def test_line_raw(self):
filename = "test-spec-line.csv"
self.spec_stream.selectionWidth.value = 1
proj = LineSpectrumProjection(self.spec_stream)
exported_data = img.line_to_export_data(proj, True)
self.assertEqual(exported_data.shape[1], self.spec_data.shape[0])
self.assertGreater(exported_data.shape[0], 64) # at least 65-1 px
self.assertEqual(exported_data.metadata[model.MD_DIMS], "XC")
# Save into a CSV file
exporter = dataio.get_converter("CSV")
exporter.export(filename, exported_data)
st = os.stat(filename) # this test also that the file is created
self.assertGreater(st.st_size, 100)
self.spec_stream.selectionWidth.value = 4
exported_data = img.line_to_export_data(proj, True)
self.assertEqual(exported_data.shape[1], self.spec_data.shape[0])
self.assertGreater(exported_data.shape[0], 64) # at least 65-1 px
self.assertEqual(exported_data.metadata[model.MD_DIMS], "XC")
# Save into a CSV file
exporter = dataio.get_converter("CSV")
exporter.export(filename, exported_data)
st = os.stat(filename) # this test also that the file is created
self.assertGreater(st.st_size, 100)
# clean up
try:
os.remove(filename)
except Exception:
pass
def test_line_raw(self):
filename = "test-spec-line.csv"
self.spec_stream.selectionWidth.value = 1
proj = LineSpectrumProjection(self.spec_stream)
exported_data = img.line_to_export_data(proj, True)
self.assertEqual(exported_data.shape[1], self.spec_data.shape[0])
self.assertGreater(exported_data.shape[0], 64) # at least 65-1 px
self.assertEqual(exported_data.metadata[model.MD_DIMS],"XC")
# Save into a CSV file
exporter = dataio.get_converter("CSV")
exporter.export(filename, exported_data)
st = os.stat(filename) # this test also that the file is created
self.assertGreater(st.st_size, 100)
self.spec_stream.selectionWidth.value = 4
exported_data = img.line_to_export_data(proj, True)
self.assertEqual(exported_data.shape[1], self.spec_data.shape[0])
self.assertGreater(exported_data.shape[0], 64) # at least 65-1 px
self.assertEqual(exported_data.metadata[model.MD_DIMS],"XC")
# Save into a CSV file
exporter = dataio.get_converter("CSV")
exporter.export(filename, exported_data)
st = os.stat(filename) # this test also that the file is created
self.assertGreater(st.st_size, 100)
# clean up
try:
os.remove(filename)
except Exception:
pass
def test_line_ready(self):
self.spec_stream.selectionWidth.value = 1
exported_data = img.line_to_export_data(self.spec_stream, False)
self.assertEqual(exported_data.metadata[model.MD_DIMS], 'YXC') # ready for RGB export
self.assertEqual(exported_data.shape[:2],
(img.SPEC_PLOT_SIZE + img.SPEC_SCALE_HEIGHT + img.SMALL_SCALE_WIDTH,
img.SPEC_PLOT_SIZE + img.SPEC_SCALE_WIDTH + img.SMALL_SCALE_WIDTH)) # exported image includes scale bars
self.spec_stream.selectionWidth.value = 3
exported_data = img.line_to_export_data(self.spec_stream, False)
self.assertEqual(exported_data.metadata[model.MD_DIMS], 'YXC') # ready for RGB export
self.assertEqual(exported_data.shape[:2],
(img.SPEC_PLOT_SIZE + img.SPEC_SCALE_HEIGHT + img.SMALL_SCALE_WIDTH,
img.SPEC_PLOT_SIZE + img.SPEC_SCALE_WIDTH + img.SMALL_SCALE_WIDTH)) # exported image includes scale bars
def test_line_ready(self):
self.spec_stream.selectionWidth.value = 1
exported_data = img.line_to_export_data(self.spec_stream, False)
self.assertEqual(exported_data.metadata[model.MD_DIMS], 'YXC') # ready for RGB export
self.assertEqual(exported_data.shape[:2],
(img.SPEC_PLOT_SIZE + img.SPEC_SCALE_HEIGHT + img.SMALL_SCALE_WIDTH,
img.SPEC_PLOT_SIZE + img.SPEC_SCALE_WIDTH + img.SMALL_SCALE_WIDTH)) # exported image includes scale bars
self.spec_stream.selectionWidth.value = 3
exported_data = img.line_to_export_data(self.spec_stream, False)
self.assertEqual(exported_data.metadata[model.MD_DIMS], 'YXC') # ready for RGB export
self.assertEqual(exported_data.shape[:2],
(img.SPEC_PLOT_SIZE + img.SPEC_SCALE_HEIGHT + img.SMALL_SCALE_WIDTH,
img.SPEC_PLOT_SIZE + img.SPEC_SCALE_WIDTH + img.SMALL_SCALE_WIDTH)) # exported image includes scale bars
def export(self, export_type, raw=False):
"""
Returns the data to be exported with respect to the settings and options.
:param export_type (string): spatial, AR, spectrum or spectrum-line
:param raw (boolean): raw data format if True
:param interpolate_data (boolean): apply interpolation on data if True
returns DataArray or list of DataArray: the data to be exported, either
an RGB image or raw data.
raises:
LookupError: if no data found to export
"""
fview = self._data_model.focussedView.value
vp = self.get_viewport_by_view(fview)
streams = fview.getStreams()
if export_type == 'AR':
# TODO: set MD_ACQ_TYPE in stream code
for i, _ in enumerate(streams):
for r in streams[i].raw:
r.metadata[model.MD_ACQ_TYPE] = model.MD_AT_AR
exported_data = ar_to_export_data(streams, raw)
elif export_type == 'spectrum':
spectrum = vp.stream.get_pixel_spectrum()
spectrum_range, unit = vp.stream.get_spectrum_range()
spectrum.metadata[model.MD_ACQ_TYPE] = model.MD_AT_SPECTRUM
exported_data = spectrum_to_export_data(spectrum, raw, unit, spectrum_range)
elif export_type == 'spectrum-line':
spectrum_md = vp.stream.get_pixel_spectrum().metadata
spectrum = vp.stream.get_line_spectrum()
# copy only non existed values (we mainly care about MD_WL_*)
spectrum.metadata.update({k: v for k, v in spectrum_md.iteritems() if k not in spectrum.metadata})
spectrum_range, unit = vp.stream.get_spectrum_range()
spectrum.metadata[model.MD_ACQ_TYPE] = model.MD_AT_SPECTRUM
exported_data = line_to_export_data(spectrum, raw, unit, spectrum_range)
else:
export_type = 'spatial'
view_px = tuple(vp.canvas.ClientSize)
view_mpp = fview.mpp.value
view_hfw = (view_mpp * view_px[0], view_mpp * view_px[1])
view_pos = fview.view_pos.value
draw_merge_ratio = fview.stream_tree.kwargs.get("merge", 0.5)
interpolate_data = fview.interpolate_content.value
exported_data = images_to_export_data(streams,
view_hfw, view_pos,
draw_merge_ratio, raw,
interpolate_data=interpolate_data,
logo=self._main_frame.legend_logo)
return exported_data
def export(self, export_type, raw=False):
"""
Returns the data to be exported with respect to the settings and options.
:param export_type (string): spatial, AR, spectrum, spectrum-temporal,
spectrum-time, or spectrum-line
:param raw (boolean): raw data format if True
:param interpolate_data (boolean): apply interpolation on data if True
returns DataArray or list of DataArray: the data to be exported, either
an RGB image or raw data.
raises:
LookupError: if no data found to export
"""
fview = self._data_model.focussedView.value
vp = self.get_viewport_by_view(fview)
streams = fview.stream_tree.getProjections(
) # Stream tree to get the DataProjection
if export_type == 'AR':
exported_data = ar_to_export_data(streams, raw)
elif export_type == 'spectrum':
exported_data = spectrum_to_export_data(streams[0], raw, vp)
elif export_type == 'spectrum-line':
exported_data = line_to_export_data(streams[0], raw)
elif export_type == 'spectrum-temporal':
exported_data = temporal_spectrum_to_export_data(streams[0], raw)
elif export_type == 'spectrum-time':
exported_data = chronogram_to_export_data(streams[0], raw, vp)
else:
view_px = tuple(vp.canvas.ClientSize)
view_mpp = fview.mpp.value
view_hfw = (view_mpp * view_px[0], view_mpp * view_px[1])
view_pos = fview.view_pos.value
draw_merge_ratio = fview.stream_tree.kwargs.get("merge", 0.5)
interpolate_data = fview.interpolate_content.value
exported_data = images_to_export_data(
streams,
view_hfw,
view_pos,
draw_merge_ratio,
raw,
vp.canvas,
interpolate_data=interpolate_data,
logo=self._main_frame.legend_logo)
return exported_data
def test_line_raw(self):
filename = "test-spec-line.csv"
exported_data = img.line_to_export_data(self.spectrum, True, self.unit, self.spectrum_range)
self.assertEqual(exported_data.shape[0], self.spectrum.shape[1])
self.assertEqual(exported_data.shape[1], self.spectrum.shape[0])
# Save into a CSV file
exporter = dataio.get_converter("CSV")
exporter.export(filename, exported_data)
st = os.stat(filename) # this test also that the file is created
self.assertGreater(st.st_size, 100)
# clean up
try:
os.remove(filename)
except Exception:
pass
def export(self, export_type, raw=False):
"""
Returns the data to be exported with respect to the settings and options.
:param export_type (string): spatial, AR, spectrum, spectrum-temporal,
spectrum-time, or spectrum-line
:param raw (boolean): raw data format if True
:param interpolate_data (boolean): apply interpolation on data if True
returns DataArray or list of DataArray: the data to be exported, either
an RGB image or raw data.
raises:
LookupError: if no data found to export
"""
fview = self._data_model.focussedView.value
vp = self.get_viewport_by_view(fview)
streams = fview.stream_tree.getProjections() # Stream tree to get the DataProjection
if export_type == 'AR':
exported_data = ar_to_export_data(streams, raw)
elif export_type == 'spectrum':
exported_data = spectrum_to_export_data(streams[0], raw, vp)
elif export_type == 'spectrum-line':
exported_data = line_to_export_data(streams[0], raw)
elif export_type == 'spectrum-temporal':
exported_data = temporal_spectrum_to_export_data(streams[0], raw)
elif export_type == 'spectrum-time':
exported_data = chronogram_to_export_data(streams[0], raw, vp)
else:
view_px = tuple(vp.canvas.ClientSize)
view_mpp = fview.mpp.value
view_hfw = (view_mpp * view_px[0], view_mpp * view_px[1])
view_pos = fview.view_pos.value
draw_merge_ratio = fview.stream_tree.kwargs.get("merge", 0.5)
interpolate_data = fview.interpolate_content.value
exported_data = images_to_export_data(streams,
view_hfw, view_pos,
draw_merge_ratio, raw,
interpolate_data=interpolate_data,
logo=self._main_frame.legend_logo)
return exported_data
def test_line_ready(self):
exported_data = img.line_to_export_data(self.spectrum, False, self.unit, self.spectrum_range)
self.assertEqual(exported_data.metadata[model.MD_DIMS], 'YXC') # ready for RGB export
self.assertEqual(exported_data.shape[:2],
(img.SPEC_PLOT_SIZE + img.SPEC_SCALE_HEIGHT + img.SMALL_SCALE_WIDTH,
img.SPEC_PLOT_SIZE + img.SPEC_SCALE_WIDTH + img.SMALL_SCALE_WIDTH)) # exported image includes scale bars