add option to select trendline typeHEADmain

2 files changed, 76 insertions, 9 deletions

diff --git a/app.py b/app.py
index 18b66c1..f2f3e41 100644
--- a/app.py
+++ b/app.py
@@ -29,7 +29,7 @@ def plot_data(x_data, y_data, std_dev_data, color_picker, labels, df,
               title = "Plot", x_label = "X Axis", y_label = "Y Axis",
               plot_background_color="#ffffff", constant_line=[],
               enable_trendline=True, enable_grid=False,
-              trendline_color="#000000", x_axis_scale="linear", y_axis_scale="linear", trendline_equation=None, chart_type="default"):
+              trendline_color="#000000", x_axis_scale="linear", y_axis_scale="linear", trendline_equation=None, chart_type="default", trendline_type="linear", polynomial_order=2):
     fig, ax = plt.subplots(dpi=300)
 
     plots = []
@@ -77,9 +77,36 @@ def plot_data(x_data, y_data, std_dev_data, color_picker, labels, df,
         else:
             x = df[x_data[0]].astype(float)
             y = df[y_data[0]].astype(float)
-            z = np.polyfit(x, y, 2)
-            p = np.poly1d(z)
-            h, = ax.plot(x,p(x), linestyle="dashed", label="Trendline", color=trendline_color)
+            # z = np.polyfit(x, y, 2)
+            # p = np.poly1d(z)
+            #
+            z = None
+            if trendline_type == 'linear':
+                z = np.polyfit(x, y, 1)
+            elif trendline_type == 'polynomial':
+                z = np.polyfit(x, y, polynomial_order)
+            elif trendline_type == 'exponential':
+                z = np.polyfit(x, np.log(y), 1)
+                p = lambda x: np.exp(z[1]) * np.exp(z[0] * x)
+            elif trendline_type == 'logarithmic':
+                z = np.polyfit(np.log(x), y, 1)
+                p = lambda x: z[1] + z[0] * np.log(x)
+            elif trendline_type == 'power':
+                z = np.polyfit(np.log(x), np.log(y), 1)
+                p = lambda x: np.exp(z[1]) * x ** z[0]
+            else:
+                print("Should not have happened")
+                print("Trendline type: ", trendline_type)
+                z = np.polyfit(x, y, 1)
+                p = np.poly1d(z)
+
+            x_range = np.linspace(x.min(), x.max(), 100)
+            if trendline_type in ['exponential', 'logarithmic', 'power']:
+                y_range = p(x_range)
+            else:
+                y_range = np.poly1d(z)(x_range)
+
+            h, = ax.plot(x_range, y_range, linestyle="dashed", label="Trendline", color=trendline_color)
             handles.append(h)
 
     light_grey = 0.9
@@ -144,7 +171,7 @@ def patent():
 # POST for process_data
 @app.route('/process_data', methods=['POST'])
 def process_data():
-    print(request.form)
+    print("Request form",request.form)
 
     textarea = request.form['excelData']
     df = create_df_from_textarea(textarea)
@@ -239,6 +266,12 @@ def process_data():
     x_axis_scale = request.form.get('xAxisScale', 'linear')
     y_axis_scale = request.form.get('yAxisScale', 'linear')
 
+    trendline_type = request.form.get('trendlineSelect', 'none')
+    polynomial_order = int(request.form.get('polynomialOrder', '2'))
+    if polynomial_order > 6:
+        polynomial_order = 6
+
+
     calc_trendline = request.form.get('calcTrendline', 'off')
     if calc_trendline == 'on':
         enable_trendline = True
@@ -259,7 +292,7 @@ def process_data():
                     trendline_color=color_picker_trendline,
                     x_axis_scale=x_axis_scale,
                     y_axis_scale=y_axis_scale,
-                    trendline_equation=trendline_equation, chart_type=chart_type)
+                    trendline_equation=trendline_equation, chart_type=chart_type, trendline_type=trendline_type, polynomial_order=polynomial_order)
 
     # Return plot as image
     from io import BytesIO
diff --git a/templates/index.html b/templates/index.html
index 46b53e0..ca40c20 100644
--- a/templates/index.html
+++ b/templates/index.html
@@ -194,7 +194,29 @@
     </div>
 
     <div class="row mb-3">
-        <label for="trendlineEquation" class="form-label">Trendline Equation (Leave blank if you want it to be auto-calculated)</label>
+        <div class="col-md-3">
+          <div class="mb-3">
+            <label for="trendlineSelect" class="form-label">Trendline Type:</label>
+            <select name="trendlineSelect" id="trendlineSelect" class="form-select">
+              <option value="none" selected>None</option>
+              <option value="linear">Linear</option>
+              <option value="exponential">Exponential</option>
+              <option value="logarithmic">Logarithmic</option>
+              <option value="polynomial">Polynomial</option>
+              <option value="power">Power</option>
+            </select>
+          </div>
+        </div>
+        <div class="col-md-3">
+          <div class="mb-3" id="polynomialOrderContainer" style="display: none;">
+            <label for="polynomialOrder" class="form-label">Polynomial Order:</label>
+            <input type="number" id="polynomialOrder" name="polynomialOrder" class="form-control" value="2" min="1"/>
+          </div>
+        </div>
+    </div>
+
+    <div class="row mb-3">
+        <label for="trendlineEquation" class="form-label">Trendline Equation Override (Leave blank if you want it to be auto-calculated)</label>
         <input type="text" name="trendlineEquation" id="trendlineEquation" class="form-control" placeholder="">
     </div>
 
@@ -242,6 +264,18 @@
     // add change handler for textarea and execute processData function
     //document.getElementById('excelData').addEventListener('change', processData);
 
+    window.onload = async() => {
+      document.getElementById('trendlineSelect').addEventListener('change', function () {
+        const trendlineType = this.value;
+        const orderContainer = document.getElementById('polynomialOrderContainer');
+        if (trendlineType === 'polynomial') {
+          orderContainer.style.display = 'block';
+        } else {
+          orderContainer.style.display = 'none';
+        }
+      });
+    }
+
 
     function prepareSubmission() {
     const data = document.getElementById('excelData').value;
@@ -271,8 +305,8 @@
 
     function processData() {
     const data = document.getElementById('excelData').value;
-    // const rows = data.split('\n').map(row => row.split('\t'));
-    const rows = data.split('\n').filter(row => row.trim() !== '').map(row => row.split('\t'));
+    const rows = data.split('\n').map(row => row.split('\t'));
+    // const rows = data.split('\n').filter(row => row.trim() !== '').map(row => row.split('\t'));
     if (rows.length === 0) {
         alert('No data found');
         return;