numpy version issue?

[GuptonLab]

Hi! I am trying to make my way through the tutorial and hit a command that has been depreciated in numpy 2.3.3 which is the version installed currently with pip install numpy. The numpy.product function has been replaced with numpy.prod. I made this pretty simple change but that caused further problems that I will definitely not be able to solve. What versions of numpy and the other dependencies do I need to run ExTrack? Or, am I doing something wrong that is causing this issue?

Thanks for any help you can offer!

[FrancoisSimon]

Hi,
Thank you for noticing and reporting this issue. I tried to reproduce this bug by creating a new python 3.11 environement (with anaconda and the IDE spyder) with the latest version of numpy but extrack was working just fine with the numpy.product. Checking the script tracking more carefully, I noticed that numpy.product is only used in the function fuse_tracks_th which is actually never called in the current version of extrack. Sorry if the code is a bit messy and possesses legacy functions. Could you try to replace the script 'tracking.py' with the 'tracking.py' in the attached zip file?

tracking.zip

Here is some informations that could help me better understand/reproduce the problem:
What OS are you using?
environment manager
version of python
Did you install extrack via 'pip install extrack' or are you downloading the github repository.
Which function didn't work ? I imagine it should come from param_fitting
Could you also provide the error log

Thank you!

[GuptonLab]

Hi Francois, Thanks so much for getting back to me. I apologize in advance for anything silly that I am doing – I am new at this and just muddling my way through…I first tried using the pip install option and was working my way through the tutorial script. I ran into the issue in the block commented “show the longest tracks in more details” which calls extrack.visualization. Line 116 in the visualization code has numpy.product in it. With the help of a colleague who reproduced my problem, I removed everything from my computer, created a new conda environment just for this and downloaded the code from github. I changed the sys path to my local folder so I could change the code in line 116 of the visualization script and then got this error instead: ***@***.*** I can try to go back to my original problem if that is helpful but basically it said product was not recognized. I am working on a mac running OS 14.7.2 I created an environment with conda which includes python 3.13.7 – full list below: # packages in environment at /opt/anaconda3/envs/forExT: # # Name Version Build Channel _python_abi3_support 1.0 hd8ed1ab_2 conda-forge appnope 0.1.4 pyhd8ed1ab_1 conda-forge asteval 1.0.6 pypi_0 pypi asttokens 3.0.0 pyhd8ed1ab_1 conda-forge bzip2 1.0.8 h80987f9_6 ca-certificates 2025.9.9 hca03da5_0 comm 0.2.3 pyhe01879c_0 conda-forge contourpy 1.3.3 pypi_0 pypi cpython 3.13.7 py313hd8ed1ab_100 conda-forge cycler 0.12.1 pypi_0 pypi debugpy 1.8.16 py313hab38a8b_1 conda-forge decorator 5.2.1 pyhd8ed1ab_0 conda-forge dill 0.4.0 pypi_0 pypi exceptiongroup 1.3.0 pyhd8ed1ab_0 conda-forge executing 2.2.1 pyhd8ed1ab_0 conda-forge expat 2.7.1 h313beb8_0 fonttools 4.59.2 pypi_0 pypi importlib-metadata 8.7.0 pyhe01879c_1 conda-forge ipykernel 6.30.1 pyh92f572d_0 conda-forge ipython 9.5.0 pyhfa0c392_0 conda-forge ipython_pygments_lexers 1.1.1 pyhd8ed1ab_0 conda-forge jedi 0.19.2 pyhd8ed1ab_1 conda-forge jupyter_client 8.6.3 pyhd8ed1ab_1 conda-forge jupyter_core 5.8.1 pyh31011fe_0 conda-forge kiwisolver 1.4.9 pypi_0 pypi krb5 1.21.3 h237132a_0 conda-forge libcxx 20.1.8 h8869778_0 libedit 3.1.20250104 pl5321hafb1f1b_0 conda-forge libffi 3.4.4 hca03da5_1 libmpdec 4.0.0 h80987f9_0 libsodium 1.0.20 h99b78c6_0 conda-forge libzlib 1.3.1 h5f15de7_0 lmfit 1.3.4 pypi_0 pypi matplotlib 3.10.6 pypi_0 pypi matplotlib-inline 0.1.7 pyhd8ed1ab_1 conda-forge ncurses 6.5 hee39554_0 nest-asyncio 1.6.0 pyhd8ed1ab_1 conda-forge numpy 2.3.3 pypi_0 pypi openssl 3.5.2 he92f556_0 conda-forge packaging 25.0 pyh29332c3_1 conda-forge pandas 2.3.2 pypi_0 pypi parso 0.8.5 pyhcf101f3_0 conda-forge pexpect 4.9.0 pyhd8ed1ab_1 conda-forge pickleshare 0.7.5 pyhd8ed1ab_1004 conda-forge pillow 11.3.0 pypi_0 pypi pip 25.2 pyhc872135_0 platformdirs 4.4.0 pyhcf101f3_0 conda-forge prompt-toolkit 3.0.52 pyha770c72_0 conda-forge psutil 7.0.0 py313hcdf3177_1 conda-forge ptyprocess 0.7.0 pyhd8ed1ab_1 conda-forge pure_eval 0.2.3 pyhd8ed1ab_1 conda-forge pygments 2.19.2 pyhd8ed1ab_0 conda-forge pyparsing 3.2.3 pypi_0 pypi python 3.13.7 hc28b8d9_100_cp313 python-dateutil 2.9.0.post0 pyhe01879c_2 conda-forge python-gil 3.13.7 h4df99d1_100 conda-forge python_abi 3.13 1_cp313 pytz 2025.2 pypi_0 pypi pyzmq 27.1.0 py312hd65ceae_0 conda-forge readline 8.3 h0b18652_0 scipy 1.16.2 pypi_0 pypi setuptools 78.1.1 py313hca03da5_0 six 1.17.0 pyhe01879c_1 conda-forge sqlite 3.50.2 h79febb2_1 stack_data 0.6.3 pyhd8ed1ab_1 conda-forge tk 8.6.15 hcd8a7d5_0 tornado 6.5.2 py313hcdf3177_1 conda-forge traitlets 5.14.3 pyhd8ed1ab_1 conda-forge typing_extensions 4.15.0 pyhcf101f3_0 conda-forge tzdata 2025.2 pypi_0 pypi uncertainties 3.2.3 pypi_0 pypi wcwidth 0.2.13 pyhd8ed1ab_1 conda-forge wheel 0.45.1 py313hca03da5_0 xmltodict 0.15.1 pypi_0 pypi xz 5.6.4 h80987f9_1 zeromq 4.3.5 h888dc83_9 conda-forge zipp 3.23.0 pyhd8ed1ab_0 conda-forge zlib 1.3.1 h5f15de7_0 Ok – I hope that is all the information you asked for and thank you for the new script – I will try that as soon as I can. Thanks again for your help, it is much appreciated. Ellen From: François Simon ***@***.***> Date: Thursday, September 11, 2025 at 7:32 PM To: vanTeeffelenLab/ExTrack ***@***.***> Cc: O'Shaughnessy, Ellen C ***@***.***>, Author ***@***.***> Subject: Re: [vanTeeffelenLab/ExTrack] numpy version issue? (Issue #7) You don't often get email from ***@***.*** Learn why this is important<https://aka.ms/LearnAboutSenderIdentification> [Image removed by sender.]FrancoisSimon left a comment (vanTeeffelenLab/ExTrack#7)<#7 (comment)> Hi, Thank you for noticing and reporting this issue. I tried to reproduce this bug by creating a new python 3.11 environement (with anaconda and the IDE spyder) with the latest version of numpy but extrack was working just fine with the numpy.product. Checking the script tracking more carefully, I noticed that numpy.product is only used in the function fuse_tracks_th which is actually never called in the current version of extrack. Sorry if the code is a bit messy and possesses legacy functions. Could you try to replace the script 'tracking.py' with the 'tracking.py' in the attached zip file? tracking.zip<https://github.com/user-attachments/files/22286218/tracking.zip> Here is some informations that could help me better understand/reproduce the problem: What OS are you using? environment manager version of python Did you install extrack via 'pip install extrack' or are you downloading the github repository. Which function didn't work ? I imagine it should come from param_fitting Could you also provide the error log Thank you! — Reply to this email directly, view it on GitHub<#7 (comment)>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/AIJKBYM6XCRKESPJOUP22HL3SIBBNAVCNFSM6AAAAACGIZUOK2VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZTEOBSHE3DIMJQGM>. You are receiving this because you authored the thread.Message ID: ***@***.***>

[GuptonLab]

Hi again. Just for completeness I recreated using pip install. Before I run the block I see this: ***@***.*** And after I get this: ***@***.*** Best, Ellen From: François Simon ***@***.***> Date: Thursday, September 11, 2025 at 7:32 PM To: vanTeeffelenLab/ExTrack ***@***.***> Cc: O'Shaughnessy, Ellen C ***@***.***>, Author ***@***.***> Subject: Re: [vanTeeffelenLab/ExTrack] numpy version issue? (Issue #7) You don't often get email from ***@***.*** Learn why this is important<https://aka.ms/LearnAboutSenderIdentification> [Image removed by sender.]FrancoisSimon left a comment (vanTeeffelenLab/ExTrack#7)<#7 (comment)> Hi, Thank you for noticing and reporting this issue. I tried to reproduce this bug by creating a new python 3.11 environement (with anaconda and the IDE spyder) with the latest version of numpy but extrack was working just fine with the numpy.product. Checking the script tracking more carefully, I noticed that numpy.product is only used in the function fuse_tracks_th which is actually never called in the current version of extrack. Sorry if the code is a bit messy and possesses legacy functions. Could you try to replace the script 'tracking.py' with the 'tracking.py' in the attached zip file? tracking.zip<https://github.com/user-attachments/files/22286218/tracking.zip> Here is some informations that could help me better understand/reproduce the problem: What OS are you using? environment manager version of python Did you install extrack via 'pip install extrack' or are you downloading the github repository. Which function didn't work ? I imagine it should come from param_fitting Could you also provide the error log Thank you! — Reply to this email directly, view it on GitHub<#7 (comment)>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/AIJKBYM6XCRKESPJOUP22HL3SIBBNAVCNFSM6AAAAACGIZUOK2VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZTEOBSHE3DIMJQGM>. You are receiving this because you authored the thread.Message ID: ***@***.***>

[FrancoisSimon]

Hi,

I have no idea what the error message "@.***" means. Does it only appears when you try to run extrack.visualization.plot_tracks or earlier in the pipline? When I replace np.product with np.prod, it works just fine for me (both on python 3.11 and 3.13.7. I will update the extrack version with the pip install command soon to to replace the np.prod.
While I am doing that, check that your system pathes do not contain any specific python environment (as it could create conflicts). Then, here is a workaround that you can try to fix the situation:

First, on a clean environment, use pip install extrack, then open spyder and open the following script in spyder (just don't save this script in an extrack folder that contains the other extrack scripts as it could result with system path conflicts).

test_extrack.py

Then, put your mouse cursor on plot_tracks of extrack.visualization.plot_tracks(DATA, line 59 an click rigth.
A window like this should appear :

Then click on 'go to definition'. It should open the script visualization.py.
If visualization.py does not open, you can open it manually by locating it and opening the visualization.py script. The location should look like pathtoanaconda\anaconda3\envs\environment_name\Lib\site-packages\extrack\visualization.py

Then, replace the function plot_tracks with:

def plot_tracks(DATA,
                max_track_length = 50,
                nb_subplots = [5,5],
                figsize = (10,10),
                lim = 0.4 ):
    '''
    DATA: dataframe outputed by extrack.exporters.extrack_2_pandas.
    max_track_length: maximum track length to be outputed, it will plot the longest tracks respecting this criteria.
    nb_subplots: number of lines and columns of subplots.
    figsize: size of the figure plotted
    lim: limit for x and y axis around the track center
    '''
    
    # Count number of states
    nb_states = 0
    pred_columns = []
    for param in list(DATA.keys()):
        if param.find('pred')+1:
            nb_states += 1
            pred_columns.append(param)
    
    # Sort prediction columns to ensure consistent ordering
    pred_columns.sort()
    
    plt.figure(figsize=figsize)
    
    # Remove tracks longer than max_track_length
    for ID in np.unique(DATA['TRACK_ID'])[::-1]:
        track = DATA[DATA['TRACK_ID'] == ID]
        if len(track) > max_track_length:
            DATA.drop((DATA[DATA['TRACK_ID'] == ID]).index, inplace=True)
    
    # Generate distinct colors for each state
    if nb_states > 0:
        # Use a colormap that provides distinct colors
        if nb_states <= 10:
            colormap = cm.tab10
        elif nb_states <= 20:
            colormap = cm.tab20
        else:
            colormap = cm.hsv
        
        # Generate colors for each state
        state_colors = [colormap(i) for i in range(nb_states)]
    
    # Plot tracks
    for k, ID in enumerate(np.unique(DATA['TRACK_ID'])[::-1][:min(len(np.unique(DATA['TRACK_ID'])), np.prod(nb_subplots))]):
        
        plt.subplot(nb_subplots[0], nb_subplots[1], k+1)
        track = DATA[DATA['TRACK_ID'] == ID]

        if nb_states == 1:
            # Single state, use intensity based on prediction
            pred = track[pred_columns[0]].values
            pred = cm.viridis(pred)
        elif nb_states == 2:
            # Two states, interpolate between two colors
            pred = track[pred_columns[1]].values  # Usually pred_1 for binary classification
            pred = cm.brg(pred*0.5)
        elif nb_states == 3:
            pred = track[pred_columns].values  # Usually pred_1 for binary classification

        else:
            # Multiple states, use RGB mixing or dominant state coloring
            pred_values = track[pred_columns].values
            
            # Method 1: Color by dominant state
            dominant_states = np.argmax(pred_values, axis=1)
            pred = [state_colors[state] for state in dominant_states]
            
            # Alternative Method 2: RGB mixing (uncomment to use instead)
            # if nb_states == 3:
            #     pred = pred_values  # Direct RGB for 3 states
            # else:
            #     # For more than 3 states, use weighted average of first 3 colors
            #     weights = pred_values[:, :min(3, nb_states)]
            #     if nb_states > 3:
            #         weights = weights / np.sum(weights, axis=1, keepdims=True)
            #     pred = weights
        
        # Plot track
        plt.plot(track['POSITION_X'], track['POSITION_Y'], 'k:', alpha = 0.2)
        plt.scatter(track['POSITION_X'], track['POSITION_Y'], c = pred, s=3)
        plt.xlim([np.mean(track['POSITION_X']) - lim, np.mean(track['POSITION_X']) + lim])
        plt.ylim([np.mean(track['POSITION_Y']) - lim, np.mean(track['POSITION_Y']) + lim])
        plt.gca().set_aspect('equal', adjustable='box')
        plt.yticks(fontsize = 6)
        plt.xticks(fontsize = 6)
    
    # Add legend for states
    legend_elements = []
    for i in range(nb_states):
        label = f'State {i}'
        if nb_states == 1:
            color = cm.viridis(1)  # Middle color for representation
        elif nb_states == 2:
            if i == 0:
                color = cm.brg(0.0)
            else:
                color = cm.brg(0.5)
        elif nb_states == 3:
            color = [0,0,0]
            color[i] = 1
        else:
            label = f'State {i}'
            color = state_colors[i]
        
        legend_elements.append(plt.Line2D([0], [0], marker='o', color='w', 
                                            markerfacecolor=color, markersize=5, 
                                            label=label, linestyle='None'))
    
    # Place legend outside the plot area
    plt.figlegend(handles=legend_elements, 
                 loc='center right', 
                 bbox_to_anchor=(0.98, 0.5),
                 fontsize=8)
    
    print('')
    plt.tight_layout(h_pad = 1, w_pad = 1)
    # Adjust layout to make room for legend
    if nb_states > 0:
        plt.subplots_adjust(right=0.85)

and save visualization.py
Then you should be able to run the function via text_extrack.py or Tutorial_ExTrack.ipynb
Let me know if that fixes your problem. If not I can suggest another workaround

[GuptonLab]

Sorry! I responded in an email and included a screenshot which apparently doesn’t work in the github platform. Can you see this: --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) Cell In[14], line 3 1 # show the longest tracks in more details : ----> 3 extrack.visualization.plot_tracks(DATA, 4 max_track_length = 50, 5 nb_subplots = [5,5], 6 figsize = (10,10), 7 lim = 0.6) File /opt/anaconda3/envs/spt/lib/python3.13/site-packages/extrack/visualization.py:116<http://localhost:8888/opt/anaconda3/envs/spt/lib/python3.13/site-packages/extrack/visualization.py#line=115>, in plot_tracks(DATA, max_track_length, nb_subplots, figsize, lim) 113 if len(track) > max_track_length: 114 DATA.drop((DATA[DATA['TRACK_ID'] == ID]).index, inplace=True) --> 116 for k, ID in enumerate(np.unique(DATA['TRACK_ID'])[::-1][:np.product(nb_subplots)]): 117 plt.subplot(nb_subplots[0], nb_subplots[1], k+1) 119 track = DATA[DATA['TRACK_ID'] ==ID ] File /opt/anaconda3/envs/spt/lib/python3.13/site-packages/numpy/__init__.py:414<http://localhost:8888/opt/anaconda3/envs/spt/lib/python3.13/site-packages/numpy/__init__.py#line=413>, in __getattr__(attr) 411 import numpy.char as char 412 return char.chararray --> 414 raise AttributeError("module {!r} has no attribute " 415 "{!r}".format(__name__, attr)) AttributeError: module 'numpy' has no attribute 'product' This is the error that I get when installing with pip install. From: François Simon ***@***.***> Date: Saturday, September 13, 2025 at 12:07 PM To: vanTeeffelenLab/ExTrack ***@***.***> Cc: O'Shaughnessy, Ellen C ***@***.***>, Author ***@***.***> Subject: Re: [vanTeeffelenLab/ExTrack] numpy version issue? (Issue #7) You don't often get email from ***@***.*** Learn why this is important<https://aka.ms/LearnAboutSenderIdentification> [Image removed by sender.]FrancoisSimon left a comment (vanTeeffelenLab/ExTrack#7)<#7 (comment)> Hi, I have no idea what the error message ***@***.******" means. Does it only appears when you try to run extrack.visualization.plot_tracks or earlier in the pipline? When I replace np.product with np.prod, it works just fine for me (both on python 3.11 and 3.13.7. I will update the extrack version with the pip install command soon to to replace the np.prod. While I am doing that, check that your system pathes do not contain any specific python environment (as it could create conflicts). Then, here is a workaround that you can try to fix the situation: First, on a clean environment, use pip install extrack, then open spyder and open the following script in spyder (just don't save this script in an extrack folder that contains the other extrack scripts as it could result with system path conflicts). test_extrack.py<https://github.com/user-attachments/files/22311623/test_extrack.py> Then, put your mouse cursor on plot_tracks of extrack.visualization.plot_tracks(DATA, line 59 an click rigth. A window like this should appear : image.png (view on web)<https://github.com/user-attachments/assets/cff7f6f4-ac3e-49d9-bd26-467d05bf0b29> Then click on 'go to definition'. It should open the script visualization.py. If visualization.py does not open, you can open it manually by locating it and opening the visualization.py script. The location should look like pathtoanaconda\anaconda3\envs\environment_name\Lib\site-packages\extrack\visualization.py Then, replace the function plot_tracks with: def plot_tracks(DATA, max_track_length = 50, nb_subplots = [5,5], figsize = (10,10), lim = 0.4 ): ''' DATA: dataframe outputed by extrack.exporters.extrack_2_pandas. max_track_length: maximum track length to be outputed, it will plot the longest tracks respecting this criteria. nb_subplots: number of lines and columns of subplots. figsize: size of the figure plotted lim: limit for x and y axis around the track center ''' # Count number of states nb_states = 0 pred_columns = [] for param in list(DATA.keys()): if param.find('pred')+1: nb_states += 1 pred_columns.append(param) # Sort prediction columns to ensure consistent ordering pred_columns.sort() plt.figure(figsize=figsize) # Remove tracks longer than max_track_length for ID in np.unique(DATA['TRACK_ID'])[::-1]: track = DATA[DATA['TRACK_ID'] == ID] if len(track) > max_track_length: DATA.drop((DATA[DATA['TRACK_ID'] == ID]).index, inplace=True) # Generate distinct colors for each state if nb_states > 0: # Use a colormap that provides distinct colors if nb_states <= 10: colormap = cm.tab10 elif nb_states <= 20: colormap = cm.tab20 else: colormap = cm.hsv # Generate colors for each state state_colors = [colormap(i) for i in range(nb_states)] # Plot tracks for k, ID in enumerate(np.unique(DATA['TRACK_ID'])[::-1][:min(len(np.unique(DATA['TRACK_ID'])), np.prod(nb_subplots))]): plt.subplot(nb_subplots[0], nb_subplots[1], k+1) track = DATA[DATA['TRACK_ID'] == ID] if nb_states == 1: # Single state, use intensity based on prediction pred = track[pred_columns[0]].values pred = cm.viridis(pred) elif nb_states == 2: # Two states, interpolate between two colors pred = track[pred_columns[1]].values # Usually pred_1 for binary classification pred = cm.brg(pred*0.5) elif nb_states == 3: pred = track[pred_columns].values # Usually pred_1 for binary classification else: # Multiple states, use RGB mixing or dominant state coloring pred_values = track[pred_columns].values # Method 1: Color by dominant state dominant_states = np.argmax(pred_values, axis=1) pred = [state_colors[state] for state in dominant_states] # Alternative Method 2: RGB mixing (uncomment to use instead) # if nb_states == 3: # pred = pred_values # Direct RGB for 3 states # else: # # For more than 3 states, use weighted average of first 3 colors # weights = pred_values[:, :min(3, nb_states)] # if nb_states > 3: # weights = weights / np.sum(weights, axis=1, keepdims=True) # pred = weights # Plot track plt.plot(track['POSITION_X'], track['POSITION_Y'], 'k:', alpha = 0.2) plt.scatter(track['POSITION_X'], track['POSITION_Y'], c = pred, s=3) plt.xlim([np.mean(track['POSITION_X']) - lim, np.mean(track['POSITION_X']) + lim]) plt.ylim([np.mean(track['POSITION_Y']) - lim, np.mean(track['POSITION_Y']) + lim]) plt.gca().set_aspect('equal', adjustable='box') plt.yticks(fontsize = 6) plt.xticks(fontsize = 6) # Add legend for states legend_elements = [] for i in range(nb_states): label = f'State {i}' if nb_states == 1: color = cm.viridis(1) # Middle color for representation elif nb_states == 2: if i == 0: color = cm.brg(0.0) else: color = cm.brg(0.5) elif nb_states == 3: color = [0,0,0] color[i] = 1 else: label = f'State {i}' color = state_colors[i] legend_elements.append(plt.Line2D([0], [0], marker='o', color='w', markerfacecolor=color, markersize=5, label=label, linestyle='None')) # Place legend outside the plot area plt.figlegend(handles=legend_elements, loc='center right', bbox_to_anchor=(0.98, 0.5), fontsize=8) print('') plt.tight_layout(h_pad = 1, w_pad = 1) # Adjust layout to make room for legend if nb_states > 0: plt.subplots_adjust(right=0.85) and save visualization.py Then you should be able to run the function via text_extrack.py or Tutorial_ExTrack.ipynb Let me know if that fixes your problem. If not I can suggest another workaround — Reply to this email directly, view it on GitHub<#7 (comment)>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/AIJKBYPRVTOXXUXTAQ45S3D3SQ6K3AVCNFSM6AAAAACGIZUOK2VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZTEOBYGU3TSMRZG4>. You are receiving this because you authored the thread.Message ID: ***@***.***>

[GuptonLab]

***@***.*** would like to recall the message, "Re: [vanTeeffelenLab/ExTrack] numpy version issue? (Issue #7)".

[FrancoisSimon]

Hi, yes this error makes sense, did you already try to fix extrack installed with pip by modifying the script /opt/anaconda3/envs/spt/lib/python3.13/site-packages/extrack/visualization.py (by changing np.product to np.prod). This should work. If it does not please send me the error message.
Thank you
Francois

[GuptonLab]

Hi Francois! Yes - it worked!! Thanks so much for your detailed instructions despite not having the actual error messages :) Once again I am sorry that I included screen shots in an email and not the actual code. Now that the tutorial is working in full I will move on to loading my own data...

I really appreciate your help!
Best,
Ellen

[FrancoisSimon]

Hi Ellen,
I'm glad that I could help you. If you have any other question about ExTrack or about SPT data analysis let me know. I'll be happy to help :)
Best wishes
François