def plot_eigenvectors(eigenvectors,
num_components,
sz,
filename=None,
start_component=0,
rows=None,
cols=None,
title="Subplot",
color=True):
if (rows is None) or (cols is None):
rows = cols = int(math.ceil(np.sqrt(num_components)))
num_components = np.min(num_components, eigenvectors.shape[1])
fig = plt.figure()
for i in range(start_component, num_components):
vi = eigenvectors[0:, i].copy()
vi = minmax(np.asarray(vi), 0, 255, dtype=np.uint8)
vi = vi.reshape(sz)
ax0 = fig.add_subplot(rows, cols, (i - start_component) + 1)
plt.setp(ax0.get_xticklabels(), visible=False)
plt.setp(ax0.get_yticklabels(), visible=False)
plt.title("%s #%d" % (title, i), create_font('Tahoma', 10))
if color:
implot = plt.imshow(np.asarray(vi))
else:
implot = plt.imshow(np.asarray(vi), cmap=cm.grey)
if filename is None:
fig.show()
else:
fig.savefig(filename, format="png", transparent=False)
def plot_gray(X, sz=None, filename=None):
if not sz is None:
X = X.reshape(sz)
X = minmax(I, 0, 255)
fig = plt.figure()
implot = plt.imshow(np.asarray(Ig), cmap=cm.gray)
if filename is None:
plt.show()
else:
fig.savefig(filename, format="png", transparent=False)
def plot_gray(X, sz=None, filename=None):
if not sz is None:
X = X.reshape(sz)
X = minmax(I, 0, 255)
fig = plt.figure()
implot = plt.imshow(np.asarray(Ig), cmap=cm.gray)
if filename is None:
plt.show()
else:
fig.savefig(filename, format="png", transparent=False)
def plot_eigenvectors(eigenvectors, num_components, sz, filename=None, start_component=0, rows = None, cols = None, title="Subplot", color=True):
if (rows is None) or (cols is None):
rows = cols = int(math.ceil(np.sqrt(num_components)))
num_components = np.min(num_components, eigenvectors.shape[1])
fig = plt.figure()
for i in range(start_component, num_components):
vi = eigenvectors[0:,i].copy()
vi = minmax(np.asarray(vi), 0, 255, dtype=np.uint8)
vi = vi.reshape(sz)
ax0 = fig.add_subplot(rows,cols,(i-start_component)+1)
plt.setp(ax0.get_xticklabels(), visible=False)
plt.setp(ax0.get_yticklabels(), visible=False)
plt.title("%s #%d" % (title, i), create_font('Tahoma',10))
if color:
implot = plt.imshow(np.asarray(vi))
else:
implot = plt.imshow(np.asarray(vi), cmap=cm.grey)
if filename is None:
fig.show()
else:
fig.savefig(filename, format="png", transparent=False)
import normalization as n
datastring = '10 12 3 6 5 25 17 100 1000 98 11 27 78 33 9 18 23 44 690 200'
datastringarray = datastring.split(' ')
data = []
normalizeddata = []
for i in datastringarray:
data.append(float(i))
oldmin = min(data)
oldmax = max(data)
for i in data:
normalizeddata.append(n.minmax(i, oldmin, oldmax, 0, 1))
print(normalizeddata)
def extract(self, X):
return minmax(X, self._low, self._high, self._min, self._max)
