class_docstr: A Numba `Type` modeled after the base class `scipy.sparse.compressed._cs_matrix`.
class_docstr_tok: ["A","Numba","`","Type","`","modeled","after","the","base","class","`","scipy.sparse.compressed._cs_matrix","`","."]
code: def __init__(self, dtype):
      self.dtype = dtype
      self.data = types.Array(dtype, 1, "A")
      self.indices = types.Array(types.int32, 1, "A")
      self.indptr = types.Array(types.int32, 1, "A")
      self.shape = types.UniTuple(types.int64, 2)
      super().__init__(self.name)
  
imports: import numpy
  import scipy
  import scipy.sparse
  from numba.core import cgutils, types
  from numba.core.imputils import impl_ret_borrowed
  from numba.extending import NativeValue, box, intrinsic, make_attribute_wrapper, models, overload, overload_attribute, overload_method, register_model, typeof_impl, unbox
label_desc: Use image node_id 2 to create a new CSMatrixType object from inherited base classes: types with example: obj = CSMatrixType(dtype)