def construct_bvdata(bpm):
# just read the last image
image = _control_ref().ReadImage()
last_acq_time, last_x, last_y, last_intensity,\
last_fwhm_x, last_fwhm_y, last_max_intensity,\
last_proj_x, last_proj_y = bpm.get_bpm_result(image.frameNumber, image.timestamp)
lima_roi = _control_ref().image().getRoi()
roi_top_left = lima_roi.getTopLeft()
roi_size = lima_roi.getSize()
jpegFile = StringIO()
image_type = _control_ref().image().getImageType()
bpp = bpm.ImageType2Bpp[image_type]
# manual scaling: use the user image min/max intensity to filter
if not bpm.autoscale:
min_val = bpm.min_max[0]
max_val = bpm.min_max[1]
scale_image = image.buffer.clip(min_val, max_val)
# auto scaling: use natural image intensity
else:
min_val = image.buffer.min()
max_val = image.buffer.max()
if max_val == 0: max_val = 1
scale_image = image.buffer
# logarithmic scaling
if bpm.lut_method == "LOG":
if min_val > 0:
scale_image = numpy.log10(scale_image)
else:
scale_image = numpy.log10(scale_image.clip(1, None))
min_val += 1
min_val = numpy.log10(min_val)
max_val = numpy.log10(max_val)
# scale the image to the whole range 16bit before palette transformation for 0 to 65535
if max_val == min_val: max_val += 1
scaling = (2**16 - 1.) / (max_val - min_val)
scale_image = ((scale_image - min_val) * scaling).astype(numpy.uint16)
# last transformation ot color or greys palette
if bpm.color_map:
img_buffer = bpm.palette["color"].take(scale_image, axis=0)
else:
img_buffer = bpm.palette["grey"].take(scale_image, axis=0)
I = Image.fromarray(img_buffer, "RGB")
if turbo_jpeg:
jpegFile.write(
turbo_jpeg.encode(numpy.asarray(I),
pixel_format=TJPF_RGB,
quality=bpm.jpeg_quality))
else:
I.save(jpegFile, "jpeg", quality=bpm.jpeg_quality)
raw_jpeg_data = jpegFile.getvalue()
image_jpeg = base64.b64encode(raw_jpeg_data)
if bpm.return_bpm_profiles:
profile_x = last_proj_x.tobytes()
profile_y = last_proj_y.tobytes()
else:
profile_y = image.buffer[:, bpm.beammark[0]].astype(numpy.uint64)
profile_y = profile_y.tobytes()
profile_x = image.buffer[bpm.beammark[1], :].astype(numpy.uint64)
profile_x = profile_x.tobytes()
bvdata_format = 'dldddliiiidd%ds%ds%ds' % (len(profile_x), len(profile_y),
len(image_jpeg))
bvdata = struct.pack(bvdata_format, last_acq_time, image.frameNumber,
last_x, last_y, last_intensity, last_max_intensity,
roi_top_left.x, roi_top_left.y, roi_size.getWidth(),
roi_size.getHeight(), last_fwhm_x, last_fwhm_y,
profile_x, profile_y, image_jpeg)
return bvdata, bvdata_format
