intermediate commit towards xarray depreceation

Author: davidsebfischer

diffxpy/api/utils.py

@@ -1,4 +1,4 @@
 from diffxpy.testing.utils import constraint_matrix_from_string, constraint_matrix_from_dict, \
     constraint_system_from_star
-from diffxpy.testing.utils import design_matrix, design_matrix_from_xarray, design_matrix_from_anndata
+from diffxpy.testing.utils import design_matrix
 from diffxpy.testing.utils import view_coef_names, preview_coef_names

diffxpy/models/batch_bfgs/optim.py

@@ -16,17 +16,17 @@
 class Estim_BFGS_Model():
 
     def __init__(self, Estim_BFGS, nproc):
-        self._num_observations = Estim_BFGS.X.shape[0]
-        self._num_features = Estim_BFGS.X.shape[1]
+        self._num_observations = Estim_BFGS.x.shape[0]
+        self._num_features = Estim_BFGS.x.shape[1]
         self._features = Estim_BFGS.feature_names
-        self._observations = Estim_BFGS.X.shape[0]
+        self._observations = Estim_BFGS.x.shape[0]
         self._design_loc = Estim_BFGS.design_loc
         self._design_scale = Estim_BFGS.design_scale
         self._loss = xr.DataArray(Estim_BFGS.full_loss(nproc))
         self._log_probs = -self._loss
         self._probs = np.exp(self._log_probs)
         self._mles = xr.DataArray(np.transpose(Estim_BFGS.mles()))
-        self._gradient = xr.DataArray(np.zeros([Estim_BFGS.X.shape[1]]))
+        self._gradient = xr.DataArray(np.zeros([Estim_BFGS.x.shape[1]]))
         self._fisher_inv = xr.DataArray(Estim_BFGS.fisher_inv)
         self._idx_loc = np.arange(0, Estim_BFGS.design_loc.shape[1])
         self._idx_scale = np.arange(Estim_BFGS.design_loc.shape[1],

diffxpy/stats/stats.py

@@ -3,7 +3,6 @@
 import numpy as np
 import numpy.linalg
 import scipy.stats
-import xarray as xr
 
 
 def likelihood_ratio_test(
@@ -264,8 +263,6 @@ def wald_test_chisq(
 
     theta_diff = theta_mle - theta0
     # Convert to nd.array to avoid gufunc error.
-    if isinstance(theta_diff, xr.DataArray):
-        theta_diff = theta_diff.values
     wald_statistic = np.array([
         np.matmul(
             np.matmul(