From b32c465529baa447b8b34b528035b4b0457501b0 Mon Sep 17 00:00:00 2001
From: Anton Akhmerov <anton.akhmerov@gmail.com>
Date: Sat, 7 Sep 2013 20:13:00 +0200
Subject: [PATCH] add logo-generating script to examples
---
examples/logo.py | 99 ++++++++++++++++++++++++++++++++++++++++++++++++
1 file changed, 99 insertions(+)
create mode 100644 examples/logo.py
diff --git a/examples/logo.py b/examples/logo.py
new file mode 100644
index 00000000..c3dcb1f6
--- /dev/null
+++ b/examples/logo.py
@@ -0,0 +1,99 @@
+"""The script generating Kwant logo. In addition to Kwant it also needs Python
+image library (PIL)."""
+
+import Image
+import ImageFont
+import ImageDraw
+import matplotlib
+import numpy as np
+import scipy
+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.
+ sys = kwant.Builder()
+ lat = kwant.lattice.square()
+ sys[(lat(*coord) for coord in np.argwhere(geometry))] = mu_system
+ sys[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
+ sys.attach_lead(lead)
+ sys = sys.finalized()
+ ldos = kwant.solvers.default.ldos(sys, 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 = sys.site(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()
--
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