Search enhancements

fieldtrial/grassroots_csv.py

@@ -234,6 +234,7 @@ def create_CSV(plot_data, phenotypes, treatment_factors, plot_id):
     name = plot_id + '.csv' 
     path = os.path.abspath(os.path.join(os.path.dirname( __file__ ), '..', 'filedownload/Files'))
     filename = os.path.join(path, name)
+    data_cleaned_path = os.path.join(path, 'data_cleaned.csv')
     print(filename)
 
     # Actual order of columns given by these headers 
@@ -294,18 +295,18 @@ def create_CSV(plot_data, phenotypes, treatment_factors, plot_id):
         print(removed_columns_message)
         #print(f"The following columns have been removed due to being empty: {', '.join(removed_columns)}")
 
-        with open('data_cleaned.csv', 'w', encoding='UTF8', newline='') as f:
+        with open(data_cleaned_path, 'w', encoding='UTF8', newline='') as f:
             writer = csv.DictWriter(f, fieldnames=[col for col in headers if col in exception or col not in empty_columns])
             writer.writeheader()
             writer.writerows(new_rows)
     else:
     # no empty columns, so write the original data to the cleaned file
-        with open('data_cleaned.csv', 'w', encoding='UTF8', newline='') as f:
+        with open(data_cleaned_path, 'w', encoding='UTF8', newline='') as f:
             writer = csv.DictWriter(f, fieldnames=headers)
             writer.writeheader()
             writer.writerows(new_rows)
 
 
     # replace the original file with the cleaned data
     os.remove(filename)
-    os.rename('data_cleaned.csv', filename)
+    os.rename(data_cleaned_path, filename)

fieldtrial/grassroots_plots.py

@@ -59,7 +59,7 @@ def searchPhenotypeUnit(listPheno, value):
 '''
 test rendering plotly interactive heatmap
 '''
-def plotly_plot(numpy_matrix, accession, title, unit, IDs, treatments):
+def plotly_plot(numpy_matrix, accession, title, unit, IDs, treatments, dates):
 
     ##numpy_matrix = np.flipud(numpy_matrix)      # To Match order shown originally in JS code
     #plotID      = np.flipud(IDs)        
@@ -116,20 +116,38 @@ def plotly_plot(numpy_matrix, accession, title, unit, IDs, treatments):
             labels=dict(x="columns", y="rows", color=units),
             color_continuous_scale=px.colors.sequential.Greens, height=800 )
 
-    #print(treatments)
     if len(treatments)>0:
         treatments = treatments.reshape(Y,X)
         treatments = np.flipud(treatments)
 
-        fig.update_traces(
-        customdata = np.moveaxis([accession, s_matrix, plotID, treatments], 0,-1),
-        #hovertemplate="Accession: %{customdata[0]}<br>raw value: %{customdata[1]:.2f}  <extra></extra>")
-        hovertemplate="Accession: %{customdata[0]}<br>Raw value: %{customdata[1]}<br>Plot ID: %{customdata[2]} (column: %{x}, row: %{y})<br>Treatment: %{customdata[3]} <extra></extra>")
+        if len(dates)>0:  # Only include dates if they are not an empty list
+            dates = dates.reshape(Y, X)
+            dates = np.flipud(dates)
+            fig.update_traces(
+                customdata=np.moveaxis([accession, s_matrix, plotID, treatments, dates], 0, -1),
+                hovertemplate="Accession: %{customdata[0]}<br>Raw value: %{customdata[1]}<br>Plot ID: %{customdata[2]} (column: %{x}, row: %{y})<br>Treatment: %{customdata[3]}<br>Date: %{customdata[4]}<extra></extra>"
+            )
+        else:
+            fig.update_traces(
+                customdata=np.moveaxis([accession, s_matrix, plotID, treatments], 0, -1),
+                hovertemplate="Accession: %{customdata[0]}<br>Raw value: %{customdata[1]}<br>Plot ID: %{customdata[2]} (column: %{x}, row: %{y})<br>Treatment: %{customdata[3]}<extra></extra>"
+            )
+
 
     else:
-        fig.update_traces(
-        customdata = np.moveaxis([accession, s_matrix, plotID], 0,-1),
-        hovertemplate="Accession: %{customdata[0]}<br>Raw value: %{customdata[1]}<br>Plot ID: %{customdata[2]} (column: %{x}, row:%{y})<extra></extra>")
+        if len(dates)>0:  # Only include dates if they are not an empty list
+            dates = dates.reshape(Y, X)
+            dates = np.flipud(dates)
+            fig.update_traces(
+                customdata=np.moveaxis([accession, s_matrix, plotID, dates], 0, -1),
+                hovertemplate="Accession: %{customdata[0]}<br>Raw value: %{customdata[1]}<br>Plot ID: %{customdata[2]} (column: %{x}, row:%{y})<br>Date: %{customdata[3]}<extra></extra>"
+            )
+        else:
+            fig.update_traces(
+                customdata=np.moveaxis([accession, s_matrix, plotID], 0, -1),
+                hovertemplate="Accession: %{customdata[0]}<br>Raw value: %{customdata[1]}<br>Plot ID: %{customdata[2]} (column: %{x}, row:%{y})<extra></extra>"
+            )
+
 
     fig.update_layout(font=dict(family="Courier New, monospace",size=12,color="Black"),title={
         'text': title,
@@ -150,6 +168,35 @@ def plotly_plot(numpy_matrix, accession, title, unit, IDs, treatments):
 
     return plot_div
 
+#########################################################################################################
+def observation_dates(arraysJson, rows, columns, current_name):
+    dt = np.dtype(('U', 80))  # Adjust dtype if date strings are longer
+    matrix = np.zeros((rows, columns), dtype=dt)
+    matrix[:] = "N/A"
+
+    for r in range(len(arraysJson)):
+        i = int(arraysJson[r]['row_index'])
+        j = int(arraysJson[r]['column_index'])
+        i = i - 1
+        j = j - 1
+
+        if 'observations' in arraysJson[r]['rows'][0]:
+            # Filter observations by the selected phenotype
+            relevant_observations = [
+                obs for obs in arraysJson[r]['rows'][0]['observations'] if obs['phenotype']['variable'] == current_name
+            ]
+
+            if relevant_observations:
+                # Sort observations by date and select the latest one
+                relevant_observations.sort(key=lambda x: x.get('date', ''), reverse=True)
+                latest_observation = relevant_observations[0]
+                observation_date = latest_observation.get('date', 'N/A').split('T')[0]  # Keep only the date part
+                matrix[i][j] = observation_date
+
+    matrix = matrix.flatten()
+    return matrix
+
+
 ############################################################################################
 '''
 test rendering seaborn image
@@ -362,18 +409,27 @@ def numpy_data(json, pheno, current_name, total_rows, total_columns):
                     plotsIds = np.append(plotsIds, json[j]['rows'][0]['study_index'] )
 
                elif ( 'observations' in json[j]['rows'][0] ):
-                    if( search_phenotype(json[j]['rows'][0]['observations'], current_name) ):
-                        indexCurrentPhenotype = search_phenotype_index (json[j]['rows'][0]['observations'], current_name)                        
-                        if 'raw_value' in json[j]['rows'][0]['observations'][indexCurrentPhenotype]:
-                            row_raw  = np.append(row_raw, json[j]['rows'][0]['observations'][indexCurrentPhenotype]['raw_value'])
-                        if 'corrected_value' in json[j]['rows'][0]['observations'][indexCurrentPhenotype]:
-                            row_raw  = np.append(row_raw, json[j]['rows'][0]['observations'][indexCurrentPhenotype]['corrected_value'])
-                        row_acc  = np.append(row_acc, json[j]['rows'][0]['material']['accession']) 
-                        plotsIds = np.append(plotsIds, json[j]['rows'][0]['study_index'] )
+                    if search_phenotype(json[j]['rows'][0]['observations'], current_name):
+                        # Instead of getting the first match, we now sort the relevant observations by date
+                        relevant_observations = [
+                            obs for obs in json[j]['rows'][0]['observations'] if lookup_keys(obs, 'phenotype.variable') == current_name
+                        ]
+                        relevant_observations.sort(key=lambda x: x.get('date', ''), reverse=True)
+                        latest_observation = relevant_observations[0]
+                        #print("latest_observations -> ", latest_observation)
+
+                        if 'raw_value' in latest_observation:
+                            row_raw = np.append(row_raw, latest_observation['raw_value'])
+                        if 'corrected_value' in latest_observation:
+                            row_raw = np.append(row_raw, latest_observation['corrected_value'])
+
+                        row_acc = np.append(row_acc, json[j]['rows'][0]['material']['accession'])
+                        plotsIds = np.append(plotsIds, json[j]['rows'][0]['study_index'])
                     else:
-                        row_raw  = np.append(row_raw, np.inf )  # use infinity for N/A data
-                        row_acc  = np.append(row_acc, json[j]['rows'][0]['material']['accession'])  
-                        plotsIds = np.append(plotsIds, json[j]['rows'][0]['study_index'] )
+                        row_raw = np.append(row_raw, np.inf)  # use infinity for N/A data
+                        row_acc = np.append(row_acc, json[j]['rows'][0]['material']['accession'])
+                        plotsIds = np.append(plotsIds, json[j]['rows'][0]['study_index'])
+
                else:
                   if('rows' in json[j]):      # when plots have rows but no observations!!
                         row_raw = np.append(row_raw, np.inf ) #   use infinity for N/A data
@@ -398,18 +454,26 @@ def numpy_data(json, pheno, current_name, total_rows, total_columns):
                     plotsIds = np.append(plotsIds, json[j]['rows'][0]['study_index'] )
 
             elif ( 'observations' in json[j]['rows'][0] ):
-                    if( search_phenotype(json[j]['rows'][0]['observations'], current_name) ):
-                        indexCurrentPhenotype = search_phenotype_index (json[j]['rows'][0]['observations'], current_name)
-                        if 'raw_value' in json[j]['rows'][0]['observations'][indexCurrentPhenotype]:
-                            row_raw  = np.append(row_raw, json[j]['rows'][0]['observations'][indexCurrentPhenotype]['raw_value'])
-                        if 'corrected_value' in json[j]['rows'][0]['observations'][indexCurrentPhenotype]:
-                            row_raw  = np.append(row_raw, json[j]['rows'][0]['observations'][indexCurrentPhenotype]['corrected_value'])
-                        row_acc  = np.append(row_acc, json[j]['rows'][0]['material']['accession']) 
-                        plotsIds = np.append(plotsIds, json[j]['rows'][0]['study_index'] )
+                    if search_phenotype(json[j]['rows'][0]['observations'], current_name):
+                        # Instead of getting the first match, we now sort the relevant observations by date
+                        relevant_observations = [
+                            obs for obs in json[j]['rows'][0]['observations'] if lookup_keys(obs, 'phenotype.variable') == current_name
+                        ]
+                        relevant_observations.sort(key=lambda x: x.get('date', ''), reverse=True)
+                        latest_observation = relevant_observations[0]
+                        #print("latest_observations -> ", latest_observation)
+
+                        if 'raw_value' in latest_observation:
+                            row_raw = np.append(row_raw, latest_observation['raw_value'])
+                        if 'corrected_value' in latest_observation:
+                            row_raw = np.append(row_raw, latest_observation['corrected_value'])
+
+                        row_acc = np.append(row_acc, json[j]['rows'][0]['material']['accession'])
+                        plotsIds = np.append(plotsIds, json[j]['rows'][0]['study_index'])
                     else:
-                        row_raw  = np.append(row_raw, np.inf )
-                        row_acc  = np.append(row_acc, json[j]['rows'][0]['material']['accession'])  
-                        plotsIds = np.append(plotsIds, json[j]['rows'][0]['study_index'] )
+                        row_raw = np.append(row_raw, np.inf)  # use infinity for N/A data
+                        row_acc = np.append(row_acc, json[j]['rows'][0]['material']['accession'])
+                        plotsIds = np.append(plotsIds, json[j]['rows'][0]['study_index'])
             else:
                   if('rows' in json[j]):      # when plots have rows but no observations!!
                         row_raw = np.append(row_raw, np.inf ) #   use infinity for N/A data

fieldtrial/templates/fieldtrial/study.html

@@ -7,6 +7,13 @@
 {% block all_styles_and_scripts %}
 {{ block.super }} 
 <!-- ********************************************************-->
+<script type="text/javascript">
+    var images = [
+        {% for url in imageUrls %}
+            "{{ url }}",
+        {% endfor %}
+    ];
+</script>
     <!-- Leaflet NEWEST VERSION -->
     <link rel="stylesheet" href="{% static 'fieldtrial/SCRIPTS/leaflet/leaflet.css' %}"/>
     <script src="{% static 'fieldtrial/SCRIPTS/leaflet/leaflet.js' %}"></script> 
@@ -77,6 +84,43 @@
         margin: 0 auto;
         text-align: left; 
     }
+
+    .carousel-button {
+        cursor: pointer;
+        background-color: transparent;
+        border: none;
+        font-size: 24px;
+        padding: 10px;
+        z-index: 10; /* Ensures the button is above the image */
+    }
+
+    .image-carousel {
+        display: flex;
+        align-items: center;
+        justify-content: center;
+        position: relative; /* Required for absolute positioning of children */
+    }
+
+    .image-carousel .carouselImage {
+        width: 300px;  /* Fixed width, adjust as necessary */
+        height: auto;  /* Maintain aspect ratio */
+        display: block;
+    }
+
+    .image-container {
+        max-width: 100%;
+        text-align: center; // Centers the text and image
+        position: relative; // Needed for positioning elements inside it
+    }
+
+    .image-title {
+        background-color: #fff; // White background for the text
+        color: #000; // Black text color
+        padding: 5px;
+        display: block;
+        width: 100%; // Take full width of the container
+        text-align: center;
+    }
 
  </style>
 
@@ -284,6 +328,21 @@ <h3 class="table-title centered-title">Study details</h3>
  <tr><td><strong>Handbook pdf:</strong></td><td> 
          <a href="{% lookup_keys study_json "handbook.so:url" %}"> {% lookup_keys study_json "handbook.name" %} </a></td></tr>
  {% endif %}
+
+
+{% if "marti_samples" in study_json %}
+	<tr><td><strong>MARTi Samples:</strong></td>
+	<td> 
+	{% for sample in study_json.marti_samples %}
+		<ul>
+	  <li><a href="{% lookup_keys sample "so:url" %}"> {% lookup_keys sample "so:name" %} </a></li>	
+	  </ul>  
+	{% endfor %}
+	</td>	
+{% else %}
+	<tr><td><strong>No MARTi Samples:</strong></td> <td></td>
+{% endif %}
+
 </table>
 </section>
 

fieldtrial/templates/plots.html

@@ -18,8 +18,62 @@
             height: 600px;
         }
     }
+    .carousel-button {
+        cursor: pointer;
+        background-color: transparent;
+        border: none;
+        font-size: 24px;
+        padding: 10px;
+        top: 50%; /* Center vertically */
+        transform: translateY(-50%); /* Center vertically */
+        position: absolute;
+    }
+
+    .carousel-button.left {
+        left: 50px; /* Adjust as necessary */
+    }
+
+    .carousel-button.right {
+        right: 50px; /* Adjust as necessary */
+    }
+
+    .image-carousel {
+        display: flex;
+        align-items: center;
+        justify-content: center;
+        position: relative; /* Required for absolute positioning of children */
+    }
+
+    .image-carousel .carouselImage {
+        width: 300px;  /* Fixed width, adjust as necessary */
+        height: auto;  /* Maintain aspect ratio */
+        display: block;
+    }
+
+    .image-container {
+        max-width: 100%;
+        text-align: center; // Centers the text and image
+        position: relative; // Needed for positioning elements inside it
+    }
+
+    .image-title {
+        background-color: #fff; // White background for the text
+        color: #000; // Black text color
+        padding: 5px;
+        display: block;
+        width: 100%; // Take full width of the container
+        text-align: center;
+    }
+
 </style>
 
+<script type="text/javascript">
+    var images = [
+        {% for url in imageUrls %}
+            "{{ url }}",
+        {% endfor %}
+    ];
+</script>
 <section id="services" style="padding: 100px 0px 100px 0px ! important;">
     <div class="container">
         <!--style="width: 1170px ! important; margin-right: auto ! important; margin-left: auto ! important;">-->

fieldtrial/templates/study.html

@@ -347,6 +347,7 @@ <h5 class="modal-title"></h5>
 
 
 </table>
+
 </section>
 -->