fixing typos and improving codes

Author: luisub

Module2-ImageProcessing/M2A_Basic_Image_Processing.ipynb

@@ -15,10 +15,10 @@
     "               <left>Basic Image Manipulation in Python</left>\n",
     "              </h1>\n",
     "              <p><left>============================================================================</left> </p>\n",
-    "<pre>Course: BIOM 421, Spring 2024\n",
-    "Instructor: Brian Munsky\n",
-    "Authors: Dr. Zach Fox, Dr. Luis Aguilera, Brian Munsky\n",
-    "Contact Info: munsky@colostate.edu\n",
+    "<pre>Course: UQ-Bio 2024\n",
+    "Instructor: Luis Aguilera\n",
+    "Authors: Luis Aguilera, Will Raymond, Brian Munsky\n",
+    "Contact Info: luis.aguilera@colostate.edu\n",
     "</pre>\n",
     "         </div>\n",
     "    </p>\n",
@@ -200,7 +200,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# conda install pytorch\n",
+    "# conda remove pytorch\n",
     "# conda install pytorch\n",
     "# pip uninstall cellpose\n",
     "# pip install cellpose\n"
@@ -253,9 +253,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#from biom421 import codes\n",
-    "#students = codes.spring2024Students()\n",
-    "students = ['name1', 'name'] #codes.spring2024Students()"
+    "students = ['Daria', 'Wiktoria','Jinyi','Wei','Pilar','Camila','Jayden','Humberto',\n",
+    "'Jakini','Varvara','Kanniese','Kristi','Eliud','Nam','Lakshay','Margaret',\n",
+    "'Grace','Apurv','Yinfei','Samantha','Yingli','Rena','Emily','Pegah','Al-Bashir']"
    ]
   },
   {
@@ -1356,8 +1356,8 @@
    "outputs": [],
    "source": [
     "# Installing libraries\n",
-    "%pip install trackpy\n",
-    "import trackpy as tp # Library for particle tracking"
+    "#%pip install trackpy\n",
+    "#import trackpy as tp # Library for particle tracking"
    ]
   },
   {
@@ -1372,7 +1372,7 @@
     "particle_size = 5 # according to the documentation must be an odd number 3,5,7,9 etc.\n",
     "minimal_intensity_for_selection = 0 # minimal intensity to detect a particle.\n",
     "# \"spots_detected_dataframe\" is a pandas data frame that contains the information about the detected spots\n",
-    "spots_detected_dataframe = tp.locate(img_spots, diameter=particle_size, minmass=minimal_intensity_for_selection)\n"
+    "spots_detected_dataframe = tp.locate(img_spots, diameter=particle_size, minmass=minimal_intensity_for_selection)"
    ]
   },
   {
@@ -1614,7 +1614,6 @@
     "    # Find the shortest distance in the matrix and record the indexes\n",
     "    indexes = np.unravel_index(np.argmin(dist_matrix, axis=None), dist_matrix.shape)\n",
     "    indexList.append(indexes)\n",
-    "\n",
     "    # Set all entries in the row and column of the minimum distance to infinity\n",
     "    dist_matrix[indexes[0],:] = np.inf\n",
     "    dist_matrix[:,indexes[1]] = np.inf\n",
@@ -1634,9 +1633,7 @@
     "\n",
     "# Create figure with three columns of 20 images\n",
     "fig, ax = plt.subplots(20,3, figsize=(9, 20))\n",
-    "\n",
-    "img_to_show = img_spots_filtered\n",
-    "\n",
+    "img_to_show = img_spots_filtered.copy()\n",
     "# Loop through the first 20 matches, and make a plot for each\n",
     "for i in range(20):\n",
     "    # Plot the image\n",

Module2-ImageProcessing/M2B_Segmenting_Images.ipynb

@@ -15,10 +15,10 @@
     "               <left>Particle Tracking</left>\n",
     "              </h1>\n",
     "              <p><left>============================================================================</left> </p>\n",
-    "<pre>Course: BIOM 421, Spring 2024\n",
-    "Instructor: Brian Munsky\n",
-    "Authors: Dr. Luis Aguilera, Dr. Zach Fox,  Brian Munsky\n",
-    "Contact Info: munsky@colostate.edu\n",
+    "<pre>Course: UQ-Bio 2024\n",
+    "Instructor: Luis Aguilera\n",
+    "Authors: Luis Aguilera, Will Raymond, Brian Munsky\n",
+    "Contact Info: luis.aguilera@colostate.edu\n",
     "</pre>\n",
     "         </div>\n",
     "    </p>\n",
@@ -56,9 +56,9 @@
     "\n",
     "## List of objectives\n",
     "\n",
-    "1.   Simulate 2D random walks.\n",
-    "2.   Implement a code to track single particles.\n",
-    "3.   Calculate mean square displacement and diffusion coefficients.\n",
+    "1.   **Simulate 2D random walks.**\n",
+    "2.   Implement a code to **track single particles**.\n",
+    "3.   Calculate **mean square displacement** and **diffusion coefficients**.\n",
     "\n",
     "4.   Use the scientific libraries needed to segment and track single molecules in live cells."
    ]
@@ -116,9 +116,9 @@
    },
    "outputs": [],
    "source": [
-    "#from biom421 import codes\n",
-    "#students = codes.spring2024Students()\n",
-    "students = ['name1', 'name'] #codes.spring2024Students()"
+    "students = ['Daria', 'Wiktoria','Jinyi','Wei','Pilar','Camila','Jayden','Humberto',\n",
+    "'Jakini','Varvara','Kanniese','Kristi','Eliud','Nam','Lakshay','Margaret',\n",
+    "'Grace','Apurv','Yinfei','Samantha','Yingli','Rena','Emily','Pegah','Al-Bashir']"
    ]
   },
   {
@@ -722,7 +722,6 @@
     "def movieFrame(i):\n",
     "  ax.clear()\n",
     "  ax.imshow(img_with_spots[i,:,:,0],cmap= 'gray')\n",
-    "\n",
     "  for iParticle in range(len(list_trajectories_short)):\n",
     "      x_val = [x[1] for x in list_trajectories_short[iParticle][:i]]\n",
     "      y_val = [x[0] for x in list_trajectories_short[iParticle][:i]]\n",
@@ -732,9 +731,7 @@
     "        \n",
     "        # Add a line to show the trajectory of the spot.\n",
     "        ax.plot(x_val,y_val, linewidth = 2, alpha=0.75)\n",
-    "\n",
     "  return [fig]\n",
-    "\n",
     "plt.close()\n",
     "anim = animation.FuncAnimation(fig, movieFrame, frames=img_with_spots.shape[0], interval=50, blit=True)\n",
     "\n",
@@ -1189,7 +1186,7 @@
     "ax[1].imshow(img_with_spots_noisy[selected_time_point,:,:,0], cmap=plt.cm.gray, alpha=0.5)\n",
     "for i in range(0,len(list_center_mass[selected_time_point])):\n",
     "  ax[1].plot(list_center_mass[selected_time_point][i][0], list_center_mass[selected_time_point][i][1], color='r',marker='*')\n",
-    "ax[1].set_title('Binary image with pixels above treshold')\n",
+    "ax[1].set_title('Binary image with pixels above threshold')\n",
     "plt.show()"
    ]
   },
@@ -1618,7 +1615,7 @@
     "particle_size = 7 # according to the documentation must be an odd number 3,5,7,9 etc.\n",
     "minimal_intensity_for_selection = 0 # minimal intensity to detect a particle.\n",
     "\n",
-    "# \"f\" is a pandas data freame that contains the information about the detected spots\n",
+    "# \"f\" is a pandas data frame that contains the information about the detected spots\n",
     "f = tp.locate(video[10,:,:,0], particle_size, minmass=minimal_intensity_for_selection)\n",
     "\n",
     "plt.rcParams[\"figure.figsize\"] = (5,5)\n",
@@ -1670,7 +1667,7 @@
     "plt.rcParams[\"figure.figsize\"] = (10,10) # if movie is too big, change size to (7,7)\n",
     "def figure_viewer_tr(time,mass_text, drop_size):\n",
     "    ch = 0\n",
-    "    f = tp.locate(video[time,:,:,ch],drop_size, minmass=mass_text,maxsize=7,percentile=60) # \"f\" is a pandas data freame that contains the infomation about the detected spots\n",
+    "    f = tp.locate(video[time,:,:,ch],drop_size, minmass=mass_text,maxsize=7,percentile=60) # \"f\" is a pandas data frame that contains the infomation about the detected spots\n",
     "    tp.annotate(f,video[time,:,:,ch]);  # tp.anotate is a trackpy function that displays the image with the detected spots\n",
     "\n",
     "values_size=[3,5,7,9] # Notice value must be an odd number.\n",
@@ -1720,11 +1717,11 @@
     "# Loop through each frame of the video, run TP to detect spots, and then create a single\n",
     "# data frame for all time points.\n",
     "ch = 0\n",
-    "df_TrackPy = tp.locate(video[0,:,:,ch],selected_size, minmass=selected_intensity,maxsize=7,percentile=60) # \"f\" is a pandas data freame that contains the infomation about the detected spots\n",
+    "df_TrackPy = tp.locate(video[0,:,:,ch],selected_size, minmass=selected_intensity,maxsize=7,percentile=60) # \"f\" is a pandas data frame that contains the infomation about the detected spots\n",
     "df_TrackPy['frame'] = 0\n",
     "\n",
     "for iFrame in range(1,video.shape[0]):\n",
-    "    f = tp.locate(video[iFrame,:,:,ch],selected_size, minmass=selected_intensity,maxsize=7,percentile=60) # \"f\" is a pandas data freame that contains the infomation about the detected spots\n",
+    "    f = tp.locate(video[iFrame,:,:,ch],selected_size, minmass=selected_intensity,maxsize=7,percentile=60) # \"f\" is a pandas data frame that contains the infomation about the detected spots\n",
     "    f['frame'] = iFrame\n",
     "    df_TrackPy = pd.concat([df_TrackPy,f])\n",
     "\n",
@@ -1749,7 +1746,7 @@
    "outputs": [],
    "source": [
     "# Create a function that extracts the y and x coordinates from the dataframe and\n",
-    "# return an exteneded data frame that includes a boolean true if the spot is in \n",
+    "# return an extended data frame that includes a boolean true if the spot is in \n",
     "# the mask and false otherwise.\n",
     "def spots_in_mask(f,mask):\n",
     "    # extracting the contours in the image\n",
@@ -1981,15 +1978,11 @@
    "outputs": [],
    "source": [
     "# Make a movie of the original, but now add squares over the tracked particles.\n",
-    "\n",
     "# Plotting spots as a video\n",
-    "\n",
     "fig, ax = plt.subplots(figsize=(7,7))\n",
-    "\n",
     "def movieFrame(i):\n",
     "  ax.clear()\n",
     "  ax.imshow(video[i,:,:,0],cmap= 'gray')\n",
-    "\n",
     "  for iParticle in range(0,dfp['particle'].nunique() ):\n",
     "      x_val = dfp.loc[(dfp['particle']==iParticle) & (dfp['frame']<=i) ].x.values\n",
     "      y_val = dfp.loc[(dfp['particle']==iParticle) & (dfp['frame']<=i) ].y.values\n",
@@ -1999,9 +1992,7 @@
     "        \n",
     "        # Add a line to show the trajectory of the spot.\n",
     "        ax.plot(x_val,y_val, linewidth = 2, alpha=0.75)\n",
-    "\n",
     "  return [fig]\n",
-    "\n",
     "plt.close()\n",
     "anim = animation.FuncAnimation(fig, movieFrame, frames=video.shape[0], interval=50, blit=True)\n",
     "from IPython.display import HTML\n",
@@ -2023,24 +2014,20 @@
     "    ax[0].clear(); ax[1].clear()\n",
     "    x_val = dfp.loc[(dfp['particle']==spot_number) & (dfp['frame']==i) ].x.values\n",
     "    y_val = dfp.loc[(dfp['particle']==spot_number) & (dfp['frame']==i) ].y.values   \n",
-    "    \n",
     "    ax[0].imshow(video[i,:,:,0],cmap= 'gray')\n",
     "    ax[0].plot(x_val,y_val, 'o', linewidth = 1, markersize=8, color='y', alpha=0.25)\n",
-    "\n",
     "    if len(x_val)>0:    \n",
     "      ylim = [int(x_val[0]-7), int(x_val[0]+8)]\n",
     "      xlim = [int(y_val[0]-7), int(y_val[0]+8)]\n",
     "      ax[1].imshow(video[i,xlim[0]:xlim[1],ylim[0]:ylim[1],1],cmap= 'Spectral_r')\n",
     "    return [fig]\n",
-    "\n",
     "  plt.close()\n",
     "  anim = animation.FuncAnimation(fig, movieFrame, frames=video.shape[0], interval=50, blit=True)\n",
     "  return anim\n",
     "\n",
     "anim = movieViewer(spot_number=3)\n",
     "HTML(anim.to_html5_video())\n",
     "\n",
-    "\n",
     "# interactive_plot = interactive(movieViewer,spot_number = widgets.IntSlider(min=0,max=dfp['particle'].nunique(),value=0,description='Particle Number'),continuous_update=False)\n",
     "# controls = HBox(interactive_plot.children[:-1], layout = Layout(flex_flow='row wrap'))\n",
     "# output = interactive_plot.children[-1]\n",