# Path: Utilities/jtools.py
# class OutOfOrderException(Exception):
# class AnalysisError(Exception):
# class CycledList(list):
#     def __getitem__(self, key):
# def slurm_id_from_output(sbatch_output):
# def check_slurm_for_job(squeue_output):
# def get_slurm_exit_state(sjobexitmod_output):
# def write_finished_file(f):
# def midpoint(x1, x2):
# def distance(x1, x2):
# def ANobj_times_to_time_window(t):
# def break_path(p, line_length):
# def text_location(xrange, yrange):
# def valid_int_from_str(s):
# def valid_float_from_str(s):
# def complex_mag(z):
# def complex_mag_list(zz):
# def type_verify(var, typ):
# def time_window_to_filelike_str(w):
# def scan_config(f):
# def in_tkStringVar_array(s, tksvarr):
# def valid_probe_array(s, f = DEFAULT_CONFIG_FILE):
# def return_methods():
# def valid_method(s):
# def probe_positions(probe_array):
# def valid_window(s):
# def remove_key(d, k):
# def time_window_parser(s):
# def t_in_window(t, win):
# def window_subset(w1, w2):
# def valid_num_or_range(s):
# def valid_shot_str(s):
# def shot_str_parser(s):
# def reverse_shot_str_parser(shot_list):
# def squareish_grid(n, swapxy=False):
# def find_closest(arr, x):


import os
import copy
import itertools
import pickle
import numpy as np
import pyfusion as pf
import pyfusion.clustering as clust
import pyfusion.clustering.extract_features_scans as ext
        import matplotlib.pyplot as plt
        import matplotlib.pyplot as plt  # These imports are here since this file will be imported into an
        import matplotlib as mpl         # environment where matplotib cannot be imported
        import matplotlib.pyplot as plt
        import matplotlib as mpl
from multiprocessing import Pool
from PyFusionGUI import *
from Utilities import jtools as jt
        from time import strftime
        from time import strftime
            return None, None, None
        feature_object = clust.feature_object(instance_array=instance_array, misc_data_dict=misc_data_dict,
                                              instance_array_amps=+misc_data_dict["mirnov_data"])
        z = feature_object.cluster(**self.DM.datamining_settings)
        return results, feature_object, z

    @classmethod
    def restore(cls, filename):
        if not os.path.exists(filename):
            raise OSError("File ({}) does not exist!".format(filename))
        with open(filename, "rb") as pick:
            data = pickle.load(pick)
        return cls(_from_pickle=True, _pickle_data=data)

    def save(self, filename=None):
        # Saves the current instance variables as a pickled object to "filename".
        # Since there are several different data structures within an analysis object,
        # they will be compressed into a single dictionary object and then pickled.
        time_string = strftime("%d-%m-%Y--%H-%M-%S")
        if filename is None:
            local_filename = "PyFusionGUI_from_{}".format(time_string)
            filename = os.path.join(IRIS_CSCRATCH_DIR, local_filename)
        with open(filename, "wb") as pick:
            pickle.dump({"self": {"results": self.results,
                                  "feature_object": self.feature_object,
                                  "z": self.z}, "DM": self.DM.__dict__}, pick)
        return

    def show_plots(self):
        self.return_specgrams()

# Path: Utilities/jtools.py
# class OutOfOrderException(Exception):
# class AnalysisError(Exception):
# class CycledList(list):
#     def __getitem__(self, key):
# def slurm_id_from_output(sbatch_output):
# def check_slurm_for_job(squeue_output):
# def get_slurm_exit_state(sjobexitmod_output):
# def write_finished_file(f):
# def midpoint(x1, x2):
# def distance(x1, x2):
# def ANobj_times_to_time_window(t):
# def break_path(p, line_length):
# def text_location(xrange, yrange):
# def valid_int_from_str(s):
# def valid_float_from_str(s):
# def complex_mag(z):
# def complex_mag_list(zz):
# def type_verify(var, typ):
# def time_window_to_filelike_str(w):
# def scan_config(f):
# def in_tkStringVar_array(s, tksvarr):
# def valid_probe_array(s, f = DEFAULT_CONFIG_FILE):
# def return_methods():
# def valid_method(s):
# def probe_positions(probe_array):
# def valid_window(s):
# def remove_key(d, k):
# def time_window_parser(s):
# def t_in_window(t, win):
# def window_subset(w1, w2):
# def valid_num_or_range(s):
# def valid_shot_str(s):
# def shot_str_parser(s):
# def reverse_shot_str_parser(shot_list):
# def squareish_grid(n, swapxy=False):
# def find_closest(arr, x):


# Path: Analysis/analysis.py
import os
import copy
import itertools
import pickle
import numpy as np
import pyfusion as pf
import pyfusion.clustering as clust
import pyfusion.clustering.extract_features_scans as ext
        import matplotlib.pyplot as plt
        import matplotlib.pyplot as plt  # These imports are here since this file will be imported into an
        import matplotlib as mpl         # environment where matplotib cannot be imported
        import matplotlib.pyplot as plt
        import matplotlib as mpl
from multiprocessing import Pool
from PyFusionGUI import *
from Utilities import jtools as jt
        from time import strftime
        from time import strftime

            return None, None, None
        feature_object = clust.feature_object(instance_array=instance_array, misc_data_dict=misc_data_dict,
                                              instance_array_amps=+misc_data_dict["mirnov_data"])
        z = feature_object.cluster(**self.DM.datamining_settings)
        return results, feature_object, z

    @classmethod
    def restore(cls, filename):
        if not os.path.exists(filename):
            raise OSError("File ({}) does not exist!".format(filename))
        with open(filename, "rb") as pick:
            data = pickle.load(pick)
        return cls(_from_pickle=True, _pickle_data=data)

    def save(self, filename=None):
        # Saves the current instance variables as a pickled object to "filename".
        # Since there are several different data structures within an analysis object,
        # they will be compressed into a single dictionary object and then pickled.
        time_string = strftime("%d-%m-%Y--%H-%M-%S")
        if filename is None:
            local_filename = "PyFusionGUI_from_{}".format(time_string)
            filename = os.path.join(IRIS_CSCRATCH_DIR, local_filename)
        with open(filename, "wb") as pick:
            pickle.dump({"self": {"results": self.results,
                                  "feature_object": self.feature_object,
                                  "z": self.z}, "DM": self.DM.__dict__}, pick)
        return

    def show_plots(self):
        self.return_specgrams()

        plt.show()