from notebook.services.config import ConfigManager
from IPython.paths import locate_profile
cm = ConfigManager(profile_dir=locate_profile(get_ipython().profile))
cm.update('livereveal', {
'theme': 'beige',
'transition': 'zoom',
'start_slideshow_at': 'selected',
})
Eu posso escrever fórmulas:
$$ \frac{1}{2}$$Ou coisas mais avançadas:
$$\oint\vec{B}\cdot d\vec{S}=0$$Posso incluir links como esse para o Google
Eu posso inserir código diretamente e de forma interativa
1+1
First Header | Second Header |
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Content Cell | Content Cell |
Content Cell | Content Cell |
def f(x):
return x+1
Minhas Lembranças
import numpy as np
import skimage
from skimage import img_as_float
import skimage.filters as skif
from skimage.color import rgb2gray
import skimage.data as skid
import skimage.exposure as skie
from notebook.widgets import interact
import matplotlib.pyplot as plt
import seaborn
%matplotlib inline
plt.style.use('ggplot')
chelsea = skid.chelsea()
chelsea.shape, chelsea.dtype
plt.imshow(chelsea)
plt.axis('off')
img = rgb2gray(chelsea)
p2, p98 = np.percentile(img, (2, 98))
img_rescale = skie.rescale_intensity(img, in_range=(p2, p98))
img_eq = skie.equalize_hist(img)
img_adapteq = img_as_float(skie.equalize_adapthist(img, clip_limit=0.03))
hist_types = dict([('Contrast stretching', img_rescale),
('Histogram equalization', img_eq),
('Adaptive equalization', img_adapteq)])
@interact(hist_type=list(hist_types.keys()))
def display_result(hist_type):
result = hist_types[hist_type]
# We display the processed grayscale image on the left.
plt.subplot(121)
plt.imshow(result, cmap='gray')
plt.axis('off')
# We display the histogram on the right.
plt.subplot(122)
plt.hist(result.ravel(), bins=np.linspace(0., 1., 256),
histtype='step', color='black')
plt.show()