELEMS": "",
                "DPP_AC": "",
                "DPP_ADT": "",
            }
            if (self.excitation
                    in (AccExcitationMode.ACD, AccExcitationMode.ADT)):
                replace_dict["QX"] = self.nat_tune_x
                replace_dict["QY"] = self.nat_tune_y
                replace_dict["QDX"] = self.drv_tune_x
                replace_dict["QDY"] = self.drv_tune_y
        except AttributeError:
            raise AcceleratorDefinitionError(
                "The accelerator definition is incomplete. " +
                "Needs to be an accelator instance. Also: --lhcmode or --beam option missing?"
            )

        # add different dpp twiss-command lines
        twisses_tmpl = "twiss, chrom, sequence=LHCB{beam:d}, deltap={dpp:f}, file='{twiss:s}';\n"
        for dpp in dpp_list:
            replace_dict["DPP"] += twisses_tmpl.format(
                beam=beam,
                dpp=dpp,
                twiss=os.path.join(output_path, "twiss_{:f}.dat".format(dpp)))
            replace_dict["DPP_ELEMS"] += twisses_tmpl.format(
                beam=beam,
                dpp=dpp,
                twiss=os.path.join(output_path,
                                   "twiss_{:f}_elements.dat".format(dpp)))
            replace_dict["DPP_AC"] += twisses_tmpl.format(
                beam=beam,
                dpp=dpp,
                twiss=os.path.join(output_path,
                                   "twiss_{:f}_ac.dat".format(dpp)))
            replace_dict["DPP_ADT"] += twisses_tmpl.format(
                beam=beam,
                dpp=dpp,
                twiss=os.path.join(output_path,
                                   "twiss_{:f}_adt.dat".format(dpp)))
        return madx_template % replace_dict
Пример #10
0
    def init_from_model_dir(self, model_dir):
        LOGGER.debug("Creating accelerator instance from model dir")
        self.model_dir = model_dir

        LOGGER.debug("  model path = " + os.path.join(model_dir, "twiss.dat"))
        try:
            self._model = tfs_pandas.read_tfs(os.path.join(
                model_dir, "twiss.dat"),
                                              index="NAME")
        except IOError:
            self._model = tfs_pandas.read_tfs(os.path.join(
                model_dir, "twiss_elements.dat"),
                                              index="NAME")
            bpm_index = [
                idx for idx in self._model.index.values if idx.startswith("B")
            ]
            self._model = self._model.loc[bpm_index, :]
        self.nat_tune_x = float(self._model.headers["Q1"])
        self.nat_tune_y = float(self._model.headers["Q2"])

        # Excitations #####################################
        self._model_driven = None
        self.drv_tune_x = None
        self.drv_tune_y = None
        self._excitation = AccExcitationMode.FREE

        ac_filename = os.path.join(model_dir, "twiss_ac.dat")
        adt_filename = os.path.join(model_dir, "twiss_adt.dat")

        if os.path.isfile(ac_filename):
            self._model_driven = tfs_pandas.read_tfs(ac_filename, index="NAME")
            self._excitation = AccExcitationMode.ACD

        if os.path.isfile(adt_filename):
            if self._excitation == AccExcitationMode.ACD:
                raise AcceleratorDefinitionError(
                    "ADT as well as ACD models provided."
                    "Please choose only one.")

            self._model_driven = tfs_pandas.read_tfs(adt_filename,
                                                     index="NAME")
            self._excitation = AccExcitationMode.ADT

        if not self._excitation == AccExcitationMode.FREE:
            self.drv_tune_x = float(self.get_driven_tfs().headers["Q1"])
            self.drv_tune_y = float(self.get_driven_tfs().headers["Q2"])

        # Best Knowledge #####################################
        self._model_best_knowledge = None
        best_knowledge_path = os.path.join(model_dir,
                                           "twiss_best_knowledge.dat")
        if os.path.isfile(best_knowledge_path):
            self._model_best_knowledge = tfs_pandas.read_tfs(
                best_knowledge_path, index="NAME")

        # Elements #####################################
        elements_path = os.path.join(model_dir, "twiss_elements.dat")
        if os.path.isfile(elements_path):
            self._elements = tfs_pandas.read_tfs(elements_path, index="NAME")
        else:
            raise AcceleratorDefinitionError("Elements twiss not found")

        center_path = os.path.join(model_dir, "twiss_elements_centre.dat")
        if os.path.isfile(center_path):
            self._elements_centre = tfs_pandas.read_tfs(center_path,
                                                        index="NAME")
        else:
            self._elements_centre = self._elements

        # Optics File #########################################
        self.optics_file = None
        opticsfilepath = os.path.join(self.model_dir, "modifiers.madx")
        if os.path.exists(opticsfilepath):
            self.optics_file = opticsfilepath

        # Error Def #####################################
        self._errordefspath = None
        errordefspath = os.path.join(self.model_dir, "error_deff.txt")
        if os.path.exists(errordefspath):
            self._errordefspath = errordefspath
        else:  # until we have a proper file name convention
            errordefspath = os.path.join(self.model_dir, "error_deffs.txt")
            if os.path.exists(errordefspath):
                self._errordefspath = errordefspath
Пример #11
0
    def __init__(self, *args, **kwargs):
        # for reasons of import-order and class creation, decoration was not possible
        parser = EntryPoint(self.get_instance_parameters(), strict=True)
        opt = parser.parse(*args, **kwargs)

        if opt.model_dir:
            self.init_from_model_dir(opt.model_dir)
            self.energy = None
            self.dpp = 0.0
            self.xing = None
            if opt.nat_tune_x is not None:
                raise AcceleratorDefinitionError(
                    "Argument 'nat_tune_x' not allowed when loading from model directory."
                )
            if opt.nat_tune_y is not None:
                raise AcceleratorDefinitionError(
                    "Argument 'nat_tune_y' not allowed when loading from model directory."
                )
            if opt.drv_tune_x is not None:
                raise AcceleratorDefinitionError(
                    "Argument 'drv_tune_x' not allowed when loading from model directory."
                )
            if opt.drv_tune_y is not None:
                raise AcceleratorDefinitionError(
                    "Argument 'drv_tune_y' not allowed when loading from model directory."
                )
        else:
            if opt.nat_tune_x is None:
                raise AcceleratorDefinitionError(
                    "Argument 'nat_tune_x' is required.")
            if opt.nat_tune_y is None:
                raise AcceleratorDefinitionError(
                    "Argument 'nat_tune_y' is required.")

            self.nat_tune_x = opt.nat_tune_x
            self.nat_tune_y = opt.nat_tune_y

            self.drv_tune_x = None
            self.drv_tune_y = None
            self._excitation = AccExcitationMode.FREE

            if opt.acd or opt.adt:
                if opt.acd and opt.adt:
                    raise AcceleratorDefinitionError(
                        "Select only one excitation type.")

                if opt.drv_tune_x is None:
                    raise AcceleratorDefinitionError(
                        "Argument 'drv_tune_x' is required.")
                if opt.drv_tune_y is None:
                    raise AcceleratorDefinitionError(
                        "Argument 'drv_tune_x' is required.")
                self.drv_tune_x = opt.drv_tune_x
                self.drv_tune_y = opt.drv_tune_y

                if opt.acd:
                    self._excitation = AccExcitationMode.ACD
                elif opt.adt:
                    self._excitation = AccExcitationMode.ADT

            # optional with default
            self.dpp = opt.dpp
            self.fullresponse = opt.fullresponse

            # optional no default
            self.energy = opt.get("energy", None)
            self.xing = opt.get("xing", None)
            self.optics_file = opt.get("optics", None)

            # for GetLLM
            self.model_dir = None
            self._model = None
            self._model_driven = None
            self._model_best_knowledge = None
            self._elements = None
            self._elements_centre = None
            self._errordefspath = None

        self.verify_object()
Пример #12
0
 def verify_object(self):  # TODO: Maybe more checks?
     if self.optics_file is None:
         raise AcceleratorDefinitionError( 
             "The accelerator definition is incomplete, optics "
             "file has not been specified."
         )