MicEMD.tdem package¶
Submodules¶
MicEMD.tdem.classification module¶
The classification class in TDEM
Class: - classification: the implement class of the BaseTDEMSimulation
Methods: - simulate: the interface of the simulation in TDEM
- class MicEMD.tdem.classification.Classification(data, method, cls_para, *args, **kwargs)¶
Bases:
MicEMD.tdem.classification.BaseTDEMClassificationthe class of the classification algorithm
- data: tuple
conclude the train set and the test set
- method: str
the method of classification
- cls_para: dict
the Parameters for the classification algorithm
run: run the the classification algorithm and return the result
error: return the res of the classification
- property error¶
- run()¶
- MicEMD.tdem.classification.classify(data_set, cls_method, cls_para=None, *args, **kwargs)¶
the interface of the classification of the target
- data_set: tuple
conclude the train set and the test set
- cls_method: str
the method of classification
- cls_para: dict
the Parameters for the classification algorithm
- res: dict
keys: [‘accuracy’, ‘y_pred’, ‘y_true’], represent the accuracy , predict value and true value of the classification
MicEMD.tdem.collection module¶
The Collection class, conclude the parameters about collecting in underground detection system
Class: - Collection: the class conclude the parameters about collecting in TDEM
- class MicEMD.tdem.collection.Collection(t_split, snr, **kwargs)¶
Bases:
objectthe class conclude the parameters about collecting
- t_split: int
the sampled times of the response every second
- SNR: int
the Signal to Noise Ratio
MicEMD.tdem.detector module¶
The detector class, represent the detector in TDEM
Class: - Detector: the detector class in TDEM
- class MicEMD.tdem.detector.Detector(radius, current, pitch, roll)¶
Bases:
objectthe detector in TDEM
- radius: float
the radius of the detector
- current: float
the current of the detector
- pitch: float
the pitch angle of the target
- roll: float
the roll angle of the target
- mag_moment
Returns the magnetic moment value of transmitter coil
- property mag_moment¶
Calculate magnetic moment value of transmitter coil according to detector parameters.
- TYPEfloat
The value of magnetic moment of z axis.
MicEMD.tdem.model module¶
The model class, represent the model in TDEM
Class: - Model: the implement class of the BaseTDEMModel
- class MicEMD.tdem.model.Model(Survey)¶
Bases:
MicEMD.tdem.model.BaseTDEMModel- dpred()¶
product the forward data
- feature_lablendarry
shape(n,402), n represent the number of simulation feature_lable include material_flag, shape_flag and the response
- sample: dict
represent a sample,it’s to show the data one of the collection key = [‘data’, ‘M1’, ‘M2’, ‘M1_without_noise’, ‘M2_without_noise’, ‘t’, ‘SNR’, ‘material’, ‘ta’, ‘tb’]
- ellipsoid_k_plus(ta, tb, c)¶
- ellipsoid_parameter(c, c0, d, ta, tb)¶
- func(t, k, a, b, R)¶
calculate the response of the sphere and return it
- parameter_sphere(c, c0, d, r)¶
use less para to fit the sphere response To reduce the computational complexity of the charac- teristic response, a simple empirical function defined by a minimum number of parameters is utilized to replicate the features of the characteristic response
- c: float
the relative permeability of the target
- c0: float
the permeability of vacuum
- d: float
the conductivity of the target
- r: float
the radius of the target
k, a, b, R: the tuple of the fitting parameters
- 1
J. T. Smith, H. F. Morrison, and A. Becker, “Parametric forms and the inductive response of a permeable conducting sphere,” Journal of Envi- ronmental & Engineering Geophysics, vol. 9, no. 4, pp. 213–216, 2004.
- wgn_one_npower(x, snr)¶
add the noise to the date
MicEMD.tdem.preprocessing module¶
preprocess the response data in TDEM
Methods: - preprocess: the interface of the preprocessor in TDEM
- MicEMD.tdem.preprocessing.preprocess(response, dim_red_method=None)¶
The data were dimensionalized
- response: ndarry
the received response
- dim_red_method: str
the method of the dimensionality reduction
- res: tuple
the train set and test set of after dimensionality reduction for example: res[0] represent the train set after dimensionality reduction res[1] represent the test set after dimensionality reduction
MicEMD.tdem.results module¶
MicEMD.tdem.simulation module¶
The simulation in TDEM
Class: - Simulation: the implement class of the BaseTDEMSimulation
Methods: - simulate: the interface of the simulation in TDEM
- class MicEMD.tdem.simulation.Simulation(model)¶
Bases:
MicEMD.tdem.simulation.BaseTDEMSimulation- pred()¶
- MicEMD.tdem.simulation.simulate(target, detector, collection, model='dipole', *args, **kwargs)¶
the interface of the simulation
- target: class
the target of the TDEM
- detector: class
the detector of the TDEM
- collection: class
the collection of the TDEM
- model: str
the name of the model
- res: tuple
the result of the method dpred in model class
MicEMD.tdem.source module¶
The Source class, represent the source in TDEM
Class: - Source: implement class of the BaseTDEMSource in TDEM
MicEMD.tdem.survey module¶
The survey class, represent the survey in TDEM
Class: - Survey: the implement class of the BaseTDEMSurvey
MicEMD.tdem.target module¶
The target class, represent the target in underground detection
Class: - Target: the target class in TDEM
- class MicEMD.tdem.target.Target(material, shape, attribute, ta_min, ta_max, tb_min, tb_max, a_r_step, b_r_step, **kwargs)¶
Bases:
objectRefer in particular to spheroid targets.
- material: list
the list of material of the target
- shape: list
the list of shape of the target
- attribute: 2D-ndarray
the relative permeability, permeability of vacuum and conductivity of the target
- ta_minfloat
represent the min radial radius of the spheroid targets
- ta_maxfloat
represent the max radial radius of the spheroid targets
- tb_minfloat
represent the min axial radius of the spheroid targets
- tb_maxfloat
represent the max axial radius of the spheroid targets
- a_r_step: float
represent the changed step of radial radius
- b_r_step: float
represent the changed step of axial radius