Class: Numo::NArray

Inherits:
Object
  • Object
show all
Defined in:
ext/numo/narray/narray.c,
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, Step, ValueError

Constant Summary collapse

VERSION = 
rb_str_new2(NARRAY_VERSION)
@@warn_slow_dot = 
false

Class Method Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(shape) ⇒ Numo::NArray #initialize(size0, size1, ...) ⇒ Numo::NArray

Constructs an instance of NArray class using the given and shape or sizes. Note that NArray itself is an abstract super class and not suitable to create instances. Use Typed Subclasses of NArray (DFloat, Int32, etc) to create instances. This method does not allocate memory for array data. Memory is allocated on write method such as #fill, #store, #seq, etc.

Examples:

i = Numo::Int64.new([2,4,3])
#=> Numo::Int64#shape=[2,4,3](empty)

f = Numo::DFloat.new(3,4)
#=> Numo::DFloat#shape=[3,4](empty)

f.fill(2)
#=> Numo::DFloat#shape=[3,4]
# [[2, 2, 2, 2],
#  [2, 2, 2, 2],
#  [2, 2, 2, 2]]

x = Numo::NArray.new(5)
#=> in `new': allocator undefined for Numo::NArray (TypeError)
#   	from t.rb:9:in `<main>'

Parameters:

  • shape (Array) —

    (array of sizes along each dimension)

  • sizeN (Integer) —

    (size along Nth-dimension)



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# File 'ext/numo/narray/narray.c', line 367

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 = 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

.[](elements) ⇒ NArray

Generate NArray object. NArray datatype is automatically selected.

Parameters:

  • elements (Numeric, Array)

Returns:



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# File 'ext/numo/narray/array.c', line 506

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);
}

.array_type(ary) ⇒ Object 



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# File 'ext/numo/narray/array.c', line 493

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

.asarray(a) ⇒ Object 



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# File 'lib/numo/narray/extra.rb', line 162

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 ⇒ Numeric

Returns byte size of one element of NArray.

Returns:

  • (Numeric) —

    byte size.



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# File 'ext/numo/narray/narray.c', line 1239

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 158

def self.cast(a)
  a.kind_of?(NArray) ? a : NArray.array_type(a).cast(a)
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]
p 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 608

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

.concatenate(arrays, axis: 0) ⇒ Object

Examples:

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

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

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

p Numo::NArray.concatenate([a,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 464

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
    if a.ndim > nd
      nd = a.ndim
    end
    a
  end
  if axis < 0
    axis += nd
  end
  if axis < 0 || axis >= nd
    raise ArgumentError,"axis is out of range"
  end
  new_shape = nil
  sum_size = 0
  arrays.each do |a|
    a_shape = a.shape
    if nd != a_shape.size
      a_shape = [1]*(nd-a_shape.size) + a_shape
    end
    sum_size += a_shape.delete_at(axis)
    if new_shape
      if new_shape != a_shape
        raise ShapeError,"shape mismatch"
      end
    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)
    refs[axis] = fst...lst
    result[*refs] = a
  end
  result
end

.debug=(flag) ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1763

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 1098

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]
p 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]]
p 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 591

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

.eye(n) ⇒ Numo::NArray

Returns a NArray with shape=(n,n) whose diagonal elements are 1, otherwise 0.

Examples:

a = Numo::DFloat.eye(3)
=> Numo::DFloat#shape=[3,3]
[[1, 0, 0],
 [0, 1, 0],
 [0, 0, 1]]

Parameters:

  • n (Integer) —

    Size of NArray. Creates 2-D NArray with shape=(n,n)

Returns:



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# File 'ext/numo/narray/narray.c', line 580

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(string, [shape]) ⇒ Numo::NArray

Returns a new 1-D array initialized from binary raw data in a string.

Parameters:

  • string (String) —

    Binary raw data.

  • shape (Array) —

    array of integers representing array shape.

Returns:



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# File 'ext/numo/narray/narray.c', line 1253

static VALUE
nary_s_from_binary(int argc, VALUE *argv, VALUE type)
{
    size_t len, str_len, byte_size;
    size_t *shape;
    char *ptr;
    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 = RARRAY_LEN(vshape);
            if (nd == 0 || nd > NA_MAX_DIMENSION) {
                rb_raise(nary_eDimensionError,"too long or empty shape (%d)", nd);
            }
            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);
    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]
p 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]]
p 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 561

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 ⇒ Integer or nil

Returns the number of cols used for NArray#inspect

Returns:

  • (Integer or nil) —

    the number of cols.



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# File 'ext/numo/narray/narray.c', line 1818

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

.inspect_cols=(cols) ⇒ nil

Set the number of cols used for NArray#inspect

Parameters:

  • cols (Integer or nil) —

    the number of cols

Returns:

  • (nil) 


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# File 'ext/numo/narray/narray.c', line 1833

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 ⇒ Integer or nil

Returns the number of rows used for NArray#inspect

Returns:

  • (Integer or nil) —

    the number of rows.



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# File 'ext/numo/narray/narray.c', line 1788

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

.inspect_rows=(rows) ⇒ nil

Set the number of rows used for NArray#inspect

Parameters:

  • rows (Integer or nil) —

    the number of rows

Returns:

  • (nil) 


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# File 'ext/numo/narray/narray.c', line 1803

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(x1, x2, [n]) ⇒ Numo::NArray

Returns an array of N linearly spaced points between x1 and x2. This singleton method is valid not for NArray class itself but for typed NArray subclasses, e.g., DFloat, Int64.

Examples:

a = Numo::DFloat.linspace(-5,5,7)
=> Numo::DFloat#shape=[7]
[-5, -3.33333, -1.66667, 0, 1.66667, 3.33333, 5]

Parameters:

  • x1 (Numeric) —

    The start value

  • x2 (Numeric) —

    The end value

  • n (Integer) —

    The number of elements. (default is 100).

Returns:



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# File 'ext/numo/narray/narray.c', line 501

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(a, b, [n, base]) ⇒ Numo::NArray

Returns an array of N logarithmically spaced points between 10^a and 10^b. This singleton method is valid not for NArray having logseq method, i.e., DFloat, SFloat, DComplex, and SComplex.

Examples:

Numo::DFloat.logspace(4,0,5,2)
=> Numo::DFloat#shape=[5]
   [16, 8, 4, 2, 1]
Numo::DComplex.logspace(0,1i*Math::PI,5,Math::E)
=> Numo::DComplex#shape=[5]
   [1+4.44659e-323i, 0.707107+0.707107i, 6.12323e-17+1i, -0.707107+0.707107i, ...]

Parameters:

  • a (Numeric) —

    The start value

  • b (Numeric) —

    The end value

  • n (Integer) —

    The number of elements. (default is 50)

  • base (Numeric) —

    The base of log space. (default is 10)

Returns:



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# File 'ext/numo/narray/narray.c', line 543

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) ⇒ Numo::NArray

Generate new unallocated NArray instance with shape and type defined from obj. Numo::NArray.new_like(obj) returns instance whose type is defined from obj. Numo::DFloat.new_like(obj) returns DFloat instance.

Examples:

Numo::NArray.new_like([[1,2,3],[4,5,6]])
=> Numo::Int32#shape=[2,3](empty)
Numo::DFloat.new_like([[1,2],[3,4]])
=> Numo::DFloat#shape=[2,2](empty)
Numo::NArray.new_like([1,2i,3])
=> Numo::DComplex#shape=[3](empty)

Parameters:

Returns:



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# File 'ext/numo/narray/array.c', line 474

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

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

.ones(shape) ⇒ Object .ones(size1, size2, ...) ⇒ Object

Returns a one-filled narray with shape. This singleton method is valid not for NArray class itself but for typed NArray subclasses, e.g., DFloat, Int64.

Examples:

a = Numo::DFloat.ones(3,5)
=> Numo::DFloat#shape=[3,5]
[[1, 1, 1, 1, 1],
 [1, 1, 1, 1, 1],
 [1, 1, 1, 1, 1]]


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# File 'ext/numo/narray/narray.c', line 476

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]]


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# File 'lib/numo/narray/extra.rb', line 185

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

.profile ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 1771

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 1776

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

.step(*args) ⇒ Object 



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

static VALUE
nary_s_step( int argc, VALUE *argv, VALUE mod )
{
    VALUE self = rb_obj_alloc(na_cStep);
    step_initialize(argc, argv, self);
    return self;
}

.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 1082

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 uppler-triangle on and above the k-th diagonal.



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# File 'lib/numo/narray/extra.rb', line 1043

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 1175

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]
p 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]]
p 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 538

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

.zeros(shape) ⇒ Object .zeros(size1, size2, ...) ⇒ Object

Returns a zero-filled narray with shape. This singleton method is valid not for NArray class itself but for typed NArray subclasses, e.g., DFloat, Int64.

Examples:

a = Numo::DFloat.zeros(3,5)
=> Numo::DFloat#shape=[3,5]
[[0, 0, 0, 0, 0],
 [0, 0, 0, 0, 0],
 [0, 0, 0, 0, 0]]


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# File 'ext/numo/narray/narray.c', line 452

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) ⇒ Boolean

Equality of self and other in view of numerical array. i.e., both arrays have same shape and corresponding elements are equal.

Parameters:

  • other (Object)

Returns:

  • (Boolean) —

    true if self and other is equal.



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# File 'ext/numo/narray/narray.c', line 1851

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;
        }
    }
    vbool = rb_funcall(self, id_eq, 1, other);
    return (rb_funcall(vbool, id_count_false, 0)==INT2FIX(0)) ? Qtrue : Qfalse;
}

#append(other, axis: nil) ⇒ Object

Append values to the end of an narray.

Examples:

a = Numo::DFloat[1, 2, 3]
p 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]]
p 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]]
p 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 278

def append(other,axis:nil)
  other = self.class.cast(other)
  if axis
    if ndim != other.ndim
      raise DimensionError, "dimension mismatch"
    end
    return concatenate(other,axis:axis)
  else
    a = self.class.zeros(size+other.size)
    a[0...size] = self[true]
    a[size..-1] = other[true]
    return a
  end
end

#at(*indices) ⇒ Numo::NArray

Multi-dimensional array indexing. Same as [] for one-dimensional NArray. Similar to numpy’s tuple indexing, i.e., ‘a[,[3,4,..]]` (This method will be rewritten in C)

Examples:

p x = Numo::DFloat.new(3,3,3).seq
# Numo::DFloat#shape=[3,3,3]
# [[[0, 1, 2],
#   [3, 4, 5],
#   [6, 7, 8]],
#  [[9, 10, 11],
#   [12, 13, 14],
#   [15, 16, 17]],
#  [[18, 19, 20],
#   [21, 22, 23],
#   [24, 25, 26]]]

p x.at([0,1,2],[0,1,2],[-1,-2,-3])
# Numo::DFloat(view)#shape=[3]
# [2, 13, 24]

Returns:



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# File 'lib/numo/narray/extra.rb', line 67

def at(*indices)
  if indices.size != ndim
    raise DimensionError, "argument length does not match dimension size"
  end
  idx = nil
  stride = 1
  (indices.size-1).downto(0) do |i|
    ix = Int64.cast(indices[i])
    if ix.ndim != 1
      raise DimensionError, "index array is not one-dimensional"
    end
    ix[ix < 0] += shape[i]
    if ((ix < 0) & (ix >= shape[i])).any?
      raise IndexError, "index array is out of range"
    end
    if idx
      if idx.size != ix.size
        raise ShapeError, "index array sizes mismatch"
      end
      idx += ix * stride
      stride *= shape[i]
    else
      idx = ix
      stride = shape[i]
    end
  end
  self[idx]
end

#byte_size ⇒ Integer

Returns total byte size of NArray.

Returns:

  • (Integer) —

    byte size.



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# File 'ext/numo/narray/narray.c', line 1221

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? ⇒ Boolean Also known as: network_order?

Return true if byte swapped.

Returns:

  • (Boolean) 


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# File 'ext/numo/narray/narray.c', line 1700

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

#cast_to(datatype) ⇒ Numo::NArray

Cast self to another NArray datatype.

Parameters:

  • datatype (Class) —

    NArray datatype.

Returns:



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# File 'ext/numo/narray/narray.c', line 1485

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

#coerce(other) ⇒ Array

Returns an array containing other and self, both are converted to upcasted type of NArray. Note that NArray has distinct UPCAST mechanism. Coerce is used for operation between non-NArray and NArray.

Parameters:

  • other (Object) —

    numeric object.

Returns:

  • (Array) —

    NArray-casted [other,self]



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# File 'ext/numo/narray/narray.c', line 1206

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? ⇒ Boolean

Return true if column major.

Returns:

  • (Boolean) 


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# File 'ext/numo/narray/narray.c', line 1677

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

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

Examples:

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

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

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

p 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 663

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

#contiguous? ⇒ Boolean

Returns:

  • (Boolean) 


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# File 'ext/numo/narray/narray.c', line 900

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) ⇒ Object

under construction



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# File 'lib/numo/narray/extra.rb', line 1251

def cov(y=nil, ddof:1, fweights:nil, aweights:nil)
  if y
    m = NArray.vstack([self,y])
  else
    m = self
  end
  w = nil
  if fweights
    f = fweights
    w = f
  end
  if aweights
    a = aweights
    w = w ? w*a : a
  end
  if w
    w_sum = w.sum(axis:-1, keepdims:true)
    if ddof == 0
      fact = w_sum
    elsif aweights.nil?
      fact = w_sum - ddof
    else
      wa_sum = (w*a).sum(axis:-1, keepdims:true)
      fact = w_sum - ddof * wa_sum / w_sum
    end
    if (fact <= 0).any?
      raise StandardError,"Degrees of freedom <= 0 for slice"
    end
  else
    fact = m.shape[-1] - ddof
  end
  if w
    m -= (m*w).sum(axis:-1, keepdims:true) / w_sum
    mw = m*w
  else
    m -= m.mean(axis:-1, keepdims:true)
    mw = m
  end
  mt = (m.ndim < 2) ? m : m.swapaxes(-2,-1)
  mw.dot(mt.conj) / fact
end

#debug_info ⇒ Object 



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# File 'ext/numo/narray/narray.c', line 128

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 30

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

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

p 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 313

def delete(indice,axis=nil)
  if axis
    bit = Bit.ones(shape[axis])
    bit[indice] = 0
    idx = [true]*ndim
    idx[axis] = bit.where
    return self[*idx].copy
  else
    bit = Bit.ones(size)
    bit[indice] = 0
    return 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 1105

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.



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# File 'lib/numo/narray/extra.rb', line 1089

def diag_indices(k=0)
  if ndim < 2
    raise NArray::ShapeError, "must be >= 2-dimensional array"
  end
  m,n = shape[-2..-1]
  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]]

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 615

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:

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

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

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

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

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

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


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# File 'lib/numo/narray/extra.rb', line 983

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

#dot(b) ⇒ Numo::NArray

Dot product of two arrays.

Parameters:

Returns:



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# File 'lib/numo/narray/extra.rb', line 1134

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 = 200000
          am,an = shape[-2..-1]
          bm,bn = b.shape[-2..-1]
          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.\n\n"
          end
        end
        self[false,:new].mulsum(b[false,:new,true,true], axis:-2)
      end
    end
  end
end

#dsplit(indices_or_sections) ⇒ Object 



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# File 'lib/numo/narray/extra.rb', line 809

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

#each_over_axis(axis = 0) ⇒ Object

Iterate over an axis @ example

> 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 238

def each_over_axis(axis=0)
  unless block_given?
    return to_enum(:each_over_axis,axis)
  end
  if ndim == 0
    if axis != 0
      raise ArgumentError,"axis=#{axis} is invalid"
    end
    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? ⇒ Boolean

Returns true if self.size == 0.

Returns:

  • (Boolean) 


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# File 'ext/numo/narray/narray.c', line 719

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

#expand_dims(dim) ⇒ Numo::NArray

Expand the shape of an array. Insert a new axis with size=1 at a given dimension.

Parameters:

  • dim (Integer) —

    dimension at which new axis is inserted.

Returns:



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# File 'ext/numo/narray/narray.c', line 1033

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 570

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 36

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 42

def flipud
  reverse(0)
end

#fortran_contiguous? ⇒ Boolean

Returns:

  • (Boolean) 


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# File 'ext/numo/narray/narray.c', line 925

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

Release memory for array data. Ignored for NArray-view. This method is useful to free memory of referenced (i.e., GC does not work) but unused NArray object.



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# File 'ext/numo/narray/narray.c', line 737

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? ⇒ Boolean Also known as: little_endian?, vacs_order?

Return true if not byte swapped.

Returns:

  • (Boolean) 


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

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

#hsplit(indices_or_sections) ⇒ Object 



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# File 'lib/numo/narray/extra.rb', line 805

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

#initialize_copy(other) ⇒ Numo::NArray

Replaces the contents of self with the contents of other narray. Used in dup and clone method.

Parameters:

Returns:



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# File 'ext/numo/narray/narray.c', line 424

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 1173

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

#inplace ⇒ Numo::NArray

Returns view of narray with inplace flagged.

Returns:



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# File 'ext/numo/narray/narray.c', line 1722

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

#inplace! ⇒ Numo::NArray

Set inplace flag to self.

Returns:



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# File 'ext/numo/narray/narray.c', line 1734

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

#inplace? ⇒ Boolean

Return true if inplace flagged.

Returns:

  • (Boolean) 


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# File 'ext/numo/narray/narray.c', line 1743

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:

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

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

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

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

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

p 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]]

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

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

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

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

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

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

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

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

p 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 398

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 = 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] = self.flatten
    a[idx] = values
  end
  return 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 1237

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 ⇒ Array

Dump marshal data.

Returns:

  • (Array) —

    Array containing marshal data.



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# File 'ext/numo/narray/narray.c', line 1400

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(data) ⇒ nil

Load marshal data.

Returns:

  • (nil) 


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# File 'ext/numo/narray/narray.c', line 1437

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 {
        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

method: size() – returns the total number of typeents



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# File 'ext/numo/narray/narray.c', line 706

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 20

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 5

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 15

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 10

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

#out_of_place! ⇒ Numo::NArray Also known as: not_inplace!

Unset inplace flag to self.

Returns:



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# File 'ext/numo/narray/narray.c', line 1755

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 * b`.

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 1198

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
    if axis < -md
      raise ArgumentError,"axis=#{axis} is out of range"
    end
    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

#rad2deg ⇒ Object

Convert angles from radians to degrees.



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# File 'lib/numo/narray/extra.rb', line 25

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

#repeat(arg, axis: nil) ⇒ Object

Examples:

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

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

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

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

p 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 921

def repeat(arg,axis:nil)
  case axis
  when Integer
    axis = check_axis(axis)
    c = self
  when NilClass
    c = self.flatten
    axis = 0
  else
    raise ArgumentError,"invalid axis"
  end
  case arg
  when Integer
    if !arg.kind_of?(Integer) || arg<1
      raise ArgumentError,"argument should be positive integer"
    end
    idx = c.shape[axis].times.map{|i| [i]*arg}.flatten
  else
    arg = arg.to_a
    if arg.size != c.shape[axis]
      raise ArgumentError,"repeat size shoud be equal to size along axis"
    end
    arg.each do |i|
      if !i.kind_of?(Integer) || i<0
        raise ArgumentError,"argument should be non-negative integer"
      end
    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(size0, size1, ...) ⇒ Numo::NArray

Copy and change the shape of NArray. Returns a copied NArray.

Parameters:

  • sizeN (Integer) —

    new shape

Returns:



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# File 'ext/numo/narray/data.c', line 438

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!(size0, size1, ...) ⇒ Numo::NArray

Change the shape of self NArray without coping. Raise exception if self is non-contiguous.

Parameters:

  • sizeN (Integer) —

    new shape

Returns:



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# File 'ext/numo/narray/data.c', line 391

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([dim0,dim1,..]) ⇒ Object

Return reversed view along specified dimeinsion



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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:

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

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

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

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


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# File 'lib/numo/narray/extra.rb', line 117

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? ⇒ Boolean

Return true if row major.

Returns:

  • (Boolean) 


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# File 'ext/numo/narray/narray.c', line 1688

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

#shape ⇒ Object

method: shape() – returns shape, array of the size of dimensions



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

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

method: size() – returns the total number of typeents



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# File 'ext/numo/narray/narray.c', line 696

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

#split(indices_or_sections, axis: 0) ⇒ Object

Examples:

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

pp 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]]

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

pp 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 732

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
    mod_axis.times.map do |i|
      end_idx = beg_idx + div_axis + 1
      refs[axis] = beg_idx ... end_idx
      beg_idx = end_idx
      self[*refs]
    end +
    (indices_or_sections-mod_axis).times.map 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(string, [offset]) ⇒ Integer

Returns a new 1-D array initialized from binary raw data in a string.

Parameters:

  • string (String) —

    Binary raw data.

  • (optional) (Integer) —

    offset Byte offset in string.

Returns:

  • (Integer) —

    stored length.



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# File 'ext/numo/narray/narray.c', line 1327

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

    narg = rb_scan_args(argc,argv,"11",&vstr,&voffset);
    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");
    }

    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 110

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(axis1, axis2) ⇒ Numo::NArray

Interchange two axes.

Examples:

x = Numo::Int32[[1,2,3]]

p x.swapaxes(0,1)
# Numo::Int32(view)#shape=[3,1]
# [[1],
#  [2],
#  [3]]

p x = Numo::Int32[[[0,1],[2,3]],[[4,5],[6,7]]]
# Numo::Int32#shape=[2,2,2]
# [[[0, 1],
#   [2, 3]],
#  [[4, 5],
#   [6, 7]]]

p x.swapaxes(0,2)
# Numo::Int32(view)#shape=[2,2,2]
# [[[0, 4],
#   [2, 6]],
#  [[1, 5],
#   [3, 7]]]

Parameters:

  • axis1 (Integer)
  • axis2 (Integer)

Returns:



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# File 'ext/numo/narray/data.c', line 209

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:

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

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

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

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

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

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

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

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

p 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 860

def tile(*arg)
  arg.each do |i|
    if !i.kind_of?(Integer) || i<1
      raise ArgumentError,"argument should be positive integer"
    end
  end
  ns = arg.size
  nd = self.ndim
  shp = self.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 ⇒ String Also known as: to_string

Returns string containing the raw data bytes in NArray.

Returns:

  • (String) —

    String object containing binary raw data.



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# File 'ext/numo/narray/narray.c', line 1372

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 



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# File 'lib/numo/narray/extra.rb', line 148

def to_c
  if size==1
    Complex(self[0])
  else
    # convert to DComplex?
    raise TypeError, "can't convert #{self.class} into Complex"
  end
end

#to_f ⇒ Object 



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# File 'lib/numo/narray/extra.rb', line 139

def to_f
  if size==1
    self[0].to_f
  else
    # convert to DFloat?
    raise TypeError, "can't convert #{self.class} into Float"
  end
end

#to_host ⇒ Object 



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# File 'ext/numo/narray/data.c', line 146

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 



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# File 'lib/numo/narray/extra.rb', line 130

def to_i
  if size==1
    self[0].to_i
  else
    # convert to Int?
    raise TypeError, "can't convert #{self.class} into Integer"
  end
end

#to_network ⇒ Object 



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# File 'ext/numo/narray/data.c', line 128

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 155

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 137

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`. If more than 2-D array, the diagonal is determined from the axes specified by axis argument. The default is axis=.

Parameters:

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

    (optional, default=0) diagonal offset

  • axis (Array) (defaults to: nil) —

    (optional, default=) 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 1123

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 265

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 1051

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.



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# File 'lib/numo/narray/extra.rb', line 1057

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



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# File 'lib/numo/narray/extra.rb', line 1073

def tril_indices(k=0)
  if ndim < 2
    raise NArray::ShapeError, "must be >= 2-dimensional array"
  end
  m,n = shape[-2..-1]
  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 1012

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.



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# File 'lib/numo/narray/extra.rb', line 1018

def triu!(k=0)
  if ndim < 2
    raise NArray::ShapeError, "must be >= 2-dimensional array"
  end
  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 uppler-triangle on and above the k-th diagonal.



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# File 'lib/numo/narray/extra.rb', line 1034

def triu_indices(k=0)
  if ndim < 2
    raise NArray::ShapeError, "must be >= 2-dimensional array"
  end
  m,n = shape[-2..-1]
  NArray.triu_indices(m,n,k)
end

#view ⇒ Object

Return view of NArray



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# File 'ext/numo/narray/narray.c', line 966

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

Examples:

p 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]]

pp 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]]]

pp 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 801

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