''' Code to compute radial-max profiles of the FFT of live-view image in GMS, producing a 2D display of these profiles over time. WARNING: Due to a bug in GMS 3.5.0 and 3.5.1, this script will not run in those versions Run the code with the live-view image, containing a rectangular ROI, front-most in GMS The code also works with an IS video played back with the IS player To stop calculation, delete the ROI. Profiles are computed as often as possible. Lines of code between #XXXXXXXX... lines are specific to computing a radial-max profile All other lines of code are general, and can be re-used to produce other kinds of profiles from a live-view image Code written by Ben Miller. Last Updated Apr 2022 ''' import time import numpy as np import traceback if not DM.IsScriptOnMainThread(): print('Scipy scripts cannot be run on Background Thread.'); exit() import scipy from scipy import ndimage from scipy import signal from scipy import fftpack from scipy.ndimage.interpolation import geometric_transform #User editable variables are set here #XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX median = 0 #set to 1 to apply median filter to the FFT prior to profile creation (slows calculation, especially for large input images) initial_result_image_width = 200 #how many profiles can be displayed in the intial result window (window is automatically expanded as needed) profile_result_length_ratio = 4 #Set to some integer 2^N, N=>0. Smaller N will make calculation slower. Default: 4 profile_angular_sampling_resolution = 256 #set how many samples are taken around the circumference of the radial profile print_timing = True # (Default True) Select whether to output the time it takes to compute each frame #XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX class CListen(DM.Py_ScriptObject): #Function to find an ROI placed on an image by the user, returning the ROI ID. #If no ROI found, create a new one covering the entire image. def find_ROI(self,image): imageDisplay = image.GetImageDisplay(0) numROIs = imageDisplay.CountROIs() id = None for n in range(numROIs): roi = imageDisplay.GetROI(n) if roi.IsRectangle(): roi.SetVolatile(False) roi.SetResizable(False) id = roi.GetID() break if id is None: #If No ROI is found, create one that covers the whole image. print("\nRectangular ROI not found... using whole image") data_shape = image.GetNumArray().shape roi=DM.NewROI() roi.SetRectangle(0, 0, data_shape[0], data_shape[1]) imageDisplay.AddROI(roi) roi.SetVolatile(False) roi.SetResizable(False) id = roi.GetID() return id #XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX #Function to Determine Result Profile Length def profile_length(self,sx,sf): return int(sx/sf) #Function to Set Result Image Calibration def calibrate_result(self,scale,sx,sf,ustr): diff_scale = sf/scale/2/sx unit_str = ustr+"-1" return(diff_scale,unit_str) #Funtion to convert cartesian-coordinate image to polar-coordinate image def topolar(self, img, r_size, theta_size, order=1): sx, sy = img.shape max_radius = int(sx/2) #define transform def transform(coords): theta = 2.0*np.pi*coords[1] / (theta_size - 1.) radius = max_radius * coords[0] / r_size i = int(sx/2) - radius*np.sin(theta) j = radius*np.cos(theta) + int(sx/2) return i,j #perform transform polar = geometric_transform(img, transform, output_shape=(r_size,theta_size), order=order,mode='constant',cval=1.0,prefilter=False) return polar #Function to calculate radial profile of FFT from image def FFT_radial_profile(self, image_o, profile_ang_res,length_ratio,do_median): #compute FFT fft_im = np.absolute(scipy.fftpack.fftshift(np.fft.fft2(image_o))) #Median-Filter FFT to remove single-pixel outliers if do_median: fft_im_median = scipy.ndimage.median_filter(fft_im, size=3) else: fft_im_median = fft_im #determine profile size sx, sy = fft_im.shape profile_size = int(sx/length_ratio) #convert FFT image to polar coordinates polar_im = self.topolar(fft_im_median, profile_size, profile_ang_res, order=1) #compute radial mean and maximum profiles radial_max=np.amax(polar_im,1) radial_mean=np.mean(polar_im,1) #median-filter the radial mean profile to smooth this further radial_mean_median = scipy.signal.medfilt(radial_mean) #radial profile is radial-max minus radial-mean radial_profile = np.atleast_2d(radial_max-radial_mean_median) return radial_profile #XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX #Initialization Function def __init__(self, img): try: #Create an index that is incremented each time data is processed. (This index is not utilized in this script.) self.i = 0 self.name = "ImageO" self.j = True #this is only for IS player testing #get the original image and assign it to self.imgref self.imgref = img #Get the data from the region within an ROI self.roi = DM.GetROIFromID(self.find_ROI(self.imgref)) val, val2, val3, val4 = self.roi.GetRectangle() self.data = self.imgref.GetNumArray()[int(val):int(val3),int(val2):int(val4)] #get the shape and calibration of the original image (input_sizex, input_sizey) = self.data.shape x_origin = self.imgref.GetDimensionOrigin(0); y_origin = self.imgref.GetDimensionOrigin(1) x_scale = self.imgref.GetDimensionScale(0); y_scale = self.imgref.GetDimensionScale(1) #scale unit of microns causes problems for python in DM try: x_unit = self.imgref.GetDimensionUnitString(0) ; y_unit = self.imgref.GetDimensionUnitString(1) except: x_unit = self.imgref.GetDimensionUnitInfo(0)[0]; y_unit = self.imgref.GetDimensionUnitInfo(1)[0] if x_unit == 'micrometer': x_unit = 'um' if y_unit == 'micrometer': y_unit = 'um' #XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX #Set the size and calibration of the result image (self.scale,self.unit_string) = self.calibrate_result(x_scale,input_sizex,profile_result_length_ratio,x_unit) r_img_size=self.profile_length(input_sizex,profile_result_length_ratio) #XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX #create empty set for result images self.result_images = {} #create 1st result image and set calibration self.result_images[self.name] = DM.CreateImage(np.zeros((r_img_size,initial_result_image_width))) self.result_images[self.name].SetDimensionCalibration(1,0,self.scale,self.unit_string,0) #Copy tags from original to processed image Tag_Copy(self.imgref, self.result_images[self.name],subPath='OriginalImageTags') self.result_images[self.name].ShowImage() #get numpy array from result image self.result_array = self.result_images[self.name].GetNumArray() #Set the image name which will be displayed in the image window's title bar self.result_images[self.name].SetName("Radial Max Profiles of "+img.GetName()) DM.Py_ScriptObject.__init__(self) self.stop = 0 except: print(traceback.format_exc()) #This function is run each time the image changes def HandleDataChangedEvent(self, flags, image): try: if not self.stop: #start timing start=time.perf_counter() (result_sizey, result_sizex) = self.result_array.shape #if the result image is nearly full, make it 2x larger if self.i > result_sizex-2: #create a new numpy array 2x larger self.result_array_temp = np.append(self.result_array, np.zeros_like(self.result_array), axis=1) #close the old results image in DM DM.DeleteImage(self.result_images[self.name]) #create a new results image and calibrate it self.name="Image{0}".format(self.i) self.result_images[self.name] = DM.CreateImage(np.copy((self.result_array_temp))) self.result_images[self.name].SetDimensionCalibration(1,0,self.scale,self.unit_string,0) #Copy tags from original to processed image Tag_Copy(self.imgref, self.result_images[self.name],subPath='OriginalImageTags') #Set the image name which will be displayed in the image window's title bar self.result_images[self.name].SetName("Radial Max Profiles of "+self.imgref.GetName()) #display new result image in DM self.result_images[self.name].ShowImage() #get numpy array from new result image self.result_array = (self.result_images[self.name].GetNumArray()) #XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX #Get an (updated) ROI position val, val2, val3, val4 = self.roi.GetRectangle() #Get the data from the ROI area as a numpy array self.data = self.imgref.GetNumArray()[int(val):int(val3),int(val2):int(val4)] #compute radial FFT profile from the image, and place this profile into results image self.result_array[:,self.i] = self.FFT_radial_profile(self.data,profile_angular_sampling_resolution,profile_result_length_ratio, median) #XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX #Update the result image display self.result_images[self.name].UpdateImage() #end timing and output time to process this frame end=time.perf_counter() if print_timing: print("Processed Image "+str(self.i)+" Processing Time= "+str(end-start)) #Increment an index each time data is processed. self.i = self.i+1 except: print(traceback.format_exc()) #Function to Delete Image Listener def __del__(self): print("Listener Deleted") DM.Py_ScriptObject.__del__(self) #Function to end processing by deleting or unregistering listener def RemoveListeners(self): try: if not self.stop: self.stop = 1 DM.DoEvents() global listener #DM 3.5.2 and higher have new function for unregistering listeners. #DM 3.4.3 and lower should delete the listener instead #DM 3.5.0 and 3.5.1 have a fatal flaw regarding listeners, so this script is not compatible with those versions if (get_DM_version()[1][0] == "4" and get_DM_version()[0] == "3"): del listener else: listener.UnregisterAllListeners() print("Live Processing Script Ended") except: print(traceback.format_exc()) #Remove listeners if source image window is closed def HandleWindowClosedEvent(self, event_flags, window): print("Window Closed") self.RemoveListeners() #Remove listeners if the ROI is deleted def HandleROIRemovedEvent(self, img_disp_event_flags, img_disp, roi_change_flag, roi_disp_change_flags, roi): print("ROI Removed") self.RemoveListeners() #Function to get the currently used version of DigitalMicrograph def get_DM_version(): #No Python script command exists to get the DM version, #so we first run a DM script to put the values in the global tags dm_script = ('number minor, major, bugVersion\n' 'GetApplicationVersion(major, minor, bugVersion)\n' 'GetPersistentTagGroup().TagGroupSetTagAsLong("Python_Temp:DM_Version_Major",major)\n' 'GetPersistentTagGroup().TagGroupSetTagAsLong("Python_Temp:DM_Version_Minor",minor)\n' 'GetPersistentTagGroup().TagGroupSetTagAsLong("Python_Temp:DM_Version_bugVersion",bugVersion)') DM.ExecuteScriptString(dm_script) #Now get the information stored in the global tags by the DM script version = [0,0,0] _,version[0] = DM.GetPersistentTagGroup().GetTagAsString("Python_Temp:DM_Version_Major") _,version[1] = DM.GetPersistentTagGroup().GetTagAsString("Python_Temp:DM_Version_Minor") _,version[2] = DM.GetPersistentTagGroup().GetTagAsString("Python_Temp:DM_Version_bugVersion") return version def Tag_Copy(image_source, image_dest, subPath = None ): ''' Copy all tags between source and destination. If no destination subPath is provided, the destination tags will be replaced. ''' #Copy Tags tg_source = image_source.GetTagGroup() tg_dest = image_dest.GetTagGroup() if ( subPath != None ): tg_dest.SetTagAsTagGroup(subPath,tg_source.Clone()) else: tg_dest.DeleteAllTags() tg_dest.CopyTagsFrom(tg_source.Clone()) #Main Code Starts Here #Check that we are not running 3.5.0 or 3.5.1 which have a known bug affecting this script. if (((get_DM_version()[1] == '51') or (get_DM_version()[1] == '50')) and get_DM_version()[0] == "3"): DM.OkDialog("Due to a bug in DigitalMicrograph 3.5.0 and 3.5.1, this script would cause DM to crash in those versions. \n\nScript Aborted.") exit() #Get front image in GMS img1 = DM.GetFrontImage() #Get the image window, so we can check if it gets closed imageDoc = DM.GetFrontImageDocument() imDocWin = imageDoc.GetWindow() #Get the image display, for the ROI-removed listener imageDisplay = img1.GetImageDisplay(0) #Listeners are started here #initiate the image listener listener = CListen(img1) #check if the source window closes WindowClosedListenerID = listener.WindowHandleWindowClosedEvent(imDocWin, 'pythonplugin') #check if the ROI has been deleted ROIRemovedListenerID = listener.ImageDisplayHandleROIRemovedEvent(imageDisplay,'pythonplugin') #check if the source image changes DataChangedListenerID = listener.ImageHandleDataChangedEvent(img1, 'pythonplugin') #IDs are not used in this script, but could be used to unregister individual listeners in DM 3.5.2 and higher.