diff --git a/src/nomad_measurements/utils.py b/src/nomad_measurements/utils.py
index 7fbed4aa..61b984a1 100644
--- a/src/nomad_measurements/utils.py
+++ b/src/nomad_measurements/utils.py
@@ -261,3 +261,35 @@ def modify_scan_data(scan_data: dict, scan_type: str):
                 data = data[0].reshape(-1)
             output[key] = data * value[0].units
         return output
+
+def get_bounding_range_2d(ax1, ax2):
+    '''
+    Calculates the range of the smallest rectangular grid that can contain arbitrarily
+    distributed 2D data.
+
+    Args:
+        ax1 (np.ndarray): array of first axis values
+        ax2 (np.ndarray): array of second axis values
+
+    Returns:
+        (list, list): ax1_range, ax2_range
+    '''
+    ax1_range_length = np.max(ax1) - np.min(ax1)
+    ax2_range_length = np.max(ax2) - np.min(ax2)
+
+    if ax1_range_length > ax2_range_length:
+        ax1_range = [np.min(ax1),np.max(ax1)]
+        ax2_mid = np.min(ax2) + ax2_range_length/2
+        ax2_range = [
+            ax2_mid-ax1_range_length/2,
+            ax2_mid+ax1_range_length/2,
+        ]
+    else:
+        ax2_range = [np.min(ax2),np.max(ax2)]
+        ax1_mid = np.min(ax1) + ax1_range_length/2
+        ax1_range = [
+            ax1_mid-ax2_range_length/2,
+            ax1_mid+ax2_range_length/2,
+        ]
+
+    return ax1_range, ax2_range
\ No newline at end of file
diff --git a/src/nomad_measurements/xrd/plotting.py b/src/nomad_measurements/xrd/plotting.py
deleted file mode 100644
index 9293918e..00000000
--- a/src/nomad_measurements/xrd/plotting.py
+++ /dev/null
@@ -1,165 +0,0 @@
-import numpy as np
-import plotly.express as px
-from scipy.interpolate import griddata
-
-def plot_1d(x, y):
-    '''
-    Plot the 1D diffractogram.
-
-    Args:
-        x (np.ndarray): array of x values
-        y (np.ndarray): array of y values
-
-    Returns:
-        (dict, dict): line_linear, line_log
-    '''
-    fig_line_linear = px.line(
-        x = x,
-        y = y,
-        labels = {
-            'x': '2θ (°)',
-            'y': 'Intensity',
-        },
-        title = 'Intensity (linear scale)',
-    )
-    json_line_linear = fig_line_linear.to_plotly_json()
-
-    fig_line_log = px.line(
-        x = x,
-        y = y,
-        log_y = True,
-        labels = {
-            'x': '2θ (°)',
-            'y': 'Intensity',
-        },
-        title = 'Intensity (log scale)',
-    )
-    json_line_log = fig_line_log.to_plotly_json()
-
-    return json_line_linear, json_line_log
-
-def plot_2d_range(ax1, ax2):
-    '''
-    Calculate the range of the 2D plot for generation of regular grid.
-    Finds the smallest box that can contain the data.
-
-    Args:
-        ax1 (np.ndarray): array of first axis values
-        ax2 (np.ndarray): array of second axis values
-
-    Returns:
-        (list, list): ax1_range, ax2_range
-    '''
-    ax1_range_length = np.max(ax1) - np.min(ax1)
-    ax2_range_length = np.max(ax2) - np.min(ax2)
-
-    if ax1_range_length > ax2_range_length:
-        ax1_range = [np.min(ax1),np.max(ax1)]
-        ax2_mid = np.min(ax2) + ax2_range_length/2
-        ax2_range = [
-            ax2_mid-ax1_range_length/2,
-            ax2_mid+ax1_range_length/2,
-        ]
-    else:
-        ax2_range = [np.min(ax2),np.max(ax2)]
-        ax1_mid = np.min(ax1) + ax1_range_length/2
-        ax1_range = [
-            ax1_mid-ax2_range_length/2,
-            ax1_mid+ax2_range_length/2,
-        ]
-
-    return ax1_range, ax2_range
-
-def plot_2d_rsm(two_theta, omega, q_parallel, q_perpendicular, intensity):
-    '''
-    Plot the 2D RSM diffractogram.
-
-    Args:
-        two_theta (pint.Quantity): array of 2θ values
-        omega (pint.Quantity): array of ω values
-        q_parallel (pint.Quantity): array of Q_parallel values
-        q_perpendicular (pint.Quantity): array of Q_perpendicular values
-        intensity (pint.Quantity): array of intensity values
-
-    Returns:
-        (dict, dict): json_2theta_omega, json_q_vector
-    '''
-    # Plot for 2theta-omega RSM
-    x = omega.magnitude
-    y = two_theta.magnitude
-    log_z = np.log10(intensity)
-    x_range, y_range = plot_2d_range(x, y)
-
-    fig_2theta_omega = px.imshow(
-        img = np.around(log_z,3).T,
-        x = np.around(x,3),
-        y = np.around(y,3),
-        color_continuous_scale = 'inferno',
-    )
-    fig_2theta_omega.update_layout(
-        title = 'RSM plot: Intensity (log-scale) vs Axis position',
-        xaxis_title = 'ω (°)',
-        yaxis_title = '2θ (°)',
-        xaxis = dict(
-            autorange = False,
-            fixedrange = False,
-            range = x_range,
-        ),
-        yaxis = dict(
-            autorange = False,
-            fixedrange = False,
-            range = y_range,
-        ),
-        width = 600,
-        height = 600,
-    )
-    json_2theta_omega = fig_2theta_omega.to_plotly_json()
-
-    # Plot for RSM in Q-vectors
-    if q_parallel is not None and q_perpendicular is not None:
-        x = q_parallel.to('1/angstrom').magnitude.flatten()
-        y = q_perpendicular.to('1/angstrom').magnitude.flatten()
-        # q_vectors lead to irregular grid
-        # generate a regular grid using interpolation
-        x_regular = np.linspace(x.min(),x.max(),intensity.shape[0])
-        y_regular = np.linspace(y.min(),y.max(),intensity.shape[1])
-        x_grid, y_grid = np.meshgrid(x_regular,y_regular)
-        z_interpolated = griddata(
-            points = (x,y),
-            values = intensity.flatten(),
-            xi = (x_grid,y_grid),
-            method = 'linear',
-            fill_value = intensity.min(),
-        )
-        log_z_interpolated = np.log10(z_interpolated)
-        x_range, y_range = plot_2d_range(x_regular,y_regular)
-
-        fig_q_vector = px.imshow(
-            img = np.around(log_z_interpolated,3),
-            x = np.around(x_regular,3),
-            y = np.around(y_regular,3),
-            color_continuous_scale = 'inferno',
-            range_color = [np.nanmin(log_z[log_z != -np.inf]), log_z_interpolated.max()],
-        )
-        fig_q_vector.update_layout(
-            title = 'RSM plot: Intensity (log-scale) vs Q-vectors',
-            xaxis_title = 'Q_parallel (1/Å)',
-            yaxis_title = 'Q_perpendicular (1/Å)',
-            xaxis = dict(
-                autorange = False,
-                fixedrange = False,
-                range = x_range,
-            ),
-            yaxis = dict(
-                autorange = False,
-                fixedrange = False,
-                range = y_range,
-            ),
-            width = 600,
-            height = 600,
-        )
-        json_q_vector = fig_q_vector.to_plotly_json()
-
-        return json_2theta_omega, json_q_vector
-
-    return json_2theta_omega, None
diff --git a/src/nomad_measurements/xrd/schema.py b/src/nomad_measurements/xrd/schema.py
index ff8f2f72..60c07a56 100644
--- a/src/nomad_measurements/xrd/schema.py
+++ b/src/nomad_measurements/xrd/schema.py
@@ -64,8 +64,7 @@
     NOMADMeasurementsCategory,
 )
 from nomad_measurements.xrd import readers
-from nomad_measurements.xrd import plotting
-from nomad_measurements.utils import merge_sections
+from nomad_measurements.utils import merge_sections, get_bounding_range_2d
 
 if TYPE_CHECKING:
     from nomad.datamodel.datamodel import (
@@ -362,7 +361,7 @@ def derive_n_values(self):
         description='Integration time per channel',
     )
 
-class XRDResult1D(XRDResult, PlotSection):
+class XRDResult1D(XRDResult):
     '''
     Section containing the result of a 1D X-ray diffraction scan.
     '''
@@ -379,6 +378,60 @@ class XRDResult1D(XRDResult, PlotSection):
         },
     )
 
+    def generate_plots(self, archive: 'EntryArchive', logger: 'BoundLogger'):
+        '''
+        Plot the 1D diffractogram.
+
+        Args:
+            archive (EntryArchive): The archive containing the section that is being
+            normalized.
+            logger (BoundLogger): A structlog logger.
+
+        Returns:
+            (dict, dict): line_linear, line_log
+        '''
+        plots = []
+
+        x = self.two_theta.to('degree').magnitude
+        y = self.intensity.magnitude
+
+        fig_line_linear = px.line(
+            x = x,
+            y = y,
+            labels = {
+                'x': '2θ (°)',
+                'y': 'Intensity',
+            },
+            title = 'Intensity (linear scale)',
+        )
+        plots.append(
+            PlotlyFigure(
+                label = 'Intensity vs 2Theta (Linear)',
+                index = 1,
+                figure = fig_line_linear.to_plotly_json(),
+            )
+        )
+
+        fig_line_log = px.line(
+            x = x,
+            y = y,
+            log_y = True,
+            labels = {
+                'x': '2θ (°)',
+                'y': 'Intensity',
+            },
+            title = 'Intensity (log scale)',
+        )
+        plots.append(
+            PlotlyFigure(
+                label = 'Intensity vs 2Theta (Log)',
+                index = 0,
+                figure = fig_line_log.to_plotly_json(),
+            )
+        )
+
+        return plots
+
     def normalize(self, archive: 'EntryArchive', logger: 'BoundLogger'):
         '''
         The normalize function of the `XRDResult` section.
@@ -396,24 +449,7 @@ def normalize(self, archive: 'EntryArchive', logger: 'BoundLogger'):
                 q=self.q_vector,
             )
 
-        json_line_linear, json_line_log = plotting.plot_1d(
-            self.two_theta,
-            self.intensity,
-        )
-        self.figures = [
-            PlotlyFigure(
-                label = 'Log Plot',
-                index = 1,
-                figure = json_line_log,
-            ),
-            PlotlyFigure(
-                label = 'Linear Plot',
-                index = 2,
-                figure = json_line_linear,
-            ),
-        ]
-
-class XRDResultRSM(XRDResult, PlotSection):
+class XRDResultRSM(XRDResult):
     '''
     Section containing the result of a Reciprocal Space Map (RSM) scan.
     '''
@@ -437,7 +473,117 @@ class XRDResultRSM(XRDResult, PlotSection):
         description='The count at each position, dimensionless',
     )
 
-    def normalize(self, archive: 'EntryArchive', logger: BoundLogger):
+    def generate_plots(self, archive: 'EntryArchive', logger: 'BoundLogger'):
+        '''
+        Plot the 2D RSM diffractogram.
+
+        Args:
+            archive (EntryArchive): The archive containing the section that is being
+            normalized.
+            logger (BoundLogger): A structlog logger.
+
+        Returns:
+            (dict, dict): json_2theta_omega, json_q_vector
+        '''
+        plots = []
+
+        # Plot for 2theta-omega RSM
+        x = self.omega.to('degree').magnitude
+        y = self.two_theta.to('degree').magnitude
+        z = self.intensity.magnitude
+        log_z = np.log10(z)
+        x_range, y_range = get_bounding_range_2d(x, y)
+
+        fig_2theta_omega = px.imshow(
+            img = np.around(log_z,3).T,
+            x = np.around(x,3),
+            y = np.around(y,3),
+            color_continuous_scale = 'inferno',
+        )
+        fig_2theta_omega.update_layout(
+            title = 'RSM plot: Intensity (log-scale) vs Axis position',
+            xaxis_title = 'ω (°)',
+            yaxis_title = '2θ (°)',
+            xaxis = dict(
+                autorange = False,
+                fixedrange = False,
+                range = x_range,
+            ),
+            yaxis = dict(
+                autorange = False,
+                fixedrange = False,
+                range = y_range,
+            ),
+            width = 600,
+            height = 600,
+        )
+        plots.append(
+            PlotlyFigure(
+                label = 'RSM 2Theta-Omega',
+                index = 1,
+                figure = fig_2theta_omega.to_plotly_json(),
+            ),
+        )
+
+        # Plot for RSM in Q-vectors
+        print(self.q_parallel)
+        print(self.q_perpendicular)
+        print("-here----------------- ")
+
+        if self.q_parallel is not None and self.q_perpendicular is not None:
+            print("-----------------here- ")
+            x = self.q_parallel.to('1/angstrom').magnitude.flatten()
+            y = self.q_perpendicular.to('1/angstrom').magnitude.flatten()
+            # q_vectors lead to irregular grid
+            # generate a regular grid using interpolation
+            x_regular = np.linspace(x.min(),x.max(),z.shape[0])
+            y_regular = np.linspace(y.min(),y.max(),z.shape[1])
+            x_grid, y_grid = np.meshgrid(x_regular,y_regular)
+            z_interpolated = griddata(
+                points = (x,y),
+                values = z.flatten(),
+                xi = (x_grid,y_grid),
+                method = 'linear',
+                fill_value = z.min(),
+            )
+            log_z_interpolated = np.log10(z_interpolated)
+            x_range, y_range = get_bounding_range_2d(x_regular,y_regular)
+
+            fig_q_vector = px.imshow(
+                img = np.around(log_z_interpolated,3),
+                x = np.around(x_regular,3),
+                y = np.around(y_regular,3),
+                color_continuous_scale = 'inferno',
+                range_color = [np.nanmin(log_z[log_z != -np.inf]), log_z_interpolated.max()],
+            )
+            fig_q_vector.update_layout(
+                title = 'RSM plot: Intensity (log-scale) vs Q-vectors',
+                xaxis_title = 'Q_parallel (1/Å)',
+                yaxis_title = 'Q_perpendicular (1/Å)',
+                xaxis = dict(
+                    autorange = False,
+                    fixedrange = False,
+                    range = x_range,
+                ),
+                yaxis = dict(
+                    autorange = False,
+                    fixedrange = False,
+                    range = y_range,
+                ),
+                width = 600,
+                height = 600,
+            )
+            plots.append(
+                PlotlyFigure(
+                    label = 'RSM Q-Vectors',
+                    index = 0,
+                    figure = fig_q_vector.to_plotly_json(),
+                ),
+            )
+        
+        return plots
+
+    def normalize(self, archive: 'EntryArchive', logger: 'BoundLogger'):
         super().normalize(archive, logger)
         var_axis = 'omega'
         if self.source_peak_wavelength is not None:
@@ -451,29 +597,6 @@ def normalize(self, archive: 'EntryArchive', logger: BoundLogger):
                     )
                     break
 
-        json_2theta_omega, json_q_vector = plotting.plot_2d_rsm(
-            self.two_theta,
-            self[var_axis],
-            self.q_parallel,
-            self.q_perpendicular,
-            self.intensity,
-        )
-        self.figures = [
-            PlotlyFigure(
-                label = 'RSM (2Theta-Omega)',
-                index = 2,
-                figure = json_2theta_omega,
-            ),
-        ]
-        if json_2theta_omega:
-            self.figures.append(
-                PlotlyFigure(
-                    label = 'RSM (Q-vectors)',
-                    index = 1,
-                    figure = json_q_vector,
-                ),
-            )
-
 class XRayDiffraction(Measurement):
     '''
     Generic X-ray diffraction measurement.
@@ -557,7 +680,7 @@ def normalize(self, archive: 'EntryArchive', logger: 'BoundLogger'):
             )
 
 
-class ELNXRayDiffraction(XRayDiffraction, EntryData):
+class ELNXRayDiffraction(XRayDiffraction, EntryData, PlotSection):
     '''
     Example section for how XRayDiffraction can be implemented with a general reader for
     common XRD file types.
@@ -811,6 +934,7 @@ def normalize(self, archive: 'EntryArchive', logger: 'BoundLogger'):
                     xrd_dict = read_function(file.name, logger)
                 write_function(xrd_dict, archive, logger)
         super().normalize(archive, logger)
+        self.figures = self.results[0].generate_plots(archive, logger)
 
         if not self.results:
             return