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
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
// Copyright 2014-2016 bluss and ndarray developers.
//
// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
// http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
// <LICENSE-MIT or http://opensource.org/licenses/MIT>, at your
// option. This file may not be copied, modified, or distributed
// except according to those terms.

//! Constructor methods for ndarray
//!
//!

use libnum::{Zero, One, Float};

use imp_prelude::*;
use {Shape, StrideShape};
use dimension;
use linspace;
use error::{self, ShapeError, ErrorKind};
use Indexes;
use iterators::{to_vec, to_vec_mapped};

/// Constructor methods for one-dimensional arrays.
///
/// Note that the constructor methods apply to `Array` and `RcArray`,
/// the two array types that have owned storage.
impl<S> ArrayBase<S, Ix1>
    where S: DataOwned
{
    /// Create a one-dimensional array from a vector (no copying needed).
    ///
    /// ```rust
    /// use ndarray::Array;
    ///
    /// let array = Array::from_vec(vec![1., 2., 3., 4.]);
    /// ```
    pub fn from_vec(v: Vec<S::Elem>) -> Self {
        unsafe { Self::from_shape_vec_unchecked(v.len() as Ix, v) }
    }

    /// Create a one-dimensional array from an iterable.
    ///
    /// ```rust
    /// use ndarray::{Array, arr1};
    ///
    /// let array = Array::from_iter((0..5).map(|x| x * x));
    /// assert!(array == arr1(&[0, 1, 4, 9, 16]))
    /// ```
    pub fn from_iter<I>(iterable: I) -> Self
        where I: IntoIterator<Item=S::Elem>
    {
        Self::from_vec(iterable.into_iter().collect())
    }

    /// Create a one-dimensional array from the inclusive interval
    /// `[start, end]` with `n` elements. `F` must be a floating point type.
    ///
    /// ```rust
    /// use ndarray::{Array, arr1};
    ///
    /// let array = Array::linspace(0., 1., 5);
    /// assert!(array == arr1(&[0.0, 0.25, 0.5, 0.75, 1.0]))
    /// ```
    pub fn linspace<F>(start: F, end: F, n: usize) -> Self
        where S: Data<Elem=F>,
              F: Float,
    {
        Self::from_vec(to_vec(linspace::linspace(start, end, n)))
    }

    /// Create a one-dimensional array from the half-open interval
    /// `[start, end)` with elements spaced by `step`. `F` must be a floating point type.
    ///
    /// ```rust
    /// use ndarray::{Array, arr1};
    ///
    /// let array = Array::range(0., 5., 1.);
    /// assert!(array == arr1(&[0., 1., 2., 3., 4.]))
    /// ```
    pub fn range<F>(start: F, end: F, step: F) -> Self
        where S: Data<Elem=F>,
              F: Float,
    {
        Self::from_vec(to_vec(linspace::range(start, end, step)))
    }
}

/// Constructor methods for two-dimensional arrays.
impl<S, A> ArrayBase<S, Ix2>
    where S: DataOwned<Elem=A>,
{
    /// Create an identity matrix of size `n` (square 2D array).
    ///
    /// **Panics** if `n * n` would overflow usize.
    pub fn eye(n: Ix) -> Self
        where S: DataMut,
              A: Clone + Zero + One,
    {
        let mut eye = Self::zeros((n, n));
        for a_ii in eye.diag_mut() {
            *a_ii = A::one();
        }
        eye
    }
}

macro_rules! size_checked_unwrap {
    ($dim:expr) => {
        match $dim.size_checked() {
            Some(sz) => sz,
            None => panic!("ndarray: Shape too large, number of elements overflows usize"),
        }
    }
}

/// Constructor methods for n-dimensional arrays.
impl<S, A, D> ArrayBase<S, D>
    where S: DataOwned<Elem=A>,
          D: Dimension,
{
    /// Create an array with copies of `elem`, shape `shape`.
    ///
    /// **Panics** if the number of elements in `shape` would overflow usize.
    ///
    /// ```
    /// use ndarray::{Array, arr3, ShapeBuilder};
    ///
    /// let a = Array::from_elem((2, 2, 2), 1.);
    ///
    /// assert!(
    ///     a == arr3(&[[[1., 1.],
    ///                  [1., 1.]],
    ///                 [[1., 1.],
    ///                  [1., 1.]]])
    /// );
    /// assert!(a.strides() == &[4, 2, 1]);
    ///
    /// let b = Array::from_elem((2, 2, 2).f(), 1.);
    /// assert!(b.strides() == &[1, 2, 4]);
    /// ```
    pub fn from_elem<Sh>(shape: Sh, elem: A) -> Self
        where A: Clone,
              Sh: Into<Shape<D>>,
    {
        // Note: We don't need to check the case of a size between
        // isize::MAX -> usize::MAX; in this case, the vec constructor itself
        // panics.
        let shape = shape.into();
        let size = size_checked_unwrap!(shape.dim);
        let v = vec![elem; size];
        unsafe { Self::from_shape_vec_unchecked(shape, v) }
    }

    /// Create an array with zeros, shape `shape`.
    ///
    /// **Panics** if the number of elements in `shape` would overflow usize.
    pub fn zeros<Sh>(shape: Sh) -> Self
        where A: Clone + Zero,
              Sh: Into<Shape<D>>,
    {
        Self::from_elem(shape, A::zero())
    }

    /// Create an array with default values, shape `shape`
    ///
    /// **Panics** if the number of elements in `shape` would overflow usize.
    pub fn default<Sh>(shape: Sh) -> Self
        where A: Default,
              Sh: Into<Shape<D>>,
    {
        let shape = shape.into();
        let v = to_vec((0..shape.dim.size()).map(|_| A::default()));
        unsafe { Self::from_shape_vec_unchecked(shape, v) }
    }

    /// Create an array with values created by the function `f`.
    ///
    /// The elements are visited in arbitirary order.
    ///
    /// **Panics** if the number of elements in `shape` would overflow usize.
    pub fn from_shape_fn<Sh, F>(shape: Sh, f: F) -> Self
        where Sh: Into<Shape<D>>,
              F: FnMut(D) -> A,
    {
        let shape = shape.into();
        let v = to_vec_mapped(Indexes::new(shape.dim.clone()), f);
        unsafe { Self::from_shape_vec_unchecked(shape, v) }
    }

    /// Create an array with the given shape from a vector. (No cloning of
    /// elements needed.)
    ///
    /// ---- 
    ///
    /// For a contiguous c- or f-order shape, the following applies:
    ///
    /// **Errors** if `shape` does not correspond to the number of elements in `v`.
    ///
    /// ---- 
    ///
    /// For custom strides, the following applies:
    ///
    /// **Errors** if strides and dimensions can point out of bounds of `v`.<br>
    /// **Errors** if strides allow multiple indices to point to the same element.
    ///
    /// ```
    /// use ndarray::prelude::*;
    ///
    /// let a = Array::from_shape_vec((2, 2), vec![1., 2., 3., 4.]);
    /// assert!(a.is_ok());
    ///
    /// let b = Array::from_shape_vec((2, 2).strides((1, 2)),
    ///                                    vec![1., 2., 3., 4.]).unwrap();
    /// assert!(
    ///     b == arr2(&[[1., 3.],
    ///                 [2., 4.]])
    /// );
    /// ```
    pub fn from_shape_vec<Sh>(shape: Sh, v: Vec<A>) -> Result<Self, ShapeError>
        where Sh: Into<StrideShape<D>>,
    {
        // eliminate the type parameter Sh as soon as possible
        Self::from_shape_vec_impl(shape.into(), v)
    }

    fn from_shape_vec_impl(shape: StrideShape<D>, v: Vec<A>) -> Result<Self, ShapeError>
    {
        if shape.custom {
            Self::from_vec_dim_stride(shape.dim, shape.strides, v)
        } else {
            let dim = shape.dim;
            let strides = shape.strides;
            if dim.size_checked() != Some(v.len()) {
                return Err(error::incompatible_shapes(&v.len(), &dim));
            }
            unsafe { Ok(Self::from_vec_dim_stride_unchecked(dim, strides, v)) }
        }
    }

    /// Create an array from a vector and interpret it according to the
    /// provided dimensions and strides. (No cloning of elements needed.)
    ///
    /// Unsafe because dimension and strides are unchecked.
    pub unsafe fn from_shape_vec_unchecked<Sh>(shape: Sh, v: Vec<A>) -> Self
        where Sh: Into<StrideShape<D>>,
    {
        let shape = shape.into();
        Self::from_vec_dim_stride_unchecked(shape.dim, shape.strides, v)
    }

    fn from_vec_dim_stride(dim: D, strides: D, v: Vec<A>)
        -> Result<Self, ShapeError>
    {
        dimension::can_index_slice(&v, &dim, &strides).map(|_| {
            unsafe {
                Self::from_vec_dim_stride_unchecked(dim, strides, v)
            }
        })
    }

    unsafe fn from_vec_dim_stride_unchecked(dim: D, strides: D, mut v: Vec<A>)
        -> Self
    {
        // debug check for issues that indicates wrong use of this constructor
        debug_assert!(match dimension::can_index_slice(&v, &dim, &strides) {
            Ok(_) => true,
            Err(ref e) => match e.kind() {
                ErrorKind::OutOfBounds => false,
                ErrorKind::RangeLimited => false,
                _ => true,
            }
        });
        ArrayBase {
            ptr: v.as_mut_ptr(),
            data: DataOwned::new(v),
            strides: strides,
            dim: dim
        }
    }

}