remove old logo

In order not to complicate the licensing situation of Kwant proper,
the new logo will be maintained in a separate repository.

examples/logo.py

-"""The script generating Kwant logo. In addition to Kwant it also needs Python
-image library Pillow."""
-
-from PIL import Image, ImageFont, ImageDraw
-import matplotlib
-import numpy as np
-import scipy.misc
-import kwant
-
-def main():
-    def bbox(array):
-        x, y = np.where(array)
-        return np.min(x), np.max(x), np.min(y), np.max(y)
-
-    # Prepare an image.
-    x = 500
-    y = 160
-    im = Image.new('L', (x, y), 255)
-    draw = ImageDraw.Draw(im)
-
-    # Select a font for the logo and make an image of the logo.  We use a font
-    # available in Debian/Ubuntu, but it can also be downloaded e.g. at
-    # http://www.fonts2u.com/free-monospaced-bold.font
-    fontfile = "/usr/share/fonts/truetype/freefont/FreeMonoBold.ttf"
-    font = ImageFont.truetype(fontfile, 150)
-    draw.text((10, 10), "kwant", font=font)
-
-    dy = 3
-    dx1 = 5
-    dx2 = 3
-    mu_system = 3.8
-
-    # The the coordinates of text.
-    textpos = (1. - np.array(im.getdata()) / 255.).reshape(y, x)
-
-    # Cut away empty space around the letters.
-    xmin, xmax, ymin, ymax = bbox(textpos)
-    textpos = textpos[(xmin - 1) : (xmax + dx2)][:, (ymin - dy) : (ymax + dy)]
-    xmin, xmax, ymin, ymax = bbox(textpos)
-
-    # Add an underscore that touches the lettes.
-    geometry = np.copy(textpos)
-    geometry[(xmax - dx1) : (xmax + dx2)][:, (ymin - dy) : (ymax + dy)] = 1
-
-    # Find x-coordinates separating the letters.
-    nonempty = np.apply_along_axis(np.sum, 0, textpos) > 0
-    borders = np.where(np.diff(nonempty))[0]
-    letters = borders.reshape(-1, 2)
-    gaps = borders[1:-1].reshape(-1, 2)
-
-    # Construct the system, and calculate LDOS.
-    syst = kwant.Builder()
-    lat = kwant.lattice.square()
-    syst[(lat(*coord) for coord in np.argwhere(geometry))] = mu_system
-    syst[lat.neighbors()] = -1
-    lead = kwant.Builder(kwant.TranslationalSymmetry((1, 0)))
-    for y1 in range(ymin - dy, ymax + dy):
-        lead[lat(0, y1)] = mu_system
-    lead[lat.neighbors()[0]] = -3
-    syst.attach_lead(lead)
-    syst = syst.finalized()
-    ldos = kwant.solvers.default.ldos(syst, energy=0)
-
-    # Due to the letters having different overall thickness, the LDOS is larger
-    # in some letters, which makes them have visually different colors. We
-    # adjust this by normalizing each letter to its maximum.
-    def normalize_data(data):
-        sums = []
-        for letter in letters:
-            letter_data = data[:, slice(*letter)]
-            letter_data = letter_data[np.nonzero(letter_data)]
-            sums.append(np.max(letter_data))
-        weights = np.zeros(data.shape[1])
-        for i, letter in enumerate(letters):
-            weights[slice(*letter)] = 1/sums[i]
-        for i, gap in enumerate(gaps):
-            weights[slice(*gap)] = np.linspace(1 / sums[i], 1 / sums[i+1],
-                                               gap[1] - gap[0])
-        new_data = data * weights.reshape(1, -1)
-        new_data /= np.max(new_data)
-        return new_data
-
-    # Here we apply a nonlinear transformation to LDOS to ensure that the
-    # result is not too empty or not too dark.
-    out = np.zeros(textpos.shape)
-    for i, rho in enumerate(ldos**.2):
-        x1, y1 = syst.sites[i].tag
-        out[x1, y1] = rho
-    out = normalize_data(out)
-
-    # We use the original text data as a transparency mask for anti-aliasing.
-    out = matplotlib.cm.PuBu(out, bytes=True)
-    out[:, :, 3] = 255 * geometry
-    scipy.misc.imsave('logo.png', out)
-
-if __name__ == '__main__':
-    main()