Example #1
0
 def setupClass(cls):
     cls.decimal_density = 2 # low accuracy because binning is different
     res1 = KDE(Xi)
     res1.fit(kernel="gau", fft=True, bw="silverman")
     cls.res1 = res1
     rfname2 = os.path.join(curdir,'results','results_kde_fft.csv')
     cls.res_density = np.genfromtxt(open(rfname2, 'rb'))
Example #2
0
 def setupClass(cls):
     cls.decimal_density = 2  # low accuracy because binning is different
     res1 = KDE(Xi)
     res1.fit(kernel="gau", fft=True, bw="silverman")
     cls.res1 = res1
     rfname2 = os.path.join(curdir, 'results', 'results_kde_fft.csv')
     cls.res_density = np.genfromtxt(open(rfname2, 'rb'))
Example #3
0
 def setupClass(cls):
     res1 = KDE(Xi)
     weights = np.linspace(1,100,200)
     res1.fit(kernel="gau", gridsize=50, weights=weights, fft=False,
                 bw="silverman")
     cls.res1 = res1
     rfname = os.path.join(curdir,'results','results_kde_weights.csv')
     cls.res_density = np.genfromtxt(open(rfname, 'rb'), skip_header=1)
Example #4
0
 def setupClass(cls):
     res1 = KDE(Xi)
     weights = np.linspace(1, 100, 200)
     res1.fit(kernel="gau",
              gridsize=50,
              weights=weights,
              fft=False,
              bw="silverman")
     cls.res1 = res1
     rfname = os.path.join(curdir, 'results', 'results_kde_weights.csv')
     cls.res_density = np.genfromtxt(open(rfname, 'rb'), skip_header=1)
Example #5
0
 def setupClass(cls):
     res1 = KDE(Xi)
     res1.fit(kernel="biw", fft=False, bw="silverman")
     cls.res1 = res1
     cls.res_density = KDEResults["biw_d"]
Example #6
0
 def setupClass(cls):
     res1 = KDE(Xi)
     res1.fit(kernel="biw", fft=False, bw="silverman")
     cls.res1 = res1
     cls.res_density = KDEResults["biw_d"]