transcripty.data package

Submodules

transcripty.data.calibration module

transcripty.data.calibration.CPMobjective(params, target)

Used as objective function in calibrateCPM

Parameters

  • params (np.array((2,), float64)) – An array of the parameters ordered according to CPMParams

  • target (CalibrationTargets) – The calibration targets

Returns

score – The score associated with a particular parameter set

Return type

float64

transcripty.data.calibration.HPMobjective(params, target)

Used as objective function in calibrateHPM

Parameters

  • params (np.array((4,), float64)) – An array of the parameters ordered according to HPMParams

  • target (CalibrationTargets) – The calibration targets

Returns

score – The score associated with a particular parameter set

Return type

float64

transcripty.data.calibration.calibrateCPM(target=<transcripty.data.targets.CalibrationTargets object>, nevals=500)

Searches the parameter space to find the set of parameters that provide the best fit to our calibration targets

Parameters

target (CalibrationTargets) – The calibration targets

Returns

parameters – The parameters found by the optimization algorithm

Return type

dict

transcripty.data.calibration.calibrateHPM(target=<transcripty.data.targets.CalibrationTargets object>, nevals=500)

Searches the parameter space to find the set of parameters that provide the best fit to our calibration targets

Parameters

target (CalibrationTargets) – The calibration targets

Returns

parameters – The parameters found by the optimization algorithm

Return type

dict

transcripty.data.targets module

This file contains the calibration targets that we will use to find the “optimal” parameters for the model

class transcripty.data.targets.CPMParams(p, sigma)

Bases: tuple

property p

Alias for field number 0

property sigma

Alias for field number 1

class transcripty.data.targets.CalibrationTargets(credit_corr, y2_deciles)

Bases: object

This holds the calibration targets used for calibrating the model

Parameters

  • credit_corr (float64) – The correlation between the credits earned in years 1 and 2

  • y2_deciles_by_quartile (np.array((9, 5), float64)) – The 20/50/80 percent quantiles of total credits earned after two years for each gpa quartile

See parameters
compare_results(gpa, credits, corrmult=25.0, normalize=False)

Compares the credit simulation results with the calibration targets

Parameters

  • gpa (np.array((N,), float64)) – A simulation of gpa of N individuals

  • credits (np.array((N, T_c), float64)) – A simulation of credits earned by N individuals over T_c periods

  • corrmult (float64, optional(25.0)) – A multiplier used to scale the importance of the correlation between years 1 and 2

  • normalize (bool, optional(false)) – If normalize is true then computes the percent difference in targets rather than absolute differences

Returns

diff – The ‘score’ of a particular simulation. The higher the score, the less we believe the parameters that generated the score

Return type

float64

class transcripty.data.targets.HPMParams(gamma_min, gamma_1, gamma_2, sigma)

Bases: tuple

property gamma_1

Alias for field number 1

property gamma_2

Alias for field number 2

property gamma_min

Alias for field number 0

property sigma

Alias for field number 3

Module contents