def score(self, X=None, y=None, K0_whole_test=None, K1_whole_test=None, iid_if_none=None, return_mse_too=False, count_A1=None):
    '\n        Method for calculating the negative log likelihood of testing examples.\n        If the examples in X,y,  K0_whole_test, K1_whole_test are not the same, they will be reordered and intersected.\n\n        :param X: testing covariate information, optional: \n          If you give a string, it should be the file name of a PLINK phenotype-formatted file.\n        :type X: a PySnpTools `SnpReader <http://fastlmm.github.io/PySnpTools/#snpreader-snpreader>`__ (such as `Pheno <http://fastlmm.github.io/PySnpTools/#snpreader-pheno>`__ or `SnpData <http://fastlmm.github.io/PySnpTools/#snpreader-snpdata>`__) or string.\n\n        :param y: testing phenotype:\n          If you give a string, it should be the file name of a PLINK phenotype-formatted file.\n        :type y: a PySnpTools `SnpReader <http://fastlmm.github.io/PySnpTools/#snpreader-snpreader>`__ (such as `Pheno <http://fastlmm.github.io/PySnpTools/#snpreader-pheno>`__ or `SnpData <http://fastlmm.github.io/PySnpTools/#snpreader-snpdata>`__) or string.\n\n        :param K0_whole_test: Must be None. Represents the identity similarity matrix.\n        :type K0_whole_test: None\n\n        :param K1_whole_test: Must be None. Represents the identity similarity matrix.\n        :type K1_whole_test: `SnpReader <http://fastlmm.github.io/PySnpTools/#snpreader-snpreader>`__ or a string or `KernelReader <http://fastlmm.github.io/PySnpTools/#kernelreader-kernelreader>`__\n\n        :param iid_if_none: Examples to predict for if no X, K0_whole_test, K1_whole_test is provided.\n        :type iid_if_none: an ndarray of two strings\n\n        :param return_mse_too: If true, will also return the mean squared error.\n        :type return_mse_too: bool\n\n        :param count_A1: If it needs to read SNP data from a BED-formatted file, tells if it should count the number of A1\n             alleles (the PLINK standard) or the number of A2 alleles. False is the current default, but in the future the default will change to True.\n        :type count_A1: bool\n\n        :rtype: a float of the negative log likelihood and, optionally, a float of the mean squared error.\n        '
    (mean0, covar0) = self.predict(K0_whole_test=K0_whole_test, K1_whole_test=K1_whole_test, X=X, iid_if_none=iid_if_none, count_A1=count_A1)
    y = _pheno_fixup(y, iid_if_none=covar0.iid, count_A1=count_A1)
    (mean, covar, y) = intersect_apply([mean0, covar0, y])
    var = multivariate_normal(mean=mean.read(order='A', view_ok=True).val.reshape((- 1)), cov=covar.read(order='A', view_ok=True).val)
    y_actual = y.read().val
    nll = (- np.log(var.pdf(y_actual.reshape((- 1)))))
    if (not return_mse_too):
        return nll
    else:
        mse = ((y_actual - mean) ** 2).sum()
        return (nll, mse)
Method for calculating the negative log likelihood of testing examples.
If the examples in X,y,  K0_whole_test, K1_whole_test are not the same, they will be reordered and intersected.

:param X: testing covariate information, optional: 
  If you give a string, it should be the file name of a PLINK phenotype-formatted file.
:type X: a PySnpTools `SnpReader <http://fastlmm.github.io/PySnpTools/#snpreader-snpreader>`__ (such as `Pheno <http://fastlmm.github.io/PySnpTools/#snpreader-pheno>`__ or `SnpData <http://fastlmm.github.io/PySnpTools/#snpreader-snpdata>`__) or string.

:param y: testing phenotype:
  If you give a string, it should be the file name of a PLINK phenotype-formatted file.
:type y: a PySnpTools `SnpReader <http://fastlmm.github.io/PySnpTools/#snpreader-snpreader>`__ (such as `Pheno <http://fastlmm.github.io/PySnpTools/#snpreader-pheno>`__ or `SnpData <http://fastlmm.github.io/PySnpTools/#snpreader-snpdata>`__) or string.

:param K0_whole_test: Must be None. Represents the identity similarity matrix.
:type K0_whole_test: None

:param K1_whole_test: Must be None. Represents the identity similarity matrix.
:type K1_whole_test: `SnpReader <http://fastlmm.github.io/PySnpTools/#snpreader-snpreader>`__ or a string or `KernelReader <http://fastlmm.github.io/PySnpTools/#kernelreader-kernelreader>`__

:param iid_if_none: Examples to predict for if no X, K0_whole_test, K1_whole_test is provided.
:type iid_if_none: an ndarray of two strings

:param return_mse_too: If true, will also return the mean squared error.
:type return_mse_too: bool

:param count_A1: If it needs to read SNP data from a BED-formatted file, tells if it should count the number of A1
     alleles (the PLINK standard) or the number of A2 alleles. False is the current default, but in the future the default will change to True.
:type count_A1: bool

:rtype: a float of the negative log likelihood and, optionally, a float of the mean squared error.
def score(self, X=None, y=None, K0_whole_test=None, K1_whole_test=None, iid_if_none=None, return_mse_too=False, count_A1=None):
    '\n        Method for calculating the negative log likelihood of testing examples.\n        If the examples in X,y,  K0_whole_test, K1_whole_test are not the same, they will be reordered and intersected.\n\n        :param X: testing covariate information, optional: \n          If you give a string, it should be the file name of a PLINK phenotype-formatted file.\n        :type X: a PySnpTools `SnpReader <http://fastlmm.github.io/PySnpTools/#snpreader-snpreader>`__ (such as `Pheno <http://fastlmm.github.io/PySnpTools/#snpreader-pheno>`__ or `SnpData <http://fastlmm.github.io/PySnpTools/#snpreader-snpdata>`__) or string.\n\n        :param y: testing phenotype:\n          If you give a string, it should be the file name of a PLINK phenotype-formatted file.\n        :type y: a PySnpTools `SnpReader <http://fastlmm.github.io/PySnpTools/#snpreader-snpreader>`__ (such as `Pheno <http://fastlmm.github.io/PySnpTools/#snpreader-pheno>`__ or `SnpData <http://fastlmm.github.io/PySnpTools/#snpreader-snpdata>`__) or string.\n\n        :param K0_whole_test: Must be None. Represents the identity similarity matrix.\n        :type K0_whole_test: None\n\n        :param K1_whole_test: Must be None. Represents the identity similarity matrix.\n        :type K1_whole_test: `SnpReader <http://fastlmm.github.io/PySnpTools/#snpreader-snpreader>`__ or a string or `KernelReader <http://fastlmm.github.io/PySnpTools/#kernelreader-kernelreader>`__\n\n        :param iid_if_none: Examples to predict for if no X, K0_whole_test, K1_whole_test is provided.\n        :type iid_if_none: an ndarray of two strings\n\n        :param return_mse_too: If true, will also return the mean squared error.\n        :type return_mse_too: bool\n\n        :param count_A1: If it needs to read SNP data from a BED-formatted file, tells if it should count the number of A1\n             alleles (the PLINK standard) or the number of A2 alleles. False is the current default, but in the future the default will change to True.\n        :type count_A1: bool\n\n        :rtype: a float of the negative log likelihood and, optionally, a float of the mean squared error.\n        '
    (mean0, covar0) = self.predict(K0_whole_test=K0_whole_test, K1_whole_test=K1_whole_test, X=X, iid_if_none=iid_if_none, count_A1=count_A1)
    y = _pheno_fixup(y, iid_if_none=covar0.iid, count_A1=count_A1)
    (mean, covar, y) = intersect_apply([mean0, covar0, y])
    var = multivariate_normal(mean=mean.read(order='A', view_ok=True).val.reshape((- 1)), cov=covar.read(order='A', view_ok=True).val)
    y_actual = y.read().val
    nll = (- np.log(var.pdf(y_actual.reshape((- 1)))))
    if (not return_mse_too):
        return nll
    else:
        mse = ((y_actual - mean) ** 2).sum()
        return (nll, mse)