integrating new subset filtering in notebook

analyze_traj_gui.ipynb

@@ -4,7 +4,7 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
-    "scrolled": true
+    "scrolled": false
    },
    "outputs": [
     {
@@ -137,7 +137,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "5a4c6a72274844c8bcea95fbb70271cf",
+       "model_id": "7041dba9e9224efabccc5c215b5d07c2",
        "version_major": 2,
        "version_minor": 0
       },
@@ -151,7 +151,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "c5be99340492436392e402af6a686080",
+       "model_id": "530844d2d877412da20f2f3a59708827",
        "version_major": 2,
        "version_minor": 0
       },
@@ -165,7 +165,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "c69360140dd349d691c9ae7d4696b589",
+       "model_id": "f266cdf81f7343ddb776d5d03d0ff818",
        "version_major": 2,
        "version_minor": 0
       },
@@ -215,7 +215,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "375e90c3e1644c31bf470f9ca1f34ee8",
+       "model_id": "0253278378284ae4b629c394f03f84cf",
        "version_major": 2,
        "version_minor": 0
       },
@@ -229,8 +229,10 @@
    ],
    "source": [
     "# get position file path\n",
-    "data_dir=fc_table.selected_path\n",
-    "data_file=fc_table.selected\n",
+    "#data_dir = fc_table.selected_path\n",
+    "#data_file = fc_table.selected\n",
+    "data_dir = '/Users/amichaut/Desktop/Fluo-N3DH-CE/'\n",
+    "data_file = \"/Users/amichaut/Desktop/Fluo-N3DH-CE/positions.csv\"\n",
     "\n",
     "if data_file is None: \n",
     "    raise Exception(\"**ERROR: no data table has been selected**\")\n",
@@ -276,7 +278,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "a3366b16fb304cd9bdf00ae9f14ada98",
+       "model_id": "64c3f889533d4ff5a41f23a8c1257c86",
        "version_major": 2,
        "version_minor": 0
       },
@@ -314,7 +316,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "6ef3cf9f4f3349989245265ece0ca816",
+       "model_id": "43c64f65944e4b5eaf3a4906e3edc7f2",
        "version_major": 2,
        "version_minor": 0
       },
@@ -340,7 +342,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "de9330aeef4c4f008a4a0256d75829e2",
+       "model_id": "5a5f91796ca74c80bad17a87afa4189e",
        "version_major": 2,
        "version_minor": 0
       },
@@ -354,7 +356,8 @@
    ],
    "source": [
     "# get image file path\n",
-    "im_file = fc_im.selected\n",
+    "#im_file = fc_im.selected\n",
+    "im_file = \"/Users/amichaut/Desktop/Fluo-N3DH-CE/stack.tif\"\n",
     "\n",
     "# analyze image\n",
     "y_size,x_size = [512,512] #default size of an image to inialize the make info widget \n",
@@ -703,7 +706,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "72eacd9fe3f1463eae53746242419d57",
+       "model_id": "19bc28b6c98a4e579df02accb458ce13",
        "version_major": 2,
        "version_minor": 0
       },
@@ -717,7 +720,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "dab2a390c9274afa88dc51c554d1719f",
+       "model_id": "7199e707f6e540e4808f2c5f5e2c4a48",
        "version_major": 2,
        "version_minor": 0
       },
@@ -731,7 +734,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "bb5663ce2bc64f4ea80efe25d79ddcd3",
+       "model_id": "2b80d40d7c5a47b590e267f98187df7f",
        "version_major": 2,
        "version_minor": 0
       },
@@ -745,7 +748,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "8f62e1f8b0584e3480b5fa4c387c58da",
+       "model_id": "67d5ab26e7224999adf42cf093f2e2a7",
        "version_major": 2,
        "version_minor": 0
       },
@@ -771,7 +774,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "3b289239be424d63bfd8b7648fbd9347",
+       "model_id": "806844b27ec54441978447aec7d5f5cd",
        "version_major": 2,
        "version_minor": 0
       },
@@ -797,7 +800,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "2978aec72b304ee0916a9aea04012bf3",
+       "model_id": "933c61c3da574f7db800cf26e7f2f597",
        "version_major": 2,
        "version_minor": 0
       },
@@ -823,7 +826,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "592d08b791054377be9ca9c6193c520b",
+       "model_id": "50964b0930c44ec48522e815982ee509",
        "version_major": 2,
        "version_minor": 0
       },
@@ -943,7 +946,68 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 14,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/markdown": [
+       "**View trajectories on a Napari viewer before plotting**"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "If not working, please check Napari installation: https://napari.org/"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "c471f7b7992c485599572669cdd5609b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Button(description='Show viewer!', style=ButtonStyle())"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "z_step = info['z_step']\n",
+    "if z_step == 0:\n",
+    "    z_step = lengthscale  # if z_step not given, same as lengthscale\n",
+    "    \n",
+    "printmd('**View trajectories on a Napari viewer before plotting**')\n",
+    "printmd('If not working, please check Napari installation: https://napari.org/')\n",
+    "\n",
+    "viewer_wid = widgets.Button(value=True, description='Show viewer!')\n",
+    "\n",
+    "viewer_wid.on_click(lambda obj: tpl.view_traj(df, image=image, z_step=info['z_step']))\n",
+    "\n",
+    "display(viewer_wid)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
    "metadata": {
     "scrolled": false
    },
@@ -963,7 +1027,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "7aab05891e674262b124a0b7689b7d20",
+       "model_id": "f4ecf3ca6af74906b17ec207feab70a4",
        "version_major": 2,
        "version_minor": 0
       },
@@ -977,7 +1041,7 @@
     {
      "data": {
       "text/markdown": [
-       "Do you want to analyze them independently or together?"
+       "If you define several subsets, do you want to analyze them separately or together?"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -989,7 +1053,7 @@
     {
      "data": {
       "text/markdown": [
-       "Warning: if analyzed together, no other coding than the color identifying the subset will be available for trajectory plotting"
+       "If analyzed together, subsets will be plotted together. If analyzed separately, each subset will be plotted on individual plots."
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -1001,12 +1065,12 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "974fd79b8cdb493792b4dbb437199f85",
+       "model_id": "bc3478428cf646ecaf7e01c14b378b0f",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "ToggleButtons(description='Analysis', options=('independently', 'together'), value='independently')"
+       "ToggleButtons(description='Analysis', options=('separately', 'together'), value='separately')"
       ]
      },
      "metadata": {},
@@ -1026,7 +1090,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 17,
    "metadata": {
     "scrolled": false
    },
@@ -1058,7 +1122,121 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "5553587f7e1948d08820eef59e43b602",
+       "model_id": "6c0299ffdf07466790f828d21b1e95b7",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Text(value='', description='Subset name:', placeholder='optional', style=DescriptionStyle(description_width='i…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "**Crop a region**"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "You can draw it on the image or select it with the slider (values in pixels).If you do both, only the drawn region will be kept. If you select several regions on the image, they will be divided into several subsets"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "Draw using the rectangle shape, hit ENTER while you're done. Then close the image viewer. If you want more details about the email viewer please visit https://napari.org/"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "2676d429047f4d18ba78acc514b11810",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "VBox(children=(LoadedButton(description='Draw ROI', style=ButtonStyle()), HBox(children=(FloatRangeSlider(valu…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "**Select data based on trajectories duration or frame subset**"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "ce72b095b55b4431a772713ae09ae685",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "HBox(children=(IntRangeSlider(value=(0, 194), description='Frame subset:', max=194, style=SliderStyle(descript…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "### Subset #2"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "You can give it a custom name that will be used for saving data"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "89beef9c8fa2410f9ee779a2e5f6b637",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1108,7 +1286,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "3dface503d3c4d8696b0f75276cf3edd",
+       "model_id": "b09009bebd4d4c43898db2568a045135",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1134,7 +1312,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "1a2e4d3638b949bd96ae9a90a5020c2f",
+       "model_id": "095121f3157943148a51c6f07b6e43fc",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1204,7 +1382,6 @@
     "    xlim_wid_list.append(xlim_wid)\n",
     "    ylim_wid_list.append(ylim_wid)\n",
     "    drawer_wid_list.append(drawer_wid)\n",
-    "    output_list.append(output)\n",
     "    if len(zlim) > 0:\n",
     "        zlim_wid_list.append(zlim_wid)\n",
     "    else:\n",
@@ -1240,7 +1417,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": 19,
    "metadata": {
     "scrolled": true
    },
@@ -1284,7 +1461,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "9491bb49ba354304b0fba12b471afedd",
+       "model_id": "ff4a5012213c444e8b10a0857e04a409",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1337,8 +1514,8 @@
     "    # if several subsets get values of xlim, ylim, while keeping other filters constant\n",
     "    for j in range(len(xlim_list)):  \n",
     "        #name\n",
-    "        if len(xlim_list) > 1:  # if several subsets, modify name\n",
-    "            name = name_wid_list[i].value + '_{}'.format(j)\n",
+    "        if len(xlim_list) > 1:  # if several subsets, modify name: name_number if name is empty: number\n",
+    "            name = name_wid_list[i].value + '_{}'.format(j) if name_wid_list[i].value != '' else '{}'.format(j)\n",
     "        else: \n",
     "            name = name_wid_list[i].value\n",
     "        filters.append({'xlim':xlim_list[j],\n",
@@ -1364,7 +1541,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 20,
    "metadata": {
     "scrolled": false
    },
@@ -1380,82 +1557,6 @@
      },
      "metadata": {},
      "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "### Set #1"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "You can give it a custom name that will be used for saving data"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "7f48c5818e2d475cbbcec00767a20680",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Text(value='', description='Set name:', placeholder='optional', style=DescriptionStyle(description_width='init…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "Give a list of ids or select trajectories in a specific region during a specific frame intervalle using the viewer."
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "Use the ids given by the track analyzer, you need to generate the database once to access them, (visualizing the trajectories with the printed labels can be helpful)"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "207fa2d29d2a43f9b741f66ad061c677",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "VBox(children=(Text(value='', description='Id list:', placeholder='comma separated ids'), LoadedButton(descrip…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
     }
    ],
    "source": [
@@ -1515,7 +1616,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 76,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -1529,116 +1630,11 @@
      },
      "metadata": {},
      "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "printmd(\"**Don't forget to run this cell!**\")  # no output cell, make it visible\n",
-    "\n",
-    "new_filters = []\n",
-    "# for each set of filters, copy them to new sets of filters modified by the trajectory filters\n",
-    "for filt in filters:   \n",
-    "    for i in range(set_num_wid.value):\n",
-    "        # trajectory list selection\n",
-    "        track_list_val = track_list_wid_list[i].value\n",
-    "        if track_list_val == '':\n",
-    "            track_list_val = None\n",
-    "        else:\n",
-    "            try:\n",
-    "                track_list_val = [int(e) for e in track_list_val.split(',')]\n",
-    "            except:\n",
-    "                print(\"ERROR: a value in the list is not a number\")\n",
-    "                track_list_val = None\n",
-    "\n",
-    "        # ROI selection\n",
-    "        track_xlim_list, track_ylim_list, track_zlim_ = retrieve_region_wid_values(track_drawer_wid_list[i],\n",
-    "                                                                 track_xlim_wid_list[i],\n",
-    "                                                                 track_ylim_wid_list[i],\n",
-    "                                                                 track_zlim_wid_list[i])\n",
-    "\n",
-    "        # if several sets, get values of xlim, ylim, while keeping other filters constant\n",
-    "        for j in range(len(track_xlim_list)):\n",
-    "            ROI = {'xlim': track_xlim_list[j],\n",
-    "                'ylim': track_ylim_list[j],\n",
-    "                'zlim': track_zlim_,\n",
-    "                'frame_lim': track_frame_subset_wid_list[i].value}\n",
-    "            #name\n",
-    "            if len(track_xlim_list) > 1:  # if several subsets, modify name\n",
-    "                name = track_name_wid_list[i].value + '_{}'.format(j)\n",
-    "            else: \n",
-    "                name = track_name_wid_list[i].value\n",
-    "            \n",
-    "            # add new filters to existing filters\n",
-    "            new_filt = dict(filt)  # make copy of old filters\n",
-    "            new_filt['track_list'] = track_list_val\n",
-    "            new_filt['track_ROI'] = ROI\n",
-    "            if new_filt['name'] == '':\n",
-    "                new_filt['name'] = name  # name = setname\n",
-    "            else:\n",
-    "                new_filt['name'] += '_'+name  # name = subsetname_setname\n",
-    "                \n",
-    "            # store in a new list of filters\n",
-    "            new_filters.append(new_filt)\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 83,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[{'xlim': (105.0, 614.0),\n",
-       "  'ylim': (91.0, 436.0),\n",
-       "  'zlim': (7.0, 28.0),\n",
-       "  'frame_subset': (0, 194),\n",
-       "  'min_traj_len': 0,\n",
-       "  'max_traj_len': 195,\n",
-       "  'name': 'trkfdze_0',\n",
-       "  'track_list': None,\n",
-       "  'track_ROI': {'xlim': [-10.545229477872766, 338.72324599745474],\n",
-       "   'ylim': [119.82262915942106, 423.41753476489805],\n",
-       "   'zlim': (7.0, 28.0),\n",
-       "   'frame_lim': (68, 68)}},\n",
-       " {'xlim': (105.0, 614.0),\n",
-       "  'ylim': (91.0, 436.0),\n",
-       "  'zlim': (7.0, 28.0),\n",
-       "  'frame_subset': (0, 194),\n",
-       "  'min_traj_len': 0,\n",
-       "  'max_traj_len': 195,\n",
-       "  'name': 'trkfdze_1',\n",
-       "  'track_list': None,\n",
-       "  'track_ROI': {'xlim': [424.6970245759969, 610.0779846359784],\n",
-       "   'ylim': [60.715656386673324, 325.3536935737484],\n",
-       "   'zlim': (7.0, 28.0),\n",
-       "   'frame_lim': (68, 68)}}]"
-      ]
-     },
-     "execution_count": 83,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Trajectory analysis module"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 78,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
+    },
     {
      "data": {
       "text/markdown": [
-       "**View trajectories on a Napari viewer before plotting**"
+       "You set 2 subsets. Edit their names and order to be plotted if needed."
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -1647,27 +1643,43 @@
      "metadata": {},
      "output_type": "display_data"
     },
+    {
+     "name": "stdout",