Class: Numo::NArray

Inherits:
Object
  • Object
show all
Defined in:
ext/numo/narray/narray.c,
lib/numo/narray.rb,
lib/numo/narray/extra.rb,
ext/numo/narray/narray.c

Overview

Numo::NArray is the abstract super class for Numerical N-dimensional Array in the Ruby/Numo module. Use Typed Subclasses of NArray (Numo::DFloat, Int32, etc) to create data array instances.

Defined Under Namespace

Classes: CastError, DimensionError, OperationError, ShapeError, ValueError

Constant Summary collapse

ALTERNATIVE =

Constant to indicate whether it is numo-narray-alt.

true
VERSION =

:NArray Alternative.

The version of Numo
@@warn_slow_dot = 
false

Class Method Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(args) ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 359

static VALUE na_initialize(VALUE self, VALUE args) {
  VALUE v;
  size_t* shape = NULL;
  int ndim;

  if (RARRAY_LEN(args) == 1) {
    v = RARRAY_AREF(args, 0);
    if (TYPE(v) != T_ARRAY) {
      v = args;
    }
  } else {
    v = args;
  }
  ndim = (int)RARRAY_LEN(v);
  if (ndim > NA_MAX_DIMENSION) {
    rb_raise(rb_eArgError, "ndim=%d exceeds maximum dimension", ndim);
  }
  shape = ALLOCA_N(size_t, ndim);
  // setup size_t shape[] from VALUE shape argument
  na_array_to_internal_shape(self, v, shape);
  na_setup(self, ndim, shape);

  return self;
}

Class Method Details

.[](ary) ⇒ Object 



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# File 'ext/numo/narray/array.c', line 444

static VALUE nary_s_bracket(VALUE klass, VALUE ary) {
  VALUE dtype = Qnil;

  if (TYPE(ary) != T_ARRAY) {
    rb_bug("Argument is not array");
  }
  dtype = na_ary_composition_dtype(ary);
  check_subclass_of_narray(dtype);
  return rb_funcall(dtype, id_cast, 1, ary);
}

.alternative? ⇒ Boolean

Returns true if this is numo-narray-alt.

Returns:

  • (Boolean) 


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# File 'lib/numo/narray.rb', line 15

def self.alternative?
  ALTERNATIVE
end

.array_type(ary) ⇒ Class

return type of NArray which would be created from given Array.

Examples:

Numo::NArray.array_type([1, 2, 3])
# => Numo::Int32
Numo::NArray.array_type([0, 1, 2i])
# => Numo::DComplex
Numo::NArray.array_type(Numo::DFloat[1, 2, 3])
# => Numo::DFloat

Returns NArray class.

Parameters:

  • ary (Array)

Returns:

  • (Class) —

    NArray class



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# File 'ext/numo/narray/array.c', line 434

static VALUE na_s_array_type(VALUE mod, VALUE ary) {
  return na_ary_composition_dtype(ary);
}

.asarray(a) ⇒ Object

Convert the argument to an narray.



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# File 'lib/numo/narray/extra.rb', line 118

def self.asarray(a)
  case a
  when NArray
    a.ndim == 0 ? a[:new] : a
  when Numeric, Range
    self[a]
  else
    cast(a)
  end
end

.byte_size ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1231

static VALUE nary_s_byte_size(VALUE type) {
  return rb_const_get(type, id_element_byte_size);
}

.cast(a) ⇒ Object

Convert the argument to an narray if not an narray.



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# File 'lib/numo/narray/extra.rb', line 103

def self.cast(a)
  case a
  when NArray
    a
  when Array, Numeric
    NArray.array_type(a).cast(a)
  else
    raise TypeError, 'invalid type for NArray' unless a.respond_to?(:to_a)

    a = a.to_a
    NArray.array_type(a).cast(a)
  end
end

.column_stack(arrays) ⇒ Object

Stack 1-d arrays into columns of a 2-d array.

Examples:

x = Numo::Int32[1,2,3]
y = Numo::Int32[2,3,4]
Numo::NArray.column_stack([x,y])
# => Numo::Int32#shape=[3,2]
# [[1, 2],
#  [2, 3],
#  [3, 4]]


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# File 'lib/numo/narray/extra.rb', line 593

def column_stack(arrays)
  arys = arrays.map do |a|
    a = cast(a)
    case a.ndim
    when 0 then a[:new, :new]
    when 1 then a[true, :new]
    else; a
    end
  end
  concatenate(arys, axis: 1)
end

.concatenate(arrays, axis: 0) ⇒ Object

Examples:

a = Numo::DFloat[[1, 2], [3, 4]]
# => Numo::DFloat#shape=[2,2]
# [[1, 2],
#  [3, 4]]

b = Numo::DFloat[[5, 6]]
# => Numo::DFloat#shape=[1,2]
# [[5, 6]]

Numo::NArray.concatenate([a,b],axis:0)
# => Numo::DFloat#shape=[3,2]
# [[1, 2],
#  [3, 4],
#  [5, 6]]

Numo::NArray.concatenate([a,b.transpose], axis:1)
# => Numo::DFloat#shape=[2,3]
# [[1, 2, 5],
#  [3, 4, 6]]

Raises:

  • (ArgumentError) 


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# File 'lib/numo/narray/extra.rb', line 456

def concatenate(arrays, axis: 0)
  klass = self == NArray ? NArray.array_type(arrays) : self
  nd = 0
  arrays = arrays.map do |a|
    case a
    when NArray
      # ok
    when Numeric
      a = klass[a]
    when Array
      a = klass.cast(a)
    else
      raise TypeError, "not Numo::NArray: #{a.inspect[0..48]}"
    end
    nd = a.ndim if a.ndim > nd
    a
  end
  axis += nd if axis < 0
  raise ArgumentError, 'axis is out of range' if axis < 0 || axis >= nd

  new_shape = nil
  sum_size = 0
  arrays.each do |a|
    a_shape = a.shape
    a_shape = ([1] * (nd - a_shape.size)) + a_shape if nd != a_shape.size # rubocop:disable Performance/CollectionLiteralInLoop
    sum_size += a_shape.delete_at(axis)
    if new_shape
      raise ShapeError, 'shape mismatch' if new_shape != a_shape
    else
      new_shape = a_shape
    end
  end
  new_shape.insert(axis, sum_size)
  result = klass.zeros(*new_shape)
  lst = 0
  refs = [true] * nd
  arrays.each do |a|
    fst = lst
    lst = fst + (a.shape[axis - nd] || 1)
    if lst > fst
      refs[axis] = fst...lst
      result[*refs] = a
    end
  end
  result
end

.debug=(flag) ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1717

static VALUE na_debug_set(VALUE mod, VALUE flag) {
  na_debug_flag = RTEST(flag);
  return Qnil;
}

.diag_indices(m, n, k = 0) ⇒ Object

Return the k-th diagonal indices.



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# File 'lib/numo/narray/extra.rb', line 1074

def self.diag_indices(m, n, k = 0)
  x = Numo::Int64.new(m, 1).seq + k
  y = Numo::Int64.new(1, n).seq
  (x.eq y).where
end

.dstack(arrays) ⇒ Object

Stack arrays in depth wise (along third axis).

Examples:

a = Numo::Int32[1,2,3]
b = Numo::Int32[2,3,4]
Numo::NArray.dstack([a,b])
# => Numo::Int32#shape=[1,3,2]
# [[[1, 2],
#   [2, 3],
#   [3, 4]]]

a = Numo::Int32[[1],[2],[3]]
b = Numo::Int32[[2],[3],[4]]
Numo::NArray.dstack([a,b])
# => Numo::Int32#shape=[3,1,2]
# [[[1, 2]],
#  [[2, 3]],
#  [[3, 4]]]


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# File 'lib/numo/narray/extra.rb', line 576

def dstack(arrays)
  arys = arrays.map do |a|
    _atleast_3d(cast(a))
  end
  concatenate(arys, axis: 2)
end

.eye(*args) ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 552

static VALUE na_s_eye(int argc, VALUE* argv, VALUE klass) {
  VALUE obj;
  VALUE tmp[2];

  if (argc == 0) {
    rb_raise(rb_eArgError, "No argument");
  } else if (argc == 1) {
    tmp[0] = tmp[1] = argv[0];
    argv = tmp;
    argc = 2;
  }
  obj = rb_class_new_instance(argc, argv, klass);
  return rb_funcall(obj, id_eye, 0);
}

.from_binary(*args) ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1242

static VALUE nary_s_from_binary(int argc, VALUE* argv, VALUE type) {
  size_t len, str_len, byte_size;
  size_t* shape;
  int i, nd, narg;
  VALUE vstr, vshape, vna;
  VALUE velmsz;

  narg = rb_scan_args(argc, argv, "11", &vstr, &vshape);
  Check_Type(vstr, T_STRING);
  str_len = RSTRING_LEN(vstr);
  velmsz = rb_const_get(type, id_element_byte_size);
  if (narg == 2) {
    switch (TYPE(vshape)) {
    case T_FIXNUM:
      nd = 1;
      len = NUM2SIZET(vshape);
      shape = &len;
      break;
    case T_ARRAY:
      nd = (int)RARRAY_LEN(vshape);
      if (nd > NA_MAX_DIMENSION) {
        rb_raise(nary_eDimensionError, "shape exceeds max dimension");
      }
      shape = ALLOCA_N(size_t, nd);
      len = 1;
      for (i = 0; i < nd; ++i) {
        len *= shape[i] = NUM2SIZET(RARRAY_AREF(vshape, i));
      }
      break;
    default:
      rb_raise(rb_eArgError, "second argument must be size or shape");
    }
    if (FIXNUM_P(velmsz)) {
      byte_size = len * NUM2SIZET(velmsz);
    } else {
      byte_size = ceil(len * NUM2DBL(velmsz));
    }
    if (byte_size > str_len) {
      rb_raise(rb_eArgError, "specified size is too large");
    }
  } else {
    nd = 1;
    if (FIXNUM_P(velmsz)) {
      len = str_len / NUM2SIZET(velmsz);
      byte_size = len * NUM2SIZET(velmsz);
    } else {
      len = floor(str_len / NUM2DBL(velmsz));
      byte_size = str_len;
    }
    if (len == 0) {
      rb_raise(rb_eArgError, "string is empty or too short");
    }
    shape = ALLOCA_N(size_t, nd);
    shape[0] = len;
  }

  vna = nary_new(type, nd, shape);
  if (OBJ_FROZEN(vstr)) {
    na_set_pointer(vna, RSTRING_PTR(vstr), byte_size);
    rb_ivar_set(vna, id_source, vstr);
  } else {
    void* ptr = na_get_pointer_for_write(vna);
    memcpy(ptr, RSTRING_PTR(vstr), byte_size);
  }

  return vna;
}

.hstack(arrays) ⇒ Object

Stack arrays horizontally (column wise).

Examples:

a = Numo::Int32[1,2,3]
b = Numo::Int32[2,3,4]
Numo::NArray.hstack([a,b])
# => Numo::Int32#shape=[6]
# [1, 2, 3, 2, 3, 4]

a = Numo::Int32[[1],[2],[3]]
b = Numo::Int32[[2],[3],[4]]
Numo::NArray.hstack([a,b])
# => Numo::Int32#shape=[3,2]
# [[1, 2],
#  [2, 3],
#  [3, 4]]


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# File 'lib/numo/narray/extra.rb', line 546

def hstack(arrays)
  klass = self == NArray ? NArray.array_type(arrays) : self
  nd = 0
  arys = arrays.map do |a|
    a = klass.cast(a)
    nd = a.ndim if a.ndim > nd
    a
  end
  dim = nd >= 2 ? 1 : 0
  concatenate(arys, axis: dim)
end

.inspect_cols ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1766

static VALUE na_inspect_cols(VALUE mod) {
  if (numo_na_inspect_cols > 0) {
    return INT2NUM(numo_na_inspect_cols);
  } else {
    return Qnil;
  }
}

.inspect_cols=(num) ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1780

static VALUE na_inspect_cols_set(VALUE mod, VALUE num) {
  if (RTEST(num)) {
    numo_na_inspect_cols = NUM2INT(num);
  } else {
    numo_na_inspect_cols = 0;
  }
  return Qnil;
}

.inspect_rows ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1738

static VALUE na_inspect_rows(VALUE mod) {
  if (numo_na_inspect_rows > 0) {
    return INT2NUM(numo_na_inspect_rows);
  } else {
    return Qnil;
  }
}

.inspect_rows=(num) ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1752

static VALUE na_inspect_rows_set(VALUE mod, VALUE num) {
  if (RTEST(num)) {
    numo_na_inspect_rows = NUM2INT(num);
  } else {
    numo_na_inspect_rows = 0;
  }
  return Qnil;
}

.linspace(*args) ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 477

static VALUE na_s_linspace(int argc, VALUE* argv, VALUE klass) {
  VALUE obj, vx1, vx2, vstep, vsize;
  double n;
  int narg;

  narg = rb_scan_args(argc, argv, "21", &vx1, &vx2, &vsize);
  if (narg == 3) {
    n = NUM2DBL(vsize);
  } else {
    n = 100;
    vsize = INT2FIX(100);
  }

  obj = rb_funcall(vx2, '-', 1, vx1);
  vstep = rb_funcall(obj, '/', 1, DBL2NUM(n - 1));

  obj = rb_class_new_instance(1, &vsize, klass);
  return rb_funcall(obj, id_seq, 2, vx1, vstep);
}

.logspace(*args) ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 518

static VALUE na_s_logspace(int argc, VALUE* argv, VALUE klass) {
  VALUE obj, vx1, vx2, vstep, vsize, vbase;
  double n;

  rb_scan_args(argc, argv, "22", &vx1, &vx2, &vsize, &vbase);
  if (vsize == Qnil) {
    vsize = INT2FIX(50);
    n = 50;
  } else {
    n = NUM2DBL(vsize);
  }
  if (vbase == Qnil) {
    vbase = DBL2NUM(10);
  }

  obj = rb_funcall(vx2, '-', 1, vx1);
  vstep = rb_funcall(obj, '/', 1, DBL2NUM(n - 1));

  obj = rb_class_new_instance(1, &vsize, klass);
  return rb_funcall(obj, id_logseq, 3, vx1, vstep, vbase);
}

.new_like(obj) ⇒ Object 



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# File 'ext/numo/narray/array.c', line 418

VALUE
na_s_new_like(VALUE type, VALUE obj) {
  VALUE newary;

  na_composition3(obj, &type, 0, &newary);
  return newary;
}

.ones(*args) ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 455

static VALUE na_s_ones(int argc, VALUE* argv, VALUE klass) {
  VALUE obj;
  obj = rb_class_new_instance(argc, argv, klass);
  return rb_funcall(obj, id_fill, 1, INT2FIX(1));
}

.parse(str, split1d: /\s+/, split2d: /;?$|;/, split3d: /\s*\n(\s*\n)+/m) ⇒ Object

parse matrix like matlab, octave

Examples:

a = Numo::DFloat.parse %[
 2 -3 5
 4 9 7
 2 -1 6
]
# => Numo::DFloat#shape=[3,3]
# [[2, -3, 5],
#  [4, 9, 7],
#  [2, -1, 6]]
a = Numo::NArray.parse('true false nil')
# => Numo::Bit#shape=[1,3]
# [[1, 0, 0]]


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# File 'lib/numo/narray/extra.rb', line 145

def self.parse(str, split1d: /\s+/, split2d: /;?$|;/,
               split3d: /\s*\n(\s*\n)+/m)
  a = []
  str.split(split3d).each do |block|
    b = []
    # print "b"; p block
    block.split(split2d).each do |line|
      # p line
      line.strip!
      next if line.empty?

      c = []
      line.split(split1d).each do |item|
        item = item.strip
        c << parse_token(item) unless item.empty?
      end
      b << c unless c.empty?
    end
    a << b unless b.empty?
  end
  if a.size == 1
    cast(a[0])
  else
    cast(a)
  end
end

.profile ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1724

static VALUE na_profile(VALUE mod) {
  return rb_float_new(na_profile_value);
}

.profile=(val) ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1728

static VALUE na_profile_set(VALUE mod, VALUE val) {
  na_profile_value = NUM2DBL(val);
  return val;
}

.tril_indices(m, n, k = 0) ⇒ Object

Return the indices for the lower-triangle on and below the k-th diagonal.



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# File 'lib/numo/narray/extra.rb', line 1059

def self.tril_indices(m, n, k = 0)
  x = Numo::Int64.new(m, 1).seq + k
  y = Numo::Int64.new(1, n).seq
  (x >= y).where
end

.triu_indices(m, n, k = 0) ⇒ Object

Return the indices for the upper-triangle on and above the k-th diagonal.



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# File 'lib/numo/narray/extra.rb', line 1022

def self.triu_indices(m, n, k = 0)
  x = Numo::Int64.new(m, 1).seq + k
  y = Numo::Int64.new(1, n).seq
  (x <= y).where
end

.upcast(type2) ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1173

VALUE
numo_na_upcast(VALUE type1, VALUE type2) {
  VALUE upcast_hash;
  VALUE result_type;

  if (type1 == type2) {
    return type1;
  }
  upcast_hash = rb_const_get(type1, id_UPCAST);
  result_type = rb_hash_aref(upcast_hash, type2);
  if (NIL_P(result_type)) {
    if (TYPE(type2) == T_CLASS) {
      if (RTEST(rb_class_inherited_p(type2, cNArray))) {
        upcast_hash = rb_const_get(type2, id_UPCAST);
        result_type = rb_hash_aref(upcast_hash, type1);
      }
    }
  }
  return result_type;
}

.vstack(arrays) ⇒ Object

Stack arrays vertically (row wise).

Examples:

a = Numo::Int32[1,2,3]
b = Numo::Int32[2,3,4]
Numo::NArray.vstack([a,b])
# => Numo::Int32#shape=[2,3]
# [[1, 2, 3],
#  [2, 3, 4]]

a = Numo::Int32[[1],[2],[3]]
b = Numo::Int32[[2],[3],[4]]
Numo::NArray.vstack([a,b])
# => Numo::Int32#shape=[6,1]
# [[1],
#  [2],
#  [3],
#  [2],
#  [3],
#  [4]]


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# File 'lib/numo/narray/extra.rb', line 523

def vstack(arrays)
  arys = arrays.map do |a|
    _atleast_2d(cast(a))
  end
  concatenate(arys, axis: 0)
end

.zeros(*args) ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 434

static VALUE na_s_zeros(int argc, VALUE* argv, VALUE klass) {
  VALUE obj;
  obj = rb_class_new_instance(argc, argv, klass);
  return rb_funcall(obj, id_fill, 1, INT2FIX(0));
}

Instance Method Details

#==(other) ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1796

static VALUE na_equal(VALUE self, volatile VALUE other) {
  volatile VALUE vbool;
  narray_t *na1, *na2;
  int i;

  GetNArray(self, na1);

  if (!rb_obj_is_kind_of(other, cNArray)) {
    other = rb_funcall(rb_obj_class(self), id_cast, 1, other);
  }

  GetNArray(other, na2);
  if (na1->ndim != na2->ndim) {
    return Qfalse;
  }
  for (i = 0; i < na1->ndim; i++) {
    if (na1->shape[i] != na2->shape[i]) {
      return Qfalse;
    }
  }
  if (na1->size == 0) {
    return Qtrue;
  }
  vbool = rb_funcall(self, id_eq, 1, other);
  return (rb_funcall(vbool, id_count_false, 0) == INT2FIX(0)) ? Qtrue : Qfalse;
}

#[] ⇒ Object

#[]= ⇒ Object

#append(other, axis: nil) ⇒ Object

Append values to the end of an narray.

Examples:

a = Numo::DFloat[1, 2, 3]
a.append([[4, 5, 6], [7, 8, 9]])
# => Numo::DFloat#shape=[9]
# [1, 2, 3, 4, 5, 6, 7, 8, 9]

a = Numo::DFloat[[1, 2, 3]]
a.append([[4, 5, 6], [7, 8, 9]],axis:0)
# => Numo::DFloat#shape=[3,3]
# [[1, 2, 3],
#  [4, 5, 6],
#  [7, 8, 9]]

a = Numo::DFloat[[1, 2, 3], [4, 5, 6]]
a.append([7, 8, 9], axis:0)
# in `append': dimension mismatch (Numo::NArray::DimensionError)


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# File 'lib/numo/narray/extra.rb', line 271

def append(other, axis: nil)
  other = self.class.cast(other)
  if axis
    raise DimensionError, 'dimension mismatch' if ndim != other.ndim

    concatenate(other, axis: axis)
  else
    a = self.class.zeros(size + other.size)
    a[0...size] = self[true]
    a[size..-1] = other[true]
    a
  end
end

#argsort(axis: -1) ⇒ Numo::Int32

Returns an index array of sort result.

Examples:

require 'numo/narray'

a = Numo::DFloat[[0.1, 0.7],
                 [0.4, 0.2],
                 [0.2, 0.5]]
pp a.argsort
# =>
# Numo::Int32#shape=[3,2]
# [[0, 1],
#  [1, 0],
#  [0, 1]]
pp a.argsort(axis: 0)
# =>
# Numo::Int32#shape=[3,2]
# [[0, 1],
#  [2, 2],
#  [1, 0]]
pp a.argsort(axis: 1)
# =>
# Numo::Int32#shape=[3,2]
# [[0, 1],
#  [1, 0],
#  [0, 1]]
pp a.argsort(axis: nil)
# =>
# Numo::Int32#shape=[6]
# [0, 3, 4, 2, 5, 1]

Returns An array of indices that would sort the array.

Parameters:

  • axis (Integer, nil) (defaults to: -1) —

    Axis along which to sort. Default is -1 (the last axis). If nil is given, the array is flattened before sorting.

Returns:

  • (Numo::Int32) —

    An array of indices that would sort the array.

Raises:

  • (NotImplementedError) 


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# File 'lib/numo/narray/extra.rb', line 1124

def argsort(axis_ = 'none', axis: -1)
  raise NotImplementedError, "argsort is not implemented for #{self.class}" unless respond_to?(:sort_index)

  axis = axis_ unless axis_ == 'none'

  return flatten.sort_index if axis.nil?

  axis = ndim + axis if axis.negative?
  raise Numo::NArray::DimensionError, 'dimension is out of range' if axis.negative? || axis >= ndim

  case ndim
  when 1
    sort_index
  when 2
    case axis
    when 0
      indices = transpose.sort_index(1)
      indices.transpose - indices.min(1)
    when 1
      indices = sort_index(1)
      indices - indices.min(1).expand_dims(1)
    end
  else
    res = Numo::Int32.zeros(*shape)
    slicer = Array.new(ndim)
    slicer[axis] = true
    other_axes = Array.new(ndim) { |i| i } - [axis]
    axis_ids = other_axes.map do |d|
      Array.new(shape[d]) { |i| i }
    end
    axis_ids.inject(:product).each do |indices|
      indices = indices.flatten
      other_axes.each_with_index do |d, i|
        slicer[d] = indices[i]
      end
      sorted_indices = self[*slicer].sort_index
      res[*slicer] = sorted_indices - sorted_indices.min
    end
    res
  end
end

#at(*args) ⇒ Object 



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# File 'ext/numo/narray/index.c', line 1054

static VALUE na_at(int argc, VALUE* argv, VALUE self) {
  int i;
  size_t n;
  ssize_t stride = 1;
  narray_t* na;
  VALUE idx = Qnil;

  na_index_arg_to_internal_order(argc, argv, self);

  GetNArray(self, na);
  if (NA_NDIM(na) != argc) {
    rb_raise(rb_eArgError, "the number of argument must be same as dimension");
  }
  for (i = argc; i > 0;) {
    i--;
    n = NA_SHAPE(na)[i];
    na_at_parse_each(argv[i], n, i, &idx, stride);
    stride *= n;
  }
  return na_aref_main(1, &idx, self, 1, 1);
}

#byte_size ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1215

static VALUE nary_byte_size(VALUE self) {
  VALUE velmsz;
  narray_t* na;

  GetNArray(self, na);
  velmsz = rb_const_get(rb_obj_class(self), id_element_byte_size);
  if (FIXNUM_P(velmsz)) {
    return SIZET2NUM(NUM2SIZET(velmsz) * na->size);
  }
  return SIZET2NUM(ceil(NUM2DBL(velmsz) * na->size));
}

#byte_swapped? ⇒ Object Also known as: network_order? 



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# File 'ext/numo/narray/narray.c', line 1663

static VALUE na_byte_swapped_p(VALUE self) {
  if (TEST_BYTE_SWAPPED(self)) return Qtrue;
  return Qfalse;
}

#cast_to(type) ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1476

static VALUE nary_cast_to(VALUE obj, VALUE type) {
  return rb_funcall(type, id_cast, 1, obj);
}

#coerce(y) ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1203

static VALUE nary_coerce(VALUE x, VALUE y) {
  VALUE type;

  type = numo_na_upcast(rb_obj_class(x), rb_obj_class(y));
  y = rb_funcall(type, id_cast, 1, y);
  return rb_assoc_new(y, x);
}

#column_major? ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1643

static VALUE na_column_major_p(VALUE self) {
  if (TEST_COLUMN_MAJOR(self))
    return Qtrue;
  else
    return Qfalse;
}

#concatenate(*arrays, axis: 0) ⇒ Object

Examples:

a = Numo::DFloat[[1, 2], [3, 4]]
# => Numo::DFloat#shape=[2,2]
# [[1, 2],
#  [3, 4]]

b = Numo::DFloat[[5, 6]]
# => Numo::DFloat#shape=[1,2]
# [[5, 6]]

a.concatenate(b,axis:0)
# => Numo::DFloat#shape=[3,2]
# [[1, 2],
#  [3, 4],
#  [5, 6]]

a.concatenate(b.transpose, axis:1)
# => Numo::DFloat#shape=[2,3]
# [[1, 2, 5],
#  [3, 4, 6]]


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# File 'lib/numo/narray/extra.rb', line 648

def concatenate(*arrays, axis: 0)
  axis = check_axis(axis)
  self_shape = shape
  self_shape.delete_at(axis)
  sum_size = shape[axis]
  arrays.map! do |a|
    case a
    when NArray
      # ok
    when Numeric
      a = self.class.new(1).store(a)
    when Array
      a = self.class.cast(a)
    else
      raise TypeError, "not Numo::NArray: #{a.inspect[0..48]}"
    end
    raise ShapeError, 'dimension mismatch' if a.ndim > ndim

    a_shape = a.shape
    sum_size += a_shape.delete_at(axis - ndim) || 1
    raise ShapeError, 'shape mismatch' if self_shape != a_shape

    a
  end
  self_shape.insert(axis, sum_size)
  result = self.class.zeros(*self_shape)
  lst = shape[axis]
  refs = [true] * ndim
  if lst > 0
    refs[axis] = 0...lst
    result[*refs] = self
  end
  arrays.each do |a|
    fst = lst
    lst = fst + (a.shape[axis - ndim] || 1)
    if lst > fst
      refs[axis] = fst...lst
      result[*refs] = a
    end
  end
  result
end

#contiguous? ⇒ Boolean

Returns:

  • (Boolean) 


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# File 'ext/numo/narray/narray.c', line 909

VALUE
na_check_contiguous(VALUE self) {
  ssize_t elmsz;
  narray_t* na;
  GetNArray(self, na);

  switch (na->type) {
  case NARRAY_DATA_T:
  case NARRAY_FILEMAP_T:
    return Qtrue;
  case NARRAY_VIEW_T:
    if (NA_VIEW_STRIDX(na) == 0) {
      return Qtrue;
    }
    if (na_check_ladder(self, 0) == Qtrue) {
      elmsz = nary_element_stride(self);
      if (elmsz == NA_STRIDE_AT(na, NA_NDIM(na) - 1)) {
        return Qtrue;
      }
    }
  }
  return Qfalse;
}

#cov(y = nil, ddof: 1, fweights: nil, aweights: nil) ⇒ Numo::NArray

Compute a covariance matrix.

Examples:

x = Numo::DFloat[4, 5, 6]
x.cov
# => 1.0

x = Numo::DFloat[[4, 5, 6], [3, 2, 1]]
x.cov
# => Numo::DFloat#shape=[2,2]
# [[1, -1],
#  [-1, 1]]

y = Numo::DFloat[7, 9, 8]
x.cov(y)
# => Numo::DFloat#shape=[3,3]
# [[1, -1, 0.5],
#  [-1, 1, -0.5],
#  [0.5, -0.5, 1]]

Parameters:

  • y (Numo::NArray) (defaults to: nil) —

    (optional) If not nil, the covariance matrix of self and y is computed.

  • ddof (Integer) (defaults to: 1) —

    (optional) Delta degrees of freedom. The divisor used in calculations is N - ddof, where N represents the number of observations.

  • fweights (Numo::NArray) (defaults to: nil) —

    (optional) 1-D array of integer frequency weights.

  • aweights (Numo::NArray) (defaults to: nil) —

    (optional) 1-D array of observation vector weights.

Returns:

Raises:



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# File 'lib/numo/narray/extra.rb', line 1359

def cov(y = nil, ddof: 1, fweights: nil, aweights: nil) # rubocop:disable Metrics/AbcSize, Metrics/CyclomaticComplexity, Metrics/PerceivedComplexity
  raise Numo::NArray::ShapeError, 'ndim must be <= 2' if ndim > 2
  raise Numo::NArray::ShapeError, 'y.ndim must be <= 2' if !y.nil? && (y.ndim > 2)
  raise ArgumentError, 'ddof must be 0 or 1' unless [0, 1].include?(ddof)

  m = if y
        NArray.vstack([self, y])
      else
        self
      end
  w = nil
  if fweights
    fweights = Numo::NArray.cast(fweights) unless fweights.is_a?(Numo::NArray)
    raise ArgumentError, 'fweights must be 1-D array' unless fweights.ndim == 1
    raise ArgumentError, 'fweights size is wrong' unless fweights.size == m.shape[1]
    raise ArgumentError, 'fweights must be non-negative' if (fweights < 0).any?
    raise ArgumentError, 'fweights must be integer' unless fweights == fweights.floor

    w = fweights
  end
  if aweights
    aweights = Numo::NArray.cast(aweights) unless aweights.is_a?(Numo::NArray)
    raise ArgumentError, 'aweights must be 1-D array' unless aweights.ndim == 1
    raise ArgumentError, 'aweights size is wrong' unless aweights.size == m.shape[1]
    raise ArgumentError, 'aweights must be non-negative' if (aweights < 0).any?

    if w.nil?
      w = aweights
    else
      w *= aweights
    end
  end
  fact = if w.nil?
           m.shape[-1] - ddof
         elsif ddof == 0
           w.sum
         elsif aweights.nil?
           w.sum - ddof
         else
           w_sum = w.sum
           w_sum - (ddof * (w * aweights).sum / w_sum)
         end
  if fact <= 0
    warn('Degrees of freedom <= 0 for slice')
    fact = 0.0
  end
  if w.nil?
    m -= m.mean(axis: -1, keepdims: true)
    mw = m
  else
    m -= (m * w).sum(axis: -1, keepdims: true) / w.sum
    mw = m * w
  end
  m.dot(mw.transpose.conj) / fact
end

#debug_info ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 136

VALUE
nary_debug_info(VALUE self) {
  int i;
  narray_t* na;
  GetNArray(self, na);

  printf("%s:\n", rb_class2name(rb_obj_class(self)));
  printf("  id     = 0x%" PRI_VALUE_PREFIX "x\n", self);
  printf("  type   = %d\n", na->type);
  printf("  flag   = [%d,%d]\n", na->flag[0], na->flag[1]);
  printf("  size   = %" SZF "d\n", na->size);
  printf("  ndim   = %d\n", na->ndim);
  printf("  shape  = 0x%" SZF "x\n", (size_t)na->shape);
  if (na->shape) {
    printf("  shape  = [");
    for (i = 0; i < na->ndim; i++) printf(" %" SZF "d", na->shape[i]);
    printf(" ]\n");
  }

  switch (na->type) {
  case NARRAY_DATA_T:
  case NARRAY_FILEMAP_T:
    nary_debug_info_nadata(self);
    break;
  case NARRAY_VIEW_T:
    nary_debug_info_naview(self);
    break;
  }
  return Qnil;
}

#deg2rad ⇒ Object

Convert angles from degrees to radians.



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# File 'lib/numo/narray/extra.rb', line 31

def deg2rad
  self * (Math::PI / 180)
end

#delete(indice, axis = nil) ⇒ Object

Examples:

a = Numo::DFloat[[1,2,3,4], [5,6,7,8], [9,10,11,12]]
a.delete(1,0)
# => Numo::DFloat(view)#shape=[2,4]
# [[1, 2, 3, 4],
#  [9, 10, 11, 12]]

a.delete((0..-1).step(2),1)
# => Numo::DFloat(view)#shape=[3,2]
# [[2, 4],
#  [6, 8],
#  [10, 12]]

a.delete([1,3,5])
# => Numo::DFloat(view)#shape=[9]
# [1, 3, 5, 7, 8, 9, 10, 11, 12]


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# File 'lib/numo/narray/extra.rb', line 305

def delete(indice, axis = nil)
  if axis
    bit = Bit.ones(shape[axis])
    bit[indice] = 0
    idx = [true] * ndim
    idx[axis] = bit.where
    self[*idx].copy
  else
    bit = Bit.ones(size)
    bit[indice] = 0
    self[bit.where].copy
  end
end

#diag(k = 0) ⇒ Object

Return a matrix whose diagonal is constructed by self along the last axis.



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# File 'lib/numo/narray/extra.rb', line 1081

def diag(k = 0)
  *shp, n = shape
  n += k.abs
  a = self.class.zeros(*shp, n, n)
  a.diagonal(k).store(self)
  a
end

#diag_indices(k = 0) ⇒ Object

Return the k-th diagonal indices.

Raises:



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# File 'lib/numo/narray/extra.rb', line 1066

def diag_indices(k = 0)
  raise NArray::ShapeError, 'must be >= 2-dimensional array' if ndim < 2

  m, n = shape[-2..]
  NArray.diag_indices(m, n, k)
end

#diagonal([offset,axes]) ⇒ Numo::NArray

Returns a diagonal view of NArray

Examples:

a = Numo::DFloat.new(4,5).seq
# => Numo::DFloat#shape=[4,5]
# [[0, 1, 2, 3, 4],
#  [5, 6, 7, 8, 9],
#  [10, 11, 12, 13, 14],
#  [15, 16, 17, 18, 19]]
b = a.diagonal(1)
# => Numo::DFloat(view)#shape=[4]
# [1, 7, 13, 19]

b.store(0)
a
# => Numo::DFloat#shape=[4,5]
# [[0, 0, 2, 3, 4],
#  [5, 6, 0, 8, 9],
#  [10, 11, 12, 0, 14],
#  [15, 16, 17, 18, 0]]

b.store([1,2,3,4])
a
# => Numo::DFloat#shape=[4,5]
# [[0, 1, 2, 3, 4],
#  [5, 6, 2, 8, 9],
#  [10, 11, 12, 3, 14],
#  [15, 16, 17, 18, 4]]

Returns diagonal view of NArray.

Parameters:

  • offset (Integer) —

    Diagonal offset from the main diagonal. The default is 0. k>0 for diagonals above the main diagonal, and k<0 for diagonals below the main diagonal.

  • axes (Array) —

    Array of axes to be used as the 2-d sub-arrays from which the diagonals should be taken. Defaults to last-two axes ([-2,-1]).

Returns:



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# File 'ext/numo/narray/data.c', line 591

static VALUE na_diagonal(int argc, VALUE* argv, VALUE self) {
  int i, k, nd;
  size_t j;
  size_t *idx0, *idx1, *diag_idx;
  size_t* shape;
  size_t diag_size;
  ssize_t stride, stride0, stride1;
  narray_t* na;
  narray_view_t *na1, *na2;
  VALUE view;
  VALUE vofs = 0, vaxes = 0;
  ssize_t kofs;
  size_t k0, k1;
  int ax[2];

  // check arguments
  if (argc > 2) {
    rb_raise(rb_eArgError, "too many arguments (%d for 0..2)", argc);
  }

  for (i = 0; i < argc; i++) {
    switch (TYPE(argv[i])) {
    case T_FIXNUM:
      if (vofs) {
        rb_raise(rb_eArgError, "offset is given twice");
      }
      vofs = argv[i];
      break;
    case T_ARRAY:
      if (vaxes) {
        rb_raise(rb_eArgError, "axes-array is given twice");
      }
      vaxes = argv[i];
      break;
    }
  }

  if (vofs) {
    kofs = NUM2SSIZET(vofs);
  } else {
    kofs = 0;
  }

  GetNArray(self, na);
  nd = na->ndim;
  if (nd < 2) {
    rb_raise(nary_eDimensionError, "less than 2-d array");
  }

  if (vaxes) {
    if (RARRAY_LEN(vaxes) != 2) {
      rb_raise(rb_eArgError, "axes must be 2-element array");
    }
    ax[0] = NUM2INT(RARRAY_AREF(vaxes, 0));
    ax[1] = NUM2INT(RARRAY_AREF(vaxes, 1));
    if (ax[0] < -nd || ax[0] >= nd || ax[1] < -nd || ax[1] >= nd) {
      rb_raise(rb_eArgError, "axis out of range:[%d,%d]", ax[0], ax[1]);
    }
    if (ax[0] < 0) {
      ax[0] += nd;
    }
    if (ax[1] < 0) {
      ax[1] += nd;
    }
    if (ax[0] == ax[1]) {
      rb_raise(rb_eArgError, "same axes:[%d,%d]", ax[0], ax[1]);
    }
  } else {
    ax[0] = nd - 2;
    ax[1] = nd - 1;
  }

  // Diagonal offset from the main diagonal.
  if (kofs >= 0) {
    k0 = 0;
    k1 = kofs;
    if (k1 >= na->shape[ax[1]]) {
      rb_raise(
        rb_eArgError,
        "invalid diagonal offset(%" SZF "d) for "
        "last dimension size(%" SZF "d)",
        kofs, na->shape[ax[1]]
      );
    }
  } else {
    k0 = -kofs;
    k1 = 0;
    if (k0 >= na->shape[ax[0]]) {
      rb_raise(
        rb_eArgError,
        "invalid diagonal offset(=%" SZF "d) for "
        "last-1 dimension size(%" SZF "d)",
        kofs, na->shape[ax[0]]
      );
    }
  }

  diag_size = MIN(na->shape[ax[0]] - k0, na->shape[ax[1]] - k1);

  // new shape
  shape = ALLOCA_N(size_t, nd - 1);
  for (i = k = 0; i < nd; i++) {
    if (i != ax[0] && i != ax[1]) {
      shape[k++] = na->shape[i];
    }
  }
  shape[k] = diag_size;

  // new object
  view = na_s_allocate_view(rb_obj_class(self));
  na_copy_flags(self, view);
  GetNArrayView(view, na2);

  // new stride
  na_setup_shape((narray_t*)na2, nd - 1, shape);
  na2->stridx = ALLOC_N(stridx_t, nd - 1);

  switch (na->type) {
  case NARRAY_DATA_T:
  case NARRAY_FILEMAP_T:
    na2->offset = 0;
    na2->data = self;
    stride = stride0 = stride1 = nary_element_stride(self);
    for (i = nd, k = nd - 2; i--;) {
      if (i == ax[1]) {
        stride1 = stride;
        if (kofs > 0) {
          na2->offset = kofs * stride;
        }
      } else if (i == ax[0]) {
        stride0 = stride;
        if (kofs < 0) {
          na2->offset = (-kofs) * stride;
        }
      } else {
        SDX_SET_STRIDE(na2->stridx[--k], stride);
      }
      stride *= na->shape[i];
    }
    SDX_SET_STRIDE(na2->stridx[nd - 2], stride0 + stride1);
    break;

  case NARRAY_VIEW_T:
    GetNArrayView(self, na1);
    na2->data = na1->data;
    na2->offset = na1->offset;
    for (i = k = 0; i < nd; i++) {
      if (i != ax[0] && i != ax[1]) {
        if (SDX_IS_INDEX(na1->stridx[i])) {
          idx0 = SDX_GET_INDEX(na1->stridx[i]);
          idx1 = ALLOC_N(size_t, na->shape[i]);
          for (j = 0; j < na->shape[i]; j++) {
            idx1[j] = idx0[j];
          }
          SDX_SET_INDEX(na2->stridx[k], idx1);
        } else {
          na2->stridx[k] = na1->stridx[i];
        }
        k++;
      }
    }
    if (SDX_IS_INDEX(na1->stridx[ax[0]])) {
      idx0 = SDX_GET_INDEX(na1->stridx[ax[0]]);
      diag_idx = ALLOC_N(size_t, diag_size);
      if (SDX_IS_INDEX(na1->stridx[ax[1]])) {
        idx1 = SDX_GET_INDEX(na1->stridx[ax[1]]);
        for (j = 0; j < diag_size; j++) {
          diag_idx[j] = idx0[j + k0] + idx1[j + k1];
        }
      } else {
        stride1 = SDX_GET_STRIDE(na1->stridx[ax[1]]);
        for (j = 0; j < diag_size; j++) {
          diag_idx[j] = idx0[j + k0] + stride1 * (j + k1);
        }
      }
      SDX_SET_INDEX(na2->stridx[nd - 2], diag_idx);
    } else {
      stride0 = SDX_GET_STRIDE(na1->stridx[ax[0]]);
      if (SDX_IS_INDEX(na1->stridx[ax[1]])) {
        idx1 = SDX_GET_INDEX(na1->stridx[ax[1]]);
        diag_idx = ALLOC_N(size_t, diag_size);
        for (j = 0; j < diag_size; j++) {
          diag_idx[j] = stride0 * (j + k0) + idx1[j + k1];
        }
        SDX_SET_INDEX(na2->stridx[nd - 2], diag_idx);
      } else {
        stride1 = SDX_GET_STRIDE(na1->stridx[ax[1]]);
        na2->offset += stride0 * k0 + stride1 * k1;
        SDX_SET_STRIDE(na2->stridx[nd - 2], stride0 + stride1);
      }
    }
    break;
  }
  return view;
}

#diff(n = 1, axis: -1)) ⇒ Object

Calculate the n-th discrete difference along given axis.

Examples:

x = Numo::DFloat[1, 2, 4, 7, 0]
# => Numo::DFloat#shape=[5]
# [1, 2, 4, 7, 0]

x.diff
# => Numo::DFloat#shape=[4]
# [1, 2, 3, -7]

x.diff(2)
# => Numo::DFloat#shape=[3]
# [1, 1, -10]

x = Numo::DFloat[[1, 3, 6, 10], [0, 5, 6, 8]]
# => Numo::DFloat#shape=[2,4]
# [[1, 3, 6, 10],
#  [0, 5, 6, 8]]

x.diff
# => Numo::DFloat#shape=[2,3]
# [[2, 3, 4],
#  [5, 1, 2]]

x.diff(axis:0)
# => Numo::DFloat#shape=[1,4]
# [[-1, 2, 0, -2]]

Raises:



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# File 'lib/numo/narray/extra.rb', line 966

def diff(n = 1, axis: -1)
  axis = check_axis(axis)
  raise ShapeError, "n=#{n} is invalid for shape[#{axis}]=#{shape[axis]}" if n < 0 || n >= shape[axis]

  # calculate polynomial coefficient
  c = self.class[-1, 1]
  2.upto(n) do |i|
    x = self.class.zeros(i + 1)
    x[0..-2] = c
    y = self.class.zeros(i + 1)
    y[1..-1] = c
    c = y - x
  end
  s = [true] * ndim
  s[axis] = n..-1
  result = self[*s].dup
  sum = result.inplace
  (n - 1).downto(0) do |i|
    s = [true] * ndim
    s[axis] = i..(-n - 1 + i)
    sum + (self[*s] * c[i]) # inplace addition
  end
  result
end

#dot(b) ⇒ Numo::NArray

Dot product of two arrays.

Parameters:

Returns:



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# File 'lib/numo/narray/extra.rb', line 1186

def dot(b)
  t = self.class::UPCAST[b.class]
  if defined?(Linalg) && [SFloat, DFloat, SComplex, DComplex].include?(t)
    Linalg.dot(self, b)
  else
    b = self.class.asarray(b)
    case b.ndim
    when 1
      mulsum(b, axis: -1)
    else
      case ndim
      when 0
        b.mulsum(self, axis: -2)
      when 1
        self[true, :new].mulsum(b, axis: -2)
      else
        unless @@warn_slow_dot
          nx = 200
          ns = 200_000
          am, an = shape[-2..]
          bm, bn = b.shape[-2..]
          if am > nx && an > nx && bm > nx && bn > nx &&
             size > ns && b.size > ns
            @@warn_slow_dot = true
            warn "\nwarning: Built-in matrix dot is slow. Consider installing numo-linalg-alt gem.\n\n"
          end
        end
        self[false, :new].mulsum(b[false, :new, true, true], axis: -2)
      end
    end
  end
end

#dsplit(indices_or_sections) ⇒ Object

Split an array into multiple sub-arrays along the depth



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# File 'lib/numo/narray/extra.rb', line 798

def dsplit(indices_or_sections)
  split(indices_or_sections, axis: 2)
end

#each_over_axis(axis = 0) ⇒ Object

Iterate over an axis

Examples:

> a = Numo::DFloat.new(2,2,2).seq
> p a
Numo::DFloat#shape=[2,2,2]
[[[0, 1],
  [2, 3]],
 [[4, 5],
  [6, 7]]]

> a.each_over_axis{|i| p i}
Numo::DFloat(view)#shape=[2,2]
[[0, 1],
 [2, 3]]
Numo::DFloat(view)#shape=[2,2]
[[4, 5],
 [6, 7]]

> a.each_over_axis(1){|i| p i}
Numo::DFloat(view)#shape=[2,2]
[[0, 1],
 [4, 5]]
Numo::DFloat(view)#shape=[2,2]
[[2, 3],
 [6, 7]]


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# File 'lib/numo/narray/extra.rb', line 234

def each_over_axis(axis = 0)
  return to_enum(:each_over_axis, axis) unless block_given?

  if ndim == 0
    raise ArgumentError, "axis=#{axis} is invalid" if axis != 0

    niter = 1
  else
    axis = check_axis(axis)
    niter = shape[axis]
  end
  idx = [true] * ndim
  niter.times do |i|
    idx[axis] = i
    yield(self[*idx])
  end
  self
end

#empty? ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 749

static VALUE na_empty_p(VALUE self) {
  narray_t* na;
  GetNArray(self, na);
  if (NA_SIZE(na) == 0) {
    return Qtrue;
  }
  return Qfalse;
}

#expand_dims(vdim) ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1036

static VALUE na_expand_dims(VALUE self, VALUE vdim) {
  int i, j, nd, dim;
  size_t *shape, *na_shape;
  stridx_t *stridx, *na_stridx;
  narray_t* na;
  narray_view_t* na2;
  VALUE view;

  GetNArray(self, na);
  nd = na->ndim;

  dim = NUM2INT(vdim);
  if (dim < -nd - 1 || dim > nd) {
    rb_raise(nary_eDimensionError, "invalid axis (%d for %dD NArray)", dim, nd);
  }
  if (dim < 0) {
    dim += nd + 1;
  }

  view = na_make_view(self);
  GetNArrayView(view, na2);

  shape = ALLOC_N(size_t, nd + 1);
  stridx = ALLOC_N(stridx_t, nd + 1);
  na_shape = na2->base.shape;
  na_stridx = na2->stridx;

  for (i = j = 0; i <= nd; i++) {
    if (i == dim) {
      shape[i] = 1;
      SDX_SET_STRIDE(stridx[i], 0);
    } else {
      shape[i] = na_shape[j];
      stridx[i] = na_stridx[j];
      j++;
    }
  }

  na2->stridx = stridx;
  xfree(na_stridx);
  na2->base.shape = shape;
  if (na_shape != &(na2->base.size)) {
    xfree(na_shape);
  }
  na2->base.ndim++;
  return view;
}

#flatten ⇒ Object

deprecated



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# File 'ext/numo/narray/data.c', line 545

VALUE
na_flatten(VALUE self) {
  return na_flatten_dim(self, 0);
}

#fliplr ⇒ Object

Flip each row in the left/right direction. Same as a[true, (-1..0).step(-1), ...].



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# File 'lib/numo/narray/extra.rb', line 37

def fliplr
  reverse(1)
end

#flipud ⇒ Object

Flip each column in the up/down direction. Same as a[(-1..0).step(-1), ...].



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# File 'lib/numo/narray/extra.rb', line 43

def flipud
  reverse(0)
end

#fortran_contiguous? ⇒ Boolean

Returns:

  • (Boolean) 


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# File 'ext/numo/narray/narray.c', line 933

VALUE
na_check_fortran_contiguous(VALUE self) {
  int i;
  ssize_t st0;
  narray_t* na;

  switch (RNARRAY_TYPE(self)) {
  case NARRAY_DATA_T:
  case NARRAY_FILEMAP_T:
    return Qfalse;
  case NARRAY_VIEW_T:
    GetNArray(self, na);

    // not contiguous if it has index
    for (i = 0; i < NA_NDIM(na); i++) {
      if (NA_IS_INDEX_AT(na, i)) return Qfalse;
    }

    // check f-contiguous
    st0 = nary_element_stride(self); // elmsz
    for (i = 0; i < NA_NDIM(na); i++) {
      if (NA_SHAPE(na)[i] == 1) continue;
      if (NA_STRIDE_AT(na, i) != st0) return Qfalse;
      st0 *= NA_SHAPE(na)[i];
    }
  }
  return Qtrue;
}

#free ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 764

static VALUE na_free(VALUE self) {
  narray_t* na;
  char* ptr;

  GetNArray(self, na);

  switch (NA_TYPE(na)) {
  case NARRAY_DATA_T:
    ptr = NA_DATA_PTR(na);
    if (ptr != NULL) {
      NA_DATA_PTR(na) = NULL;
      xfree(ptr);
    }
    break;
  case NARRAY_VIEW_T:
    break;
  case NARRAY_FILEMAP_T:
  default:
    rb_bug("invalid narray type : %d", NA_TYPE(na));
  }
  return self;
}

#host_order? ⇒ Object Also known as: little_endian?, vacs_order? 



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# File 'ext/numo/narray/narray.c', line 1671

static VALUE na_host_order_p(VALUE self) {
  if (TEST_BYTE_SWAPPED(self)) return Qfalse;
  return Qtrue;
}

#hsplit(indices_or_sections) ⇒ Object

Split an array into multiple sub-arrays horizontally

Examples:

x = Numo::DFloat.new(4,4).seq
# => Numo::DFloat#shape=[4,4]
# [[0, 1, 2, 3],
#  [4, 5, 6, 7],
#  [8, 9, 10, 11],
#  [12, 13, 14, 15]]

x.hsplit(2)
# => [Numo::DFloat(view)#shape=[4,2]
# [[0, 1],
#  [4, 5],
#  [8, 9],
#  [12, 13]],
#  Numo::DFloat(view)#shape=[4,2]
# [[2, 3],
#  [6, 7],
#  [10, 11],
#  [14, 15]]]

x.hsplit([3, 6])
# => [Numo::DFloat(view)#shape=[4,3]
# [[0, 1, 2],
#  [4, 5, 6],
#  [8, 9, 10],
#  [12, 13, 14]],
#  Numo::DFloat(view)#shape=[4,1]
# [[3],
#  [7],
#  [11],
#  [15]],
#  Numo::DFloat(view)#shape=[4,0][]]


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# File 'lib/numo/narray/extra.rb', line 793

def hsplit(indices_or_sections)
  split(indices_or_sections, axis: 1)
end

#initialize_copy(orig) ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 409

static VALUE na_initialize_copy(VALUE self, VALUE orig) {
  narray_t* na;
  GetNArray(orig, na);

  na_setup(self, NA_NDIM(na), NA_SHAPE(na));
  na_store(self, orig);
  na_copy_flags(orig, self);
  return self;
}

#inner(b, axis: -1)) ⇒ Numo::NArray

Inner product of two arrays. Same as (a*b).sum(axis:-1).

Parameters:

  • b (Numo::NArray)
  • axis (Integer) (defaults to: -1)) —

    applied axis

Returns:



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# File 'lib/numo/narray/extra.rb', line 1225

def inner(b, axis: -1)
  mulsum(b, axis: axis)
end

#inplace ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1680

static VALUE na_inplace(VALUE self) {
  VALUE view = self;
  view = na_make_view(self);
  SET_INPLACE(view);
  return view;
}

#inplace! ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1691

static VALUE na_inplace_bang(VALUE self) {
  SET_INPLACE(self);
  return self;
}

#inplace? ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1699

static VALUE na_inplace_p(VALUE self) {
  if (TEST_INPLACE(self))
    return Qtrue;
  else
    return Qfalse;
}

#insert(indice, values, axis: nil) ⇒ Object

Insert values along the axis before the indices.

Examples:

a = Numo::DFloat[[1, 2], [3, 4]]
a = Numo::Int32[[1, 1], [2, 2], [3, 3]]

a.insert(1,5)
# => Numo::Int32#shape=[7]
# [1, 5, 1, 2, 2, 3, 3]

a.insert(1, 5, axis:1)
# => Numo::Int32#shape=[3,3]
# [[1, 5, 1],
#  [2, 5, 2],
#  [3, 5, 3]]

a.insert([1], [[11],[12],[13]], axis:1)
# => Numo::Int32#shape=[3,3]
# [[1, 11, 1],
#  [2, 12, 2],
#  [3, 13, 3]]

a.insert(1, [11, 12, 13], axis:1)
# => Numo::Int32#shape=[3,3]
# [[1, 11, 1],
#  [2, 12, 2],
#  [3, 13, 3]]

a.insert([1], [11, 12, 13], axis:1)
# => Numo::Int32#shape=[3,5]
# [[1, 11, 12, 13, 1],
#  [2, 11, 12, 13, 2],
#  [3, 11, 12, 13, 3]]

b = a.flatten
# => Numo::Int32(view)#shape=[6]
# [1, 1, 2, 2, 3, 3]

b.insert(2,[15,16])
# => Numo::Int32#shape=[8]
# [1, 1, 15, 16, 2, 2, 3, 3]

b.insert([2,2],[15,16])
# => Numo::Int32#shape=[8]
# [1, 1, 15, 16, 2, 2, 3, 3]

b.insert([2,1],[15,16])
# => Numo::Int32#shape=[8]
# [1, 16, 1, 15, 2, 2, 3, 3]

b.insert([2,0,1],[15,16,17])
# => Numo::Int32#shape=[9]
# [16, 1, 17, 1, 15, 2, 2, 3, 3]

b.insert(2..3, [15, 16])
# => Numo::Int32#shape=[8]
# [1, 1, 15, 2, 16, 2, 3, 3]

b.insert(2, [7.13, 0.5])
# => Numo::Int32#shape=[8]
# [1, 1, 7, 0, 2, 2, 3, 3]

x = Numo::DFloat.new(2,4).seq
# => Numo::DFloat#shape=[2,4]
# [[0, 1, 2, 3],
#  [4, 5, 6, 7]]

x.insert([1,3],999,axis:1)
# => Numo::DFloat#shape=[2,6]
# [[0, 999, 1, 2, 999, 3],
#  [4, 999, 5, 6, 999, 7]]


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# File 'lib/numo/narray/extra.rb', line 390

def insert(indice, values, axis: nil)
  if axis
    values = self.class.asarray(values)
    nd = values.ndim
    midx = ([:new] * (ndim - nd)) + ([true] * nd)
    case indice
    when Numeric
      midx[-nd - 1] = true
      midx[axis] = :new
    end
    values = values[*midx]
  else
    values = self.class.asarray(values).flatten
  end
  idx = Int64.asarray(indice)
  nidx = idx.size
  if nidx == 1
    nidx = values.shape[axis || 0]
    idx += Int64.new(nidx).seq
  else
    sidx = idx.sort_index
    idx[sidx] += Int64.new(nidx).seq
  end
  if axis
    bit = Bit.ones(shape[axis] + nidx)
    bit[idx] = 0
    new_shape = shape
    new_shape[axis] += nidx
    a = self.class.zeros(new_shape)
    mdidx = [true] * ndim
    mdidx[axis] = bit.where
    a[*mdidx] = self
    mdidx[axis] = idx
    a[*mdidx] = values
  else
    bit = Bit.ones(size + nidx)
    bit[idx] = 0
    a = self.class.zeros(size + nidx)
    a[bit.where] = flatten
    a[idx] = values
  end
  a
end

#kron(b) ⇒ Numo::NArray

Kronecker product of two arrays.

kron(a,b)[k_0, k_1, ...] = a[i_0, i_1, ...] * b[j_0, j_1, ...]
   where:  k_n = i_n * b.shape[n] + j_n

Examples:

Numo::DFloat[1,10,100].kron([5,6,7])
# => Numo::DFloat#shape=[9]
# [5, 6, 7, 50, 60, 70, 500, 600, 700]

Numo::DFloat[5,6,7].kron([1,10,100])
# => Numo::DFloat#shape=[9]
# [5, 50, 500, 6, 60, 600, 7, 70, 700]

Numo::DFloat.eye(2).kron(Numo::DFloat.ones(2,2))
# => Numo::DFloat#shape=[4,4]
# [[1, 1, 0, 0],
#  [1, 1, 0, 0],
#  [0, 0, 1, 1],
#  [0, 0, 1, 1]]

Parameters:

Returns:



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# File 'lib/numo/narray/extra.rb', line 1321

def kron(b)
  b = NArray.cast(b)
  nda = ndim
  ndb = b.ndim
  shpa = shape
  shpb = b.shape
  adim = ([:new] * (2 * [ndb - nda, 0].max)) + ([true, :new] * nda)
  bdim = ([:new] * (2 * [nda - ndb, 0].max)) + ([:new, true] * ndb)
  shpr = (-[nda, ndb].max..-1).map { |i| (shpa[i] || 1) * (shpb[i] || 1) }
  (self[*adim] * b[*bdim]).reshape(*shpr)
end

#marshal_dump ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1391

static VALUE nary_marshal_dump(VALUE self) {
  VALUE a;

  a = rb_ary_new();
  rb_ary_push(a, INT2FIX(1)); // version
  rb_ary_push(a, na_shape(self));
  rb_ary_push(a, INT2FIX(NA_FLAG0(self)));
  if (rb_obj_class(self) == numo_cRObject) {
    narray_t* na;
    VALUE* ptr;
    size_t offset = 0;
    GetNArray(self, na);
    if (na->type == NARRAY_VIEW_T) {
      if (na_check_contiguous(self) == Qtrue) {
        offset = NA_VIEW_OFFSET(na);
      } else {
        self = rb_funcall(self, id_dup, 0);
      }
    }
    ptr = (VALUE*)na_get_pointer_for_read(self);
    rb_ary_push(a, rb_ary_new4(NA_SIZE(na), ptr + offset));
  } else {
    rb_ary_push(a, nary_to_binary(self));
  }
  RB_GC_GUARD(self);
  return a;
}

#marshal_load(a) ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1426

static VALUE nary_marshal_load(VALUE self, VALUE a) {
  VALUE v;

  if (TYPE(a) != T_ARRAY) {
    rb_raise(rb_eArgError, "marshal argument should be array");
  }
  if (RARRAY_LEN(a) != 4) {
    rb_raise(rb_eArgError, "marshal array size should be 4");
  }
  if (RARRAY_AREF(a, 0) != INT2FIX(1)) {
    rb_raise(
      rb_eArgError,
      "NArray marshal version %d is not supported "
      "(only version 1)",
      NUM2INT(RARRAY_AREF(a, 0))
    );
  }
  na_initialize(self, RARRAY_AREF(a, 1));
  NA_FL0_SET(self, FIX2INT(RARRAY_AREF(a, 2)));
  v = RARRAY_AREF(a, 3);
  if (rb_obj_class(self) == numo_cRObject) {
    narray_t* na;
    char* ptr;
    if (TYPE(v) != T_ARRAY) {
      rb_raise(rb_eArgError, "RObject content should be array");
    }
    GetNArray(self, na);
    if (RARRAY_LEN(v) != (long)NA_SIZE(na)) {
      rb_raise(rb_eArgError, "RObject content size mismatch");
    }
    ptr = na_get_pointer_for_write(self);
    memcpy(ptr, RARRAY_PTR(v), NA_SIZE(na) * sizeof(VALUE));
  } else {
    rb_str_freeze(v);
    nary_store_binary(1, &v, self);
    if (TEST_BYTE_SWAPPED(self)) {
      rb_funcall(na_inplace(self), id_to_host, 0);
      REVERSE_ENDIAN(self); // correct behavior??
    }
  }
  RB_GC_GUARD(a);
  return self;
}

#ndim ⇒ Object Also known as: rank 



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# File 'ext/numo/narray/narray.c', line 739

static VALUE na_ndim(VALUE self) {
  narray_t* na;
  GetNArray(self, na);
  return INT2NUM(na->ndim);
}

#new_fill(value) ⇒ Object

Return an array filled with value with the same shape and type as self.



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# File 'lib/numo/narray/extra.rb', line 21

def new_fill(value)
  self.class.new(*shape).fill(value)
end

#new_narray ⇒ Object

Return an unallocated array with the same shape and type as self.



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# File 'lib/numo/narray/extra.rb', line 6

def new_narray
  self.class.new(*shape)
end

#new_ones ⇒ Object

Return an array of ones with the same shape and type as self.



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# File 'lib/numo/narray/extra.rb', line 16

def new_ones
  self.class.ones(*shape)
end

#new_zeros ⇒ Object

Return an array of zeros with the same shape and type as self.



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# File 'lib/numo/narray/extra.rb', line 11

def new_zeros
  self.class.zeros(*shape)
end

#out_of_place! ⇒ Object Also known as: not_inplace! 



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# File 'ext/numo/narray/narray.c', line 1710

static VALUE na_out_of_place_bang(VALUE self) {
  UNSET_INPLACE(self);
  return self;
}

#outer(b, axis: nil) ⇒ Numo::NArray

Outer product of two arrays. Same as self[false,:new] * b[false,:new,true].

Examples:

a = Numo::DFloat.ones(5)
# => Numo::DFloat#shape=[5]
# [1, 1, 1, 1, 1]

b = Numo::DFloat.linspace(-2,2,5)
# => Numo::DFloat#shape=[5]
# [-2, -1, 0, 1, 2]

a.outer(b)
# => Numo::DFloat#shape=[5,5]
# [[-2, -1, 0, 1, 2],
#  [-2, -1, 0, 1, 2],
#  [-2, -1, 0, 1, 2],
#  [-2, -1, 0, 1, 2],
#  [-2, -1, 0, 1, 2]]

Parameters:

  • b (Numo::NArray)
  • axis (Integer) (defaults to: nil) —

    applied axis (default=-1)

Returns:



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# File 'lib/numo/narray/extra.rb', line 1252

def outer(b, axis: nil)
  b = NArray.cast(b)
  if axis.nil?
    self[false, :new] * (b.ndim == 0 ? b : b[false, :new, true])
  else
    md, nd = [ndim, b.ndim].minmax
    axis = check_axis(axis) - nd
    raise ArgumentError, "axis=#{axis} is out of range" if axis < -md

    adim = [true] * ndim
    adim[axis + ndim + 1, 0] = :new
    bdim = [true] * b.ndim
    bdim[axis + b.ndim, 0] = :new
    self[*adim] * b[*bdim]
  end
end

#percentile(q, axis: nil) ⇒ Numo::NArray

Percentile

Parameters:

  • q (Numo::NArray)
  • axis (Integer) (defaults to: nil) —

    applied axis

Returns:

Raises:

  • (ArgumentError) 


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# File 'lib/numo/narray/extra.rb', line 1274

def percentile(q, axis: nil)
  raise ArgumentError, 'q is out of range' if q < 0 || q > 100

  x = self
  unless axis
    axis = 0
    x = x.flatten
  end

  sorted = x.sort(axis: axis)
  x = q / 100.0 * (sorted.shape[axis] - 1)
  r = x % 1
  i = x.floor
  refs = [true] * sorted.ndim
  refs[axis] = i
  if i == sorted.shape[axis] - 1
    sorted[*refs]
  else
    refs_upper = refs.dup
    refs_upper[axis] = i + 1
    sorted[*refs] + (r * (sorted[*refs_upper] - sorted[*refs]))
  end
end

#rad2deg ⇒ Object

Convert angles from radians to degrees.



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# File 'lib/numo/narray/extra.rb', line 26

def rad2deg
  self * (180 / Math::PI)
end

#repeat(arg, axis: nil) ⇒ Object

Examples:

Numo::NArray[3].repeat(4)
# => Numo::Int32#shape=[4]
# [3, 3, 3, 3]

x = Numo::NArray[[1,2],[3,4]]
# => Numo::Int32#shape=[2,2]
# [[1, 2],
#  [3, 4]]

x.repeat(2)
# => Numo::Int32#shape=[8]
# [1, 1, 2, 2, 3, 3, 4, 4]

x.repeat(3,axis:1)
# => Numo::Int32#shape=[2,6]
# [[1, 1, 1, 2, 2, 2],
#  [3, 3, 3, 4, 4, 4]]

x.repeat([1,2],axis:0)
# => Numo::Int32#shape=[3,2]
# [[1, 2],
#  [3, 4],
#  [3, 4]]


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# File 'lib/numo/narray/extra.rb', line 908

def repeat(arg, axis: nil)
  case axis
  when Integer
    axis = check_axis(axis)
    c = self
  when NilClass
    c = flatten
    axis = 0
  else
    raise ArgumentError, 'invalid axis'
  end
  case arg
  when Integer
    raise ArgumentError, 'argument should be positive integer' if !arg.is_a?(Integer) || arg < 1

    idx = Array.new(c.shape[axis]) { |i| [i] * arg }.flatten
  else
    arg = arg.to_a
    raise ArgumentError, 'repeat size shoud be equal to size along axis' if arg.size != c.shape[axis]

    arg.each do |i|
      raise ArgumentError, 'argument should be non-negative integer' if !i.is_a?(Integer) || i < 0
    end
    idx = arg.each_with_index.map { |a, i| [i] * a }.flatten
  end
  ref = [true] * c.ndim
  ref[axis] = idx
  c[*ref].copy
end

#reshape(*args) ⇒ Object 



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# File 'ext/numo/narray/data.c', line 416

static VALUE na_reshape(int argc, VALUE* argv, VALUE self) {
  size_t* shape;
  narray_t* na;
  VALUE copy;

  shape = ALLOCA_N(size_t, argc);
  na_check_reshape(argc, argv, self, shape);

  copy = rb_funcall(self, rb_intern("dup"), 0);
  GetNArray(copy, na);
  na_setup_shape(na, argc, shape);
  return copy;
}

#reshape!(*args) ⇒ Object 



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# File 'ext/numo/narray/data.c', line 372

static VALUE na_reshape_bang(int argc, VALUE* argv, VALUE self) {
  size_t* shape;
  narray_t* na;
  narray_view_t* na2;
  ssize_t stride;
  stridx_t* stridx;
  int i;

  if (na_check_contiguous(self) == Qfalse) {
    rb_raise(rb_eStandardError, "cannot change shape of non-contiguous NArray");
  }
  shape = ALLOCA_N(size_t, argc);
  na_check_reshape(argc, argv, self, shape);

  GetNArray(self, na);
  if (na->type == NARRAY_VIEW_T) {
    GetNArrayView(self, na2);
    if (na->ndim < argc) {
      stridx = ALLOC_N(stridx_t, argc);
    } else {
      stridx = na2->stridx;
    }
    stride = SDX_GET_STRIDE(na2->stridx[na->ndim - 1]);
    for (i = argc; i--;) {
      SDX_SET_STRIDE(stridx[i], stride);
      stride *= shape[i];
    }
    if (stridx != na2->stridx) {
      xfree(na2->stridx);
      na2->stridx = stridx;
    }
  }
  na_setup_shape(na, argc, shape);
  return self;
}

#reverse(*args) ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1092

static VALUE nary_reverse(int argc, VALUE* argv, VALUE self) {
  int i, nd;
  size_t j, n;
  size_t offset;
  size_t *idx1, *idx2;
  ssize_t stride;
  ssize_t sign;
  narray_t* na;
  narray_view_t *na1, *na2;
  VALUE view;
  VALUE reduce;

  reduce = na_reduce_dimension(argc, argv, 1, &self, 0, 0);

  GetNArray(self, na);
  nd = na->ndim;

  view = na_s_allocate_view(rb_obj_class(self));

  na_copy_flags(self, view);
  GetNArrayView(view, na2);

  na_setup_shape((narray_t*)na2, nd, na->shape);
  na2->stridx = ALLOC_N(stridx_t, nd);

  switch (na->type) {
  case NARRAY_DATA_T:
  case NARRAY_FILEMAP_T:
    stride = nary_element_stride(self);
    offset = 0;
    for (i = nd; i--;) {
      if (na_test_reduce(reduce, i)) {
        offset += (na->shape[i] - 1) * stride;
        sign = -1;
      } else {
        sign = 1;
      }
      SDX_SET_STRIDE(na2->stridx[i], stride * sign);
      stride *= na->shape[i];
    }
    na2->offset = offset;
    na2->data = self;
    break;
  case NARRAY_VIEW_T:
    GetNArrayView(self, na1);
    offset = na1->offset;
    for (i = 0; i < nd; i++) {
      n = na1->base.shape[i];
      if (SDX_IS_INDEX(na1->stridx[i])) {
        idx1 = SDX_GET_INDEX(na1->stridx[i]);
        idx2 = ALLOC_N(size_t, n);
        if (na_test_reduce(reduce, i)) {
          for (j = 0; j < n; j++) {
            idx2[n - 1 - j] = idx1[j];
          }
        } else {
          for (j = 0; j < n; j++) {
            idx2[j] = idx1[j];
          }
        }
        SDX_SET_INDEX(na2->stridx[i], idx2);
      } else {
        stride = SDX_GET_STRIDE(na1->stridx[i]);
        if (na_test_reduce(reduce, i)) {
          offset += (n - 1) * stride;
          SDX_SET_STRIDE(na2->stridx[i], -stride);
        } else {
          na2->stridx[i] = na1->stridx[i];
        }
      }
    }
    na2->offset = offset;
    na2->data = na1->data;
    break;
  }

  return view;
}

#rot90(k = 1, axes = [0, 1]) ⇒ Object

Rotate in the plane specified by axes.

Examples:

a = Numo::Int32.new(2,2).seq
# => Numo::Int32#shape=[2,2]
# [[0, 1],
#  [2, 3]]

a.rot90
# => Numo::Int32(view)#shape=[2,2]
# [[1, 3],
#  [0, 2]]

a.rot90(2)
# => Numo::Int32(view)#shape=[2,2]
# [[3, 2],
#  [1, 0]]

a.rot90(3)
# => Numo::Int32(view)#shape=[2,2]
# [[2, 0],
#  [3, 1]]


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# File 'lib/numo/narray/extra.rb', line 68

def rot90(k = 1, axes = [0, 1])
  case k % 4
  when 0
    view
  when 1
    swapaxes(*axes).reverse(axes[0])
  when 2
    reverse(*axes)
  when 3
    swapaxes(*axes).reverse(axes[1])
  end
end

#row_major? ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1653

static VALUE na_row_major_p(VALUE self) {
  if (TEST_ROW_MAJOR(self))
    return Qtrue;
  else
    return Qfalse;
}

#shape ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 788

static VALUE na_shape(VALUE self) {
  volatile VALUE v;
  narray_t* na;
  size_t i, n, c, s;

  GetNArray(self, na);
  n = NA_NDIM(na);
  if (TEST_COLUMN_MAJOR(self)) {
    c = n - 1;
    s = -1;
  } else {
    c = 0;
    s = 1;
  }
  v = rb_ary_new2(n);
  for (i = 0; i < n; i++) {
    rb_ary_push(v, SIZET2NUM(na->shape[c]));
    c += s;
  }
  return v;
}

#size ⇒ Object Also known as: length, total 



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# File 'ext/numo/narray/narray.c', line 732

static VALUE na_size(VALUE self) {
  narray_t* na;
  GetNArray(self, na);
  return SIZET2NUM(na->size);
}

#split(indices_or_sections, axis: 0) ⇒ Object

Examples:

x = Numo::DFloat.new(9).seq
# => Numo::DFloat#shape=[9]
# [0, 1, 2, 3, 4, 5, 6, 7, 8]

x.split(3)
# => [Numo::DFloat(view)#shape=[3]
# [0, 1, 2],
#  Numo::DFloat(view)#shape=[3]
# [3, 4, 5],
#  Numo::DFloat(view)#shape=[3]
# [6, 7, 8]]

x = Numo::DFloat.new(8).seq
# => Numo::DFloat#shape=[8]
# [0, 1, 2, 3, 4, 5, 6, 7]

x.split([3, 5, 6, 10])
# => [Numo::DFloat(view)#shape=[3]
# [0, 1, 2],
#  Numo::DFloat(view)#shape=[2]
# [3, 4],
#  Numo::DFloat(view)#shape=[1]
# [5],
#  Numo::DFloat(view)#shape=[2]
# [6, 7],
#  Numo::DFloat(view)#shape=[0][]]


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# File 'lib/numo/narray/extra.rb', line 719

def split(indices_or_sections, axis: 0)
  axis = check_axis(axis)
  size_axis = shape[axis]
  case indices_or_sections
  when Integer
    div_axis, mod_axis = size_axis.divmod(indices_or_sections)
    refs = [true] * ndim
    beg_idx = 0
    Array.new(mod_axis) do |_i|
      end_idx = beg_idx + div_axis + 1
      refs[axis] = beg_idx...end_idx
      beg_idx = end_idx
      self[*refs]
    end +
      Array.new(indices_or_sections - mod_axis) do |_i|
        end_idx = beg_idx + div_axis
        refs[axis] = beg_idx...end_idx
        beg_idx = end_idx
        self[*refs]
      end
  when NArray
    split(indices_or_sections.to_a, axis: axis)
  when Array
    refs = [true] * ndim
    fst = 0
    (indices_or_sections + [size_axis]).map do |lst|
      lst = size_axis if lst > size_axis
      refs[axis] = fst < size_axis ? fst...lst : -1...-1
      fst = lst
      self[*refs]
    end
  else
    raise TypeError, 'argument must be Integer or Array'
  end
end

#store_binary(*args) ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1317

static VALUE nary_store_binary(int argc, VALUE* argv, VALUE self) {
  size_t size, str_len, byte_size, offset;
  int narg;
  VALUE vstr, voffset;
  VALUE velmsz;
  narray_t* na;

  narg = rb_scan_args(argc, argv, "11", &vstr, &voffset);
  Check_Type(vstr, T_STRING);
  str_len = RSTRING_LEN(vstr);
  if (narg == 2) {
    offset = NUM2SIZET(voffset);
    if (str_len < offset) {
      rb_raise(rb_eArgError, "offset is larger than string length");
    }
    str_len -= offset;
  } else {
    offset = 0;
  }

  GetNArray(self, na);
  size = NA_SIZE(na);
  velmsz = rb_const_get(rb_obj_class(self), id_element_byte_size);
  if (FIXNUM_P(velmsz)) {
    byte_size = size * NUM2SIZET(velmsz);
  } else {
    byte_size = ceil(size * NUM2DBL(velmsz));
  }
  if (byte_size > str_len) {
    rb_raise(rb_eArgError, "string is too short to store");
  }

  if (OBJ_FROZEN(vstr)) {
    na_set_pointer(self, RSTRING_PTR(vstr) + offset, byte_size);
    rb_ivar_set(self, id_source, vstr);
  } else {
    void* ptr = na_get_pointer_for_write(self);
    memcpy(ptr, RSTRING_PTR(vstr) + offset, byte_size);
  }

  return SIZET2NUM(byte_size);
}

#swap_byte ⇒ Object Also known as: hton 



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# File 'ext/numo/narray/data.c', line 102

static VALUE nary_swap_byte(VALUE self) {
  VALUE v;
  ndfunc_arg_in_t ain[1] = { { Qnil, 0 } };
  ndfunc_arg_out_t aout[1] = { { INT2FIX(0), 0 } };
  ndfunc_t ndf = { iter_swap_byte, FULL_LOOP | NDF_ACCEPT_BYTESWAP, 1, 1, ain, aout };

  v = na_ndloop(&ndf, 1, self);
  if (self != v) {
    na_copy_flags(self, v);
  }
  REVERSE_ENDIAN(v);
  return v;
}

#swapaxes(a1, a2) ⇒ Object 



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# File 'ext/numo/narray/data.c', line 185

static VALUE na_swapaxes(VALUE self, VALUE a1, VALUE a2) {
  int i, j, ndim;
  size_t tmp_shape;
  stridx_t tmp_stridx;
  narray_view_t* na;
  volatile VALUE view;

  view = na_make_view(self);
  GetNArrayView(view, na);

  ndim = na->base.ndim;
  i = check_axis(NUM2INT(a1), ndim);
  j = check_axis(NUM2INT(a2), ndim);

  tmp_shape = na->base.shape[i];
  tmp_stridx = na->stridx[i];
  na->base.shape[i] = na->base.shape[j];
  na->stridx[i] = na->stridx[j];
  na->base.shape[j] = tmp_shape;
  na->stridx[j] = tmp_stridx;

  return view;
}

#tile(*arg) ⇒ Object

Examples:

a = Numo::NArray[0,1,2]
# => Numo::Int32#shape=[3]
# [0, 1, 2]

a.tile(2)
# => Numo::Int32#shape=[6]
# [0, 1, 2, 0, 1, 2]

a.tile(2,2)
# => Numo::Int32#shape=[2,6]
# [[0, 1, 2, 0, 1, 2],
#  [0, 1, 2, 0, 1, 2]]

a.tile(2,1,2)
# => Numo::Int32#shape=[2,1,6]
# [[[0, 1, 2, 0, 1, 2]],
#  [[0, 1, 2, 0, 1, 2]]]

b = Numo::NArray[[1, 2], [3, 4]]
# => Numo::Int32#shape=[2,2]
# [[1, 2],
#  [3, 4]]

b.tile(2)
# => Numo::Int32#shape=[2,4]
# [[1, 2, 1, 2],
#  [3, 4, 3, 4]]

b.tile(2,1)
# => Numo::Int32#shape=[4,2]
# [[1, 2],
#  [3, 4],
#  [1, 2],
#  [3, 4]]

c = Numo::NArray[1,2,3,4]
# => Numo::Int32#shape=[4]
# [1, 2, 3, 4]

c.tile(4,1)
# => Numo::Int32#shape=[4,4]
# [[1, 2, 3, 4],
#  [1, 2, 3, 4],
#  [1, 2, 3, 4],
#  [1, 2, 3, 4]]


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# File 'lib/numo/narray/extra.rb', line 849

def tile(*arg)
  arg.each do |i|
    raise ArgumentError, 'argument should be positive integer' if !i.is_a?(Integer) || i < 1
  end
  ns = arg.size
  nd = ndim
  shp = shape
  new_shp = []
  src_shp = []
  res_shp = []
  (nd - ns).times do
    new_shp << 1
    new_shp << (n = shp.shift)
    src_shp << :new
    src_shp << true
    res_shp << n
  end
  (ns - nd).times do
    new_shp << (m = arg.shift)
    new_shp << 1
    src_shp << :new
    src_shp << :new
    res_shp << m
  end
  [nd, ns].min.times do
    new_shp << (m = arg.shift)
    new_shp << (n = shp.shift)
    src_shp << :new
    src_shp << true
    res_shp << (n * m)
  end
  self.class.new(*new_shp).store(self[*src_shp]).reshape(*res_shp)
end

#to_binary ⇒ Object Also known as: to_string 



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# File 'ext/numo/narray/narray.c', line 1365

static VALUE nary_to_binary(VALUE self) {
  size_t len, offset = 0;
  char* ptr;
  VALUE str;
  narray_t* na;

  GetNArray(self, na);
  if (na->type == NARRAY_VIEW_T) {
    if (na_check_contiguous(self) == Qtrue) {
      offset = NA_VIEW_OFFSET(na);
    } else {
      self = rb_funcall(self, id_dup, 0);
    }
  }
  len = NUM2SIZET(nary_byte_size(self));
  ptr = na_get_pointer_for_read(self);
  str = rb_usascii_str_new(ptr + offset, len);
  RB_GC_GUARD(self);
  return str;
}

#to_c ⇒ Object

Raises:

  • (TypeError) 


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# File 'lib/numo/narray/extra.rb', line 95

def to_c
  # convert to DComplex?
  raise TypeError, "can't convert #{self.class} into Complex" unless size == 1

  Complex(self[0])
end

#to_f ⇒ Object

Raises:

  • (TypeError) 


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# File 'lib/numo/narray/extra.rb', line 88

def to_f
  # convert to DFloat?
  raise TypeError, "can't convert #{self.class} into Float" unless size == 1

  self[0].to_f
end

#to_host ⇒ Object 



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# File 'ext/numo/narray/data.c', line 130

static VALUE nary_to_host(VALUE self) {
  if (TEST_HOST_ORDER(self)) {
    return self;
  }
  return rb_funcall(self, id_swap_byte, 0);
}

#to_i ⇒ Object

Raises:

  • (TypeError) 


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# File 'lib/numo/narray/extra.rb', line 81

def to_i
  # convert to Int?
  raise TypeError, "can't convert #{self.class} into Integer" unless size == 1

  self[0].to_i
end

#to_network ⇒ Object 



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# File 'ext/numo/narray/data.c', line 116

static VALUE nary_to_network(VALUE self) {
  if (TEST_BIG_ENDIAN(self)) {
    return self;
  }
  return rb_funcall(self, id_swap_byte, 0);
}

#to_swapped ⇒ Object 



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# File 'ext/numo/narray/data.c', line 137

static VALUE nary_to_swapped(VALUE self) {
  if (TEST_BYTE_SWAPPED(self)) {
    return self;
  }
  return rb_funcall(self, id_swap_byte, 0);
}

#to_vacs ⇒ Object 



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# File 'ext/numo/narray/data.c', line 123

static VALUE nary_to_vacs(VALUE self) {
  if (TEST_LITTLE_ENDIAN(self)) {
    return self;
  }
  return rb_funcall(self, id_swap_byte, 0);
}

#trace(offset = nil, axis = nil, nan: false) ⇒ Object

Return the sum along diagonals of the array.

If 2-D array, computes the summation along its diagonal with the given offset, i.e., sum of a[i,i+offset]. If more than 2-D array, the diagonal is determined from the axes specified by axis argument. The default is axis=[-2,-1].

Parameters:

  • offset (Integer) (defaults to: nil) —

    (optional, default=0) diagonal offset

  • axis (Array) (defaults to: nil) —

    (optional, default=[-2,-1]) diagonal axis

  • nan (Bool) (defaults to: false) —

    (optional, default=false) nan-aware algorithm, i.e., if true then it ignores nan.



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# File 'lib/numo/narray/extra.rb', line 1176

def trace(offset = nil, axis = nil, nan: false)
  diagonal(offset, axis).sum(nan: nan, axis: -1)
end

#transpose(*args) ⇒ Object 



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# File 'ext/numo/narray/data.c', line 241

static VALUE na_transpose(int argc, VALUE* argv, VALUE self) {
  int ndim, *map, *permute;
  int i, d;
  bool is_positive, is_negative;
  narray_t* na1;

  GetNArray(self, na1);
  ndim = na1->ndim;
  if (ndim < 2) {
    if (argc > 0) {
      rb_raise(rb_eArgError, "unnecessary argument for 1-d array");
    }
    return na_make_view(self);
  }
  map = ALLOCA_N(int, ndim);
  if (argc == 0) {
    for (i = 0; i < ndim; i++) {
      map[i] = ndim - 1 - i;
    }
    return na_transpose_map(self, map);
  }
  // with argument
  if (argc > ndim) {
    rb_raise(rb_eArgError, "more arguments than ndim");
  }
  for (i = 0; i < ndim; i++) {
    map[i] = i;
  }
  permute = ALLOCA_N(int, argc);
  for (i = 0; i < argc; i++) {
    permute[i] = 0;
  }
  is_positive = is_negative = 0;
  for (i = 0; i < argc; i++) {
    if (TYPE(argv[i]) != T_FIXNUM) {
      rb_raise(rb_eArgError, "invalid argument");
    }
    d = FIX2INT(argv[i]);
    if (d >= 0) {
      if (d >= argc) {
        rb_raise(rb_eArgError, "out of dimension range");
      }
      if (is_negative) {
        rb_raise(rb_eArgError, "dimension must be non-negative only or negative only");
      }
      if (permute[d]) {
        rb_raise(rb_eArgError, "not permutation");
      }
      map[i] = d;
      permute[d] = 1;
      is_positive = 1;
    } else {
      if (d < -argc) {
        rb_raise(rb_eArgError, "out of dimension range");
      }
      if (is_positive) {
        rb_raise(rb_eArgError, "dimension must be non-negative only or negative only");
      }
      if (permute[argc + d]) {
        rb_raise(rb_eArgError, "not permutation");
      }
      map[ndim - argc + i] = ndim + d;
      permute[argc + d] = 1;
      is_negative = 1;
    }
  }
  return na_transpose_map(self, map);
}

#tril(k = 0) ⇒ Object

Lower triangular matrix. Return a copy with the elements above the k-th diagonal filled with zero.



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# File 'lib/numo/narray/extra.rb', line 1030

def tril(k = 0)
  dup.tril!(k)
end

#tril!(k = 0) ⇒ Object

Lower triangular matrix. Fill the self elements above the k-th diagonal with zero.

Raises:



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# File 'lib/numo/narray/extra.rb', line 1036

def tril!(k = 0)
  raise NArray::ShapeError, 'must be >= 2-dimensional array' if ndim < 2

  if contiguous?
    idx = triu_indices(k + 1)
    *shp, m, n = shape
    reshape!(*shp, m * n)
    self[false, idx] = 0
    reshape!(*shp, m, n)
  else
    store(tril(k))
  end
end

#tril_indices(k = 0) ⇒ Object

Return the indices for the lower-triangle on and below the k-th diagonal.

Raises:



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# File 'lib/numo/narray/extra.rb', line 1051

def tril_indices(k = 0)
  raise NArray::ShapeError, 'must be >= 2-dimensional array' if ndim < 2

  m, n = shape[-2..]
  NArray.tril_indices(m, n, k)
end

#triu(k = 0) ⇒ Object

Upper triangular matrix. Return a copy with the elements below the k-th diagonal filled with zero.



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# File 'lib/numo/narray/extra.rb', line 993

def triu(k = 0)
  dup.triu!(k)
end

#triu!(k = 0) ⇒ Object

Upper triangular matrix. Fill the self elements below the k-th diagonal with zero.

Raises:



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# File 'lib/numo/narray/extra.rb', line 999

def triu!(k = 0)
  raise NArray::ShapeError, 'must be >= 2-dimensional array' if ndim < 2

  if contiguous?
    *shp, m, n = shape
    idx = tril_indices(k - 1)
    reshape!(*shp, m * n)
    self[false, idx] = 0
    reshape!(*shp, m, n)
  else
    store(triu(k))
  end
end

#triu_indices(k = 0) ⇒ Object

Return the indices for the upper-triangle on and above the k-th diagonal.

Raises:



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# File 'lib/numo/narray/extra.rb', line 1014

def triu_indices(k = 0)
  raise NArray::ShapeError, 'must be >= 2-dimensional array' if ndim < 2

  m, n = shape[-2..]
  NArray.triu_indices(m, n, k)
end

#view ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 970

VALUE
na_make_view(VALUE self) {
  int i, nd;
  size_t j;
  size_t *idx1, *idx2;
  ssize_t stride;
  narray_t* na;
  narray_view_t *na1, *na2;
  volatile VALUE view;

  GetNArray(self, na);
  nd = na->ndim;

  view = na_s_allocate_view(rb_obj_class(self));

  na_copy_flags(self, view);
  GetNArrayView(view, na2);

  na_setup_shape((narray_t*)na2, nd, na->shape);
  na2->stridx = ALLOC_N(stridx_t, nd);

  switch (na->type) {
  case NARRAY_DATA_T:
  case NARRAY_FILEMAP_T:
    stride = nary_element_stride(self);
    for (i = nd; i--;) {
      SDX_SET_STRIDE(na2->stridx[i], stride);
      stride *= na->shape[i];
    }
    na2->offset = 0;
    na2->data = self;
    break;
  case NARRAY_VIEW_T:
    GetNArrayView(self, na1);
    for (i = 0; i < nd; i++) {
      if (SDX_IS_INDEX(na1->stridx[i])) {
        idx1 = SDX_GET_INDEX(na1->stridx[i]);
        idx2 = ALLOC_N(size_t, na1->base.shape[i]);
        for (j = 0; j < na1->base.shape[i]; j++) {
          idx2[j] = idx1[j];
        }
        SDX_SET_INDEX(na2->stridx[i], idx2);
      } else {
        na2->stridx[i] = na1->stridx[i];
      }
    }
    na2->offset = na1->offset;
    na2->data = na1->data;
    break;
  }

  return view;
}

#vsplit(indices_or_sections) ⇒ Object

Split an array into multiple sub-arrays vertically



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# File 'lib/numo/narray/extra.rb', line 756

def vsplit(indices_or_sections)
  split(indices_or_sections, axis: 0)
end