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I'm gonna overwrite a lot of this notebook's old content. I changed the way I'm calculating wt, and wanna test that my training worked.



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from pearce.emulator import OriginalRecipe, ExtraCrispy
from pearce.mocks import cat_dict
import numpy as np
from os import path



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import matplotlib
#matplotlib.use('Agg')
from matplotlib import pyplot as plt
%matplotlib inline
import seaborn as sns
sns.set()



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training_file = '/u/ki/swmclau2/des/PearceRedMagicWpCosmo.hdf5'

em_method = 'rf'
#split_method = 'random'



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a = 1.0
z = 1.0/a - 1.0



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fixed_params = {'z':z}#, 'r':0.18477483}

n_leaves, n_overlap = 500, 1 emu = ExtraCrispy(training_file, n_leaves, n_overlap, split_method, method = em_method, fixed_params=fixed_params)



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emu.valid_methods









    



---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-6-b88b8db39f1c> in <module>()
----> 1 emu.valid_methods

NameError: name 'emu' is not defined



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emu = OriginalRecipe(training_file,method = em_method, fixed_params=fixed_params,
                    hyperparams = {'n_estimators':500, 'max_depth':5}, custom_mean_function = 'linear')



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emu._emulator.score(emu.x, emu.y)

np.abs(emu._emulator.coef_)



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for name, imp in sorted(zip(emu.get_param_names(), emu._emulator.feature_importances_), key = lambda x: x[1], reverse = True):
    print name, imp



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emu.scale_bin_centers



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emu.get_param_names()



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emu.scale_bin_centers



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emu._ordered_params



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params = {'ombh2': 0.021,
             'omch2': 0.12,
             'w0': -1,
             'ns': 0.9578462,
             'ln10As': 3.08,
             'H0': 68.1,
             'Neff': 3.04,
             'logM1': 14.0,
             'logMmin': 11.9,
             'f_c': 0.3,
             'logM0': 13.2,
             'sigma_logM': 0.12,
             'alpha':1.1}

params = {'ombh2': 0.021, 'omch2': 0.12, 'w0': -1, 'ns': 0.9578462, 'ln10As': 3.08, 'H0': 68.1, 'Neff': 3.04}

params = {'logM1': 14.0, 'logMmin': 11.9, 'f_c': 0.2, 'logM0': 13.2, 'sigma_logM': 0.12, 'alpha':1.1}



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wp = emu.emulate_wrt_r(params, emu.scale_bin_centers)[0]



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wp

plt.plot(emu.scale_bin_centers, wp) plt.xscale('log') plt.xlabel(r'$r$ [Mpc]') plt.ylabel(r'$w_p(r_p)$') plt.show()



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idx = 12
binlen = len(emu.scale_bin_centers)

params = {pname: p for pname, p in zip(emu.get_param_names(), emu._x_std[:-1]*emu.x[idx*binlen, :-1] + emu._x_mean[:-1])}



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print params



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emu._y_std, emu._y_mean



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wp = emu.emulate_wrt_r(params,emu.scale_bin_centers)[0]



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wp



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plt.plot(emu.scale_bin_centers, wp, label = 'Emu')
plt.plot(emu.scale_bin_centers, emu._y_std*emu.y[idx*binlen:(idx+1)*binlen]+emu._y_mean, label = 'Truth')
#plt.plot(emu.x[idx*binlen:(idx+1)*binlen, -1], lm_pred)
plt.xscale('log')
plt.xlabel(r'$r$ [Mpc]')
plt.ylabel(r'$w_p(r_p)$')
plt.legend(loc = 'best')
plt.show()



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