1"""
2This module deals with making images (np arrays). It provides drawing
3methods that are difficult to do with the existing Python libraries.
4"""
5
6import numpy as np
7
8
9def blit(im1, im2, pos=None, mask=None, ismask=False):
10    """ Blit an image over another.
11
12    Blits ``im1`` on ``im2`` as position ``pos=(x,y)``, using the
13    ``mask`` if provided. If ``im1`` and ``im2`` are mask pictures
14    (2D float arrays) then ``ismask`` must be ``True``.
15    """
16    if pos is None:
17        pos = [0, 0]
18
19    # xp1,yp1,xp2,yp2 = blit area on im2
20    # x1,y1,x2,y2 = area of im1 to blit on im2
21    xp, yp = pos
22    x1 = max(0, -xp)
23    y1 = max(0, -yp)
24    h1, w1 = im1.shape[:2]
25    h2, w2 = im2.shape[:2]
26    xp2 = min(w2, xp + w1)
27    yp2 = min(h2, yp + h1)
28    x2 = min(w1, w2 - xp)
29    y2 = min(h1, h2 - yp)
30    xp1 = max(0, xp)
31    yp1 = max(0, yp)
32
33    if (xp1 >= xp2) or (yp1 >= yp2):
34        return im2
35
36    blitted = im1[y1:y2, x1:x2]
37
38    new_im2 = +im2
39
40    if mask is None:
41        new_im2[yp1:yp2, xp1:xp2] = blitted
42    else:
43        mask = mask[y1:y2, x1:x2]
44        if len(im1.shape) == 3:
45            mask = np.dstack(3 * [mask])
46        blit_region = new_im2[yp1:yp2, xp1:xp2]
47        new_im2[yp1:yp2, xp1:xp2] = (1.0 * mask * blitted + (1.0 - mask) * blit_region)
48
49    return new_im2.astype('uint8') if (not ismask) else new_im2
50
51
52
53def color_gradient(size,p1,p2=None,vector=None, r=None, col1=0,col2=1.0,
54                   shape='linear', offset = 0):
55    """Draw a linear, bilinear, or radial gradient.
56
57    The result is a picture of size ``size``, whose color varies
58    gradually from color `col1` in position ``p1`` to color ``col2``
59    in position ``p2``.
60
61    If it is a RGB picture the result must be transformed into
62    a 'uint8' array to be displayed normally:
63
64
65    Parameters
66    ------------
67
68    size
69        Size (width, height) in pixels of the final picture/array.
70
71    p1, p2
72        Coordinates (x,y) in pixels of the limit point for ``col1``
73        and ``col2``. The color 'before' ``p1`` is ``col1`` and it
74        gradually changes in the direction of ``p2`` until it is ``col2``
75        when it reaches ``p2``.
76
77    vector
78        A vector [x,y] in pixels that can be provided instead of ``p2``.
79        ``p2`` is then defined as (p1 + vector).
80
81    col1, col2
82        Either floats between 0 and 1 (for gradients used in masks)
83        or [R,G,B] arrays (for colored gradients).
84
85    shape
86        'linear', 'bilinear', or 'circular'.
87        In a linear gradient the color varies in one direction,
88        from point ``p1`` to point ``p2``.
89        In a bilinear gradient it also varies symetrically form ``p1``
90        in the other direction.
91        In a circular gradient it goes from ``col1`` to ``col2`` in all
92        directions.
93
94    offset
95        Real number between 0 and 1 indicating the fraction of the vector
96        at which the gradient actually starts. For instance if ``offset``
97        is 0.9 in a gradient going from p1 to p2, then the gradient will
98        only occur near p2 (before that everything is of color ``col1``)
99        If the offset is 0.9 in a radial gradient, the gradient will
100        occur in the region located between 90% and 100% of the radius,
101        this creates a blurry disc of radius d(p1,p2).
102
103    Returns
104    --------
105
106    image
107        An Numpy array of dimensions (W,H,ncolors) of type float
108        representing the image of the gradient.
109
110
111    Examples
112    ---------
113
114    >>> grad = color_gradient(blabla).astype('uint8')
115
116    """
117
118    # np-arrayize and change x,y coordinates to y,x
119    w,h = size
120
121    col1 = np.array(col1).astype(float)
122    col2 = np.array(col2).astype(float)
123
124    if shape == 'bilinear':
125        if vector is None:
126            vector = np.array(p2) - np.array(p1)
127
128        m1, m2 = [ color_gradient(size, p1, vector=v, col1 = 1.0, col2 = 0,
129                                 shape = 'linear', offset= offset)
130                            for v in [vector,-vector]]
131
132        arr = np.maximum(m1, m2)
133        if col1.size > 1:
134            arr = np.dstack(3*[arr])
135        return arr*col1 + (1-arr)*col2
136
137
138    p1 = np.array(p1[::-1]).astype(float)
139
140    if vector is None and p2:
141        p2 = np.array(p2[::-1])
142        vector = p2-p1
143    else:
144        vector = np.array(vector[::-1])
145        p2 = p1 + vector
146
147    if vector:
148        norm = np.linalg.norm(vector)
149
150    M = np.dstack(np.meshgrid(range(w),range(h))[::-1]).astype(float)
151
152    if shape == 'linear':
153
154        n_vec = vector/norm**2 # norm 1/norm(vector)
155
156        p1 = p1 + offset*vector
157        arr = (M- p1).dot(n_vec)/(1-offset)
158        arr = np.minimum(1,np.maximum(0,arr))
159        if col1.size > 1:
160            arr = np.dstack(3*[arr])
161        return arr*col1 + (1-arr)*col2
162
163    elif shape == 'radial':
164        if r is None:
165           r = norm
166
167        if r == 0:
168            arr = np.ones((h,w))
169        else:
170            arr = (np.sqrt(((M - p1) ** 2).sum(axis=2))) - offset * r
171            arr = arr / ((1-offset)*r)
172            arr = np.minimum(1.0, np.maximum(0, arr))
173
174        if col1.size > 1:
175            arr = np.dstack(3*[arr])
176        return (1-arr)*col1 + arr*col2
177
178
179def color_split(size,x=None,y=None,p1=None,p2=None,vector=None,
180                             col1=0,col2=1.0, grad_width=0):
181    """Make an image splitted in 2 colored regions.
182
183    Returns an array of size ``size`` divided in two regions called 1 and
184    2 in wht follows, and which will have colors col& and col2
185    respectively.
186
187    Parameters
188    -----------
189
190    x: (int)
191        If provided, the image is splitted horizontally in x, the left
192        region being region 1.
193
194    y: (int)
195        If provided, the image is splitted vertically in y, the top region
196        being region 1.
197
198    p1,p2:
199        Positions (x1,y1),(x2,y2) in pixels, where the numbers can be
200        floats. Region 1 is defined as the whole region on the left when
201        going from ``p1`` to ``p2``.
202
203    p1, vector:
204        ``p1`` is (x1,y1) and vector (v1,v2), where the numbers can be
205        floats. Region 1 is then the region on the left when starting
206        in position ``p1`` and going in the direction given by ``vector``.
207
208    gradient_width
209        If not zero, the split is not sharp, but gradual over a region of
210        width ``gradient_width`` (in pixels). This is preferable in many
211        situations (for instance for antialiasing).
212
213
214    Examples
215    ---------
216
217    >>> size = [200,200]
218    >>> # an image with all pixels with x<50 =0, the others =1
219    >>> color_split(size, x=50, col1=0, col2=1)
220    >>> # an image with all pixels with y<50 red, the others green
221    >>> color_split(size, x=50, col1=[255,0,0], col2=[0,255,0])
222    >>> # An image splitted along an arbitrary line (see below)
223    >>> color_split(size, p1=[20,50], p2=[25,70] col1=0, col2=1)
224
225    """
226
227    if grad_width or ( (x is None) and (y is None)):
228        if p2 is not None:
229            vector = (np.array(p2) - np.array(p1))
230        elif x is not None:
231            vector = np.array([0,-1.0])
232            p1 = np.array([x, 0])
233        elif y is not None:
234            vector = np.array([1.0, 0.0])
235            p1 = np.array([0,y])
236
237        x,y = vector
238        vector = np.array([y,-x]).astype('float')
239        norm = np.linalg.norm(vector)
240        vector = max(0.1, grad_width) * vector / norm
241        return color_gradient(size,p1,vector=vector,
242                              col1 = col1, col2 = col2, shape='linear')
243    else:
244        w, h = size
245        shape = (h, w) if np.isscalar(col1) else (h, w, len(col1))
246        arr = np.zeros(shape)
247        if x:
248            arr[:,:x] = col1
249            arr[:,x:] = col2
250        elif y:
251            arr[:y] = col1
252            arr[y:] = col2
253        return arr
254
255    # if we are here, it means we didn't exit with a proper 'return'
256    print( "Arguments in color_split not understood !" )
257    raise
258
259def circle(screensize, center, radius, col1=1.0, col2=0, blur=1):
260    """ Draw an image with a circle.
261
262    Draws a circle of color ``col1``, on a background of color ``col2``,
263    on a screen of size ``screensize`` at the position ``center=(x,y)``,
264    with a radius ``radius`` but slightly blurred on the border by ``blur``
265    pixels
266    """
267    offset = 1.0*(radius-blur)/radius if radius else 0
268    return color_gradient(screensize,p1=center,r=radius, col1=col1,
269                          col2=col2, shape='radial', offset=offset)
270