def testfilenumber0(self, mock_exists, mock_glob):
# The second file - filename already exists
mock_exists.return_value = True
mock_glob.return_value = ['testfolder/test/testfile.csv']
filename = 'testfolder/test/testfile.csv'
new_filename = file_namer.name_file(filename)
self.assertEqual('testfolder/test/testfile-1.csv', new_filename)
def testfilenumber1(self, mock_exists, mock_glob):
# A filename ending with the digit 1
mock_exists.return_value = True
mock_glob.return_value = ['testfolder/test/testfile1.csv']
filename = 'testfolder/test/testfile1.csv'
new_filename = file_namer.name_file(filename)
self.assertEqual('testfolder/test/testfile1-1.csv', new_filename)
def testdifffile(self, mock_exists, mock_glob):
# First file - filename does not yet exist
mock_exists.return_value = False
mock_glob.return_value = []
filename = 'testfolder/test/differentname.csv'
new_filename = file_namer.name_file(filename)
self.assertEqual('testfolder/test/differentname.csv', new_filename)
def testnofolder(self, mock_exists, mock_glob):
# File name has no folders in it
mock_exists.return_value = True
mock_glob.return_value = []
filename = 'testfile.csv'
new_filename = file_namer.name_file(filename)
self.assertEqual('testfile-1.csv', new_filename)
def save_image_scale(self, filename):
if self.Image.calibration==0:
print("You gave me no scale! I can't do it!")
return
self.axis.yaxis.set_major_locator(NullLocator())
self.axis.xaxis.set_major_locator(NullLocator())
filename = file_namer.name_file(filename)
plt.savefig(filename, transparent=True, bbox_inches='tight', pad_inches=0)
def testfileorder2(self, mock_exists, mock_glob):
# Order of files in the folder is not sequential
mock_exists.return_value = True
mock_glob.return_value=[
'testfolder/test/testfile-1.csv', 'testfolder/test/testfile.csv']
filename = 'testfolder/test/testfile.csv'
new_filename = file_namer.name_file(filename)
self.assertEqual('testfolder/test/testfile-2.csv', new_filename)
def testfileorder1(self, mock_exists, mock_glob):
# Third filename
mock_exists.return_value = True
mock_glob.return_value=[
'testfolder/test/testfile.csv', 'testfolder/test/testfile-1.csv']
filename = 'testfolder/test/testfile.csv'
new_filename = file_namer.name_file(filename)
self.assertEqual('testfolder/test/testfile-2.csv', new_filename)
def save_colourbar(self, filename):
extent_colourbar = self.colourbar_axis.get_window_extent().transformed(plt.gcf().dpi_scale_trans.inverted())
extent_toptick = self.colourbar_axis.yaxis.get_ticklabels()[0].get_window_extent().transformed(plt.gcf().dpi_scale_trans.inverted())
extent_bottomtick = self.colourbar_axis.yaxis.get_ticklabels()[-1].get_window_extent().transformed(plt.gcf().dpi_scale_trans.inverted())
new_extent = np.array([np.min((extent_colourbar.get_points()[0,:], extent_toptick.get_points()[0,:], extent_bottomtick.get_points()[0,:]), axis=0),
np.max((extent_colourbar.get_points()[1,:], extent_toptick.get_points()[1,:], extent_bottomtick.get_points()[1,:]), axis=0)])
extent_colourbar.set_points(new_extent)
filename = file_namer.name_file(filename)
# print('Saving colourbar as...', filename)
plt.gcf().savefig(filename, bbox_inches=extent_colourbar, transparent=True)
def SaveImgAsPNG(self, filename, clim, cmap=None):
# r_min = max(clim[0], self.Imglim[0])
# r_max = min(clim[1], self.Imglim[1])
r_min = clim[0]
r_max = clim[1]
filename = file_namer.name_file(filename)
writefile = open(filename, 'wb')
if type(self.data) == np.ma.MaskedArray:
writeImage = np.empty((self.size[0], self.size[1] * 2))
writeImage[:, 0::2] = np.round(
255 * (self.data.data.astype(float) - r_min) / float(
(r_max - r_min))) * np.invert(self.data.mask)
writeImage[:, 1::2] = np.invert(self.data.mask) * 255
alph = True
else:
writeImage = np.round(255 * (self.data.astype(float) - r_min) /
float((r_max - r_min)))
alph = False
if cmap is not None:
colours = (cmap(np.arange(0, 256)) * 255).astype(int)
colourstuple = map(tuple, colours)
if np.all(
np.equal(np.array(colours[:, 0]), np.array(colours[:, 1]),
np.array(colours[:, 2]))):
writer = png.Writer(size=self.size[::-1],
greyscale=True,
alpha=alph)
print('I am so gray...')
else:
writer = png.Writer(size=self.size[::-1],
palette=colourstuple,
bitdepth=8)
if type(self.data) == np.ma.MaskedArray:
writeImage = np.round(
255 * (self.data.data.astype(float) - r_min) / float(
(r_max - r_min))) * np.invert(self.data.mask)
else:
writeImage = np.round(
255 * (self.data.astype(float) - r_min) / float(
(r_max - r_min)))
print('Well, colour me pink!')
else:
writer = png.Writer(size=self.size[::-1],
greyscale=True,
alpha=alph)
writeImage[writeImage < 0] = 0
writeImage[writeImage > 255] = 255
writer.write(writefile, writeImage)
writefile.close()
def SaveSpectrumAsCSV(self, filename):
filename = file_namer.name_file(filename)
ExportSpectrumRange = np.copy(self.SpectrumRange)
ExportIntensity = np.copy(self.intensity)
ExportSpectrumRange.resize(len(ExportSpectrumRange), 1)
ExportIntensity.resize(len(ExportIntensity), 1)
ExportData = np.append(ExportSpectrumRange, ExportIntensity, axis=1)
ExportHeaders = [(self.unit_label + ' (' + self.units + ')'),
'Intensity']
with open_csv(filename, 'w') as csvfile:
writer = csv.writer(csvfile, delimiter='\t')
writer.writerow(ExportHeaders)
writer.writerows(ExportData)
print('Saved file...', filename)
def save_img(self, filename, clim=[None, None], cmap=None, **kwargs):
'''
Save image
Filename: string to name the file, include directory path if the
current folder is not desired, filetype is given by the ending
clim: colour limits, if the image should be thresholded to a minimum
and maximum value. Should be of the form [minimum, maximum]
cmap: colourmap to apply to the saved image (eg, for grayscale images)
'''
if not isstring(filename):
raise ValueError('Your filename is not a string!')
if clim[0] is not None:
r_min = clim[0]
# r_min = np.maximum(clim[0], np.min(self.data.flatten()))
else:
r_min = np.min(self.data.flatten())
if clim[1] is not None:
r_max = clim[1]
# r_max = np.minimum(clim[1], np.max(self.data.flatten()))
else:
r_max = np.max(self.data.flatten())
filename = file_namer.name_file(filename)
save_im = imfun.contrast_stretch(self.data,
r=[r_min, r_max],
s=[0, 255],
bits=8).astype('uint8')
if cmap is not None:
save_im = cmap(save_im)
# if np.ma.is_masked(self.data) and np.shape(save_im)[-1] == 4:
# print('mask')
# save_im[:, :, -1] = save_im[:, :, -1] * self.data.mask.astype(int)
imfun.write_image(save_im, filename, **kwargs)
else:
imfun.write_image(save_im, filename, **kwargs)
