Tuner: Moved tuning logic into the python wrapper - draft of Android tuning app using kivy

python/external/sklearn/_tree.pyx

@@ -23,11 +23,8 @@ from cpython cimport Py_INCREF, PyObject
 import numpy as np
 cimport numpy as np
 np.import_array()
-
 from _tree cimport StackRecord
 
-from scipy.sparse import issparse, csc_matrix, csr_matrix
-
 cdef extern from "numpy/arrayobject.h":
     object PyArray_NewFromDescr(object subtype, np.dtype descr,
                                 int nd, np.npy_intp* dims,
@@ -2063,9 +2060,6 @@ cdef class BaseSparseSplitter(Splitter):
         # Call parent init
         Splitter.init(self, X, y, sample_weight)
 
-        if not isinstance(X, csc_matrix):
-            raise ValueError("X should be in csc format")
-
         cdef SIZE_t* samples = self.samples
         cdef SIZE_t n_samples = self.n_samples
 
@@ -2790,18 +2784,7 @@ cdef class TreeBuilder:
     cdef inline _check_input(self, object X, np.ndarray y,
                              np.ndarray sample_weight):
         """Check input dtype, layout and format"""
-        if issparse(X):
-            X = X.tocsc()
-            X.sort_indices()
-
-            if X.data.dtype != DTYPE:
-                X.data = np.ascontiguousarray(X.data, dtype=DTYPE)
-
-            if X.indices.dtype != np.int32 or X.indptr.dtype != np.int32:
-                raise ValueError("No support for np.int64 index based "
-                                 "sparse matrices")
-
-        elif X.dtype != DTYPE:
+        if X.dtype != DTYPE:
             # since we have to copy we will make it fortran for efficiency
             X = np.asfortranarray(X, dtype=DTYPE)
 
@@ -3430,10 +3413,7 @@ cdef class Tree:
 
     cpdef np.ndarray apply(self, object X):
         """Finds the terminal region (=leaf node) for each sample in X."""
-        if issparse(X):
-            return self._apply_sparse_csr(X)
-        else:
-            return self._apply_dense(X)
+        return self._apply_dense(X)
 
 
     cdef inline np.ndarray _apply_dense(self, object X):
@@ -3482,10 +3462,6 @@ cdef class Tree:
         """Finds the terminal region (=leaf node) for each sample in sparse X.
 
         """
-        # Check input
-        if not isinstance(X, csr_matrix):
-            raise ValueError("X should be in csr_matrix format, got %s"
-                             % type(X))
 
         if X.dtype != DTYPE:
             raise ValueError("X.dtype should be np.float32, got %s" % X.dtype)