Visualize your predictions

How to get animation for your test prediction

For Powerspectrum:

from EmuPBk.visualize import Animate_Pk

animation = Animate_Pk(test_data,test_params,k,load_model,rescale)

 '''
 test_data : test_data(powerspectum), array(N*k)
 test_params : test_parameters of EoR, array(N*m), for m parameters used
 k : array contains k-bin values
 load_model: load_your own model from a directory path,(give a path to the model)
 rescale: the rescaling you did during your model training, default is no rescaling =1

 :return a comparision plot animation between real test_data and predicted data.

 '''

 animation.get_animation_Pk()

# This wiil create .gif at present working directory.
Example of Real vs. ANN prediction by one of our existing ANN model.

Bispectrum:

For Unique (k2/k1 vs Cos(α)) parameter space:

from EmuPBk.visualize import Animate_Bk

animation = Animate_Bk(test_data,test_params,load_model,xHI,
                     k1,cos_min,cos_max, cos_step,
                     k2byk1_min,k2byk1_max,k2byk1_step,rescale)

     '''
     It will give the animation of real bispectrum vs ANN predictions for only Unique triangle space configuration.
     test_data : test_data(Bispectrum), array type
     test_params : test_parameters of EoR , array type
     load_model: load_your own model from a directory path, (give/path/to/model)
     xHI: neutral fraction (if, any)
     k1: provide the value of k1,
     cosalpha: provide cos_min and cos_max and its step, default: (min,max,step)=>(0.50,0.99,0.01)
     k2byk1: provide the range of k2byk1 and its step, default: (min,max,step)=>(0.50,1.00,0.05)
     rescale: default 1
     :return a comparision plot animation between real test_data and predicted data.
     '''

animation.get_animation_Bk()
# It will save .gif animation at pwd.
Example of Real vs. ANN prediction by one of our existing ANN model.

For different k2/k1 ratios:

animation.get_Bk_vs_cos()
At individual k2/k1 ratio,(figure generated using our existing model)