Update readme

README.md

@@ -64,6 +64,18 @@ It will return a dense array X.
 `cast=True` will convert data to compatible floats by making an internal copy if necessary.
 It will also convert a CSC matrix to a CSR matrix if necessary.
 
+#### PARDISO
+`pardisoinit(mtype, pt=None, iparm=None, single_precision=None,zero_indexing=True)`
+`pardiso(A, B, pt, mtype, iparm, phase=13, maxfct=1, mnum=1, perm=None, msglvl=0, X=None, quiet=False)`
+
+Wrapper for MKL pardiso solver and the pardisoinit function which initializes `pt` and `iparm`.
+This is a direct solver for real or complex systems of linear equations (AX = B) where `A`
+is a sparse CSR matrix and `B` is a dense matrix with one or more right-hand sides.
+It will return a dense array X.
+
+Refer to the pardiso documentation for detailed description of options.
+Consider this wrapper to be experimental.
+
 #### gram_matrix_mkl
 `gram_matrix_mkl(matrix, transpose=False, cast=False, dense=False, debug=False, reorder_output=False)`
 

sparse_dot_mkl/solvers/__init__.py

@@ -35,7 +35,7 @@ def pardiso(
     pt,
     mtype,
     iparm,
-    phase,
+    phase=13,
     maxfct=1,
     mnum=1,
     perm=None,
@@ -65,7 +65,8 @@ def pardiso(
     :type mtype: int
     :param iparm: Solver parameters array, shape=(64,)
     :type iparm: np.ndarray
-    :param phase: Solver phase
+    :param phase: Solver phase, defaults to 13
+        (Analysis, numerical factorization, solve, iterative refinement)
     :type phase: int
     :param maxfct: Pardiso maxfct, defaults to 1
     :type maxfct: int, optional