diff --git a/Fatigue_Life/Visuize/read_node.py b/Fatigue_Life/Visuize/read_node.py
new file mode 100644
index 0000000000000000000000000000000000000000..bb48dc09f3a19bf6c971b9bb2a429a75ae7f99d3
--- /dev/null
+++ b/Fatigue_Life/Visuize/read_node.py
@@ -0,0 +1,204 @@
+import csv
+import os
+
+def read_dat_file(dat_file_path):
+    nodes = {}       # node_id -> (x,y,z)
+    elements = []    # list of node_id lists for each element
+
+    in_nodes = False
+    in_elements = False
+
+    with open(dat_file_path, "r") as file:
+        lines = file.readlines()
+
+    for line in lines:
+        line = line.strip()
+
+        # Detect node block
+        if line.lower().startswith("nblock"):
+            in_nodes = True
+            in_elements = False
+            continue
+        if line == "-1":
+            if in_nodes:
+                in_nodes = False
+            elif in_elements:
+                in_elements = False
+            continue
+
+        # Detect element block
+        if line.lower().startswith("eblock"):
+            in_elements = True
+            in_nodes = False
+            continue
+
+        # Parse nodes
+        if in_nodes:
+            parts = line.split()
+            if len(parts) >= 4:
+                try:
+                    node_id = int(parts[0])
+                    x = float(parts[1])
+                    y = float(parts[2])
+                    z = float(parts[3])
+                    nodes[node_id] = (x, y, z)
+                except Exception:
+                    pass  # ignore malformed lines
+
+        # Parse elements (assuming EBLOCK contains element lines)
+        if in_elements:
+            parts = line.split()
+            if len(parts) >= 15:
+                # Extract the 4 node IDs from the standard positions
+                # Usually nodes start around index 10 or 11 — adjust if needed
+                try:
+                    # For tetrahedral elements, pick 4 node IDs.
+                    # You need to confirm the exact positions for your .dat file.
+                    node_ids = [int(parts[11]), int(parts[12]), int(parts[13]), int(parts[15])]
+                    elements.append(node_ids)
+                except Exception:
+                    pass  # ignore malformed lines
+
+    # Sort node IDs and create a mapping from node_id to zero-based index
+    sorted_node_ids = sorted(nodes.keys())
+    id_to_index = {nid: i for i, nid in enumerate(sorted_node_ids)}
+
+    # Build positions array ordered by zero-based index
+    positions = [nodes[nid] for nid in sorted_node_ids]
+
+    # Convert element connectivity node IDs to zero-based indices
+    connectivity = []
+    for elem_node_ids in elements:
+        try:
+            zero_based = [id_to_index[nid] for nid in elem_node_ids]
+            connectivity.append(zero_based)
+        except KeyError:
+            # Skip elements with invalid node IDs
+            continue
+
+    return positions, connectivity
+
+"""
+def read_dat_file(dat_file_path):
+    in_nodes = False
+    in_elements = False
+    nodes = []
+    cells_detail = []
+
+    with open(dat_file_path, "r") as file:
+        lines = file.readlines()
+
+    lines_iter = iter(lines)
+
+    for line in lines_iter:
+
+        line = line.strip()
+
+        # Detect node block
+        if line.lower().startswith("nblock"):
+            in_nodes = True
+            continue
+
+        if in_nodes and line.strip() == "-1":
+            in_nodes = False
+            continue
+
+        # Detect element block (EBLOCK)
+        if line.lower().startswith("eblock"):
+            in_elements = True
+            continue
+
+        if in_elements and line.strip() == "-1":
+            in_elements = False
+            continue
+
+        # Parse nodes
+        if in_nodes:
+            parts = line.split()
+            if len(parts) == 4:
+                #node_id = int(parts[0])
+                x = float(parts[1])
+                y = float(parts[2])
+                z = float(parts[3])
+                nodes.append(( x, y, z))
+
+        # Parse elements (EBLOCK, 2-line format)
+        if in_elements:
+            parts = line.split()
+            num_nodes =8
+            if len(parts) > 14:
+                 # Ensure the line has 4 parts: ID, X, Y, Z
+                num_nodes = int(parts[8])
+                less = 0
+                if num_nodes < 8:
+                    less = 8-num_nodes
+                node_idsz = []
+                # print(parts)
+                element_id = [int(parts[10])]  # Element ID
+                body_id = [int(parts[0])]
+                for i in range(11, 19-less):
+                    # print(i)
+                    node_idsz.append(int(parts[i]))   # Node IDs
+                if num_nodes<=8:
+                    cells_detail.append(element_id+body_id+node_idsz)
+            if len(parts) == num_nodes-8 and num_nodes>8:  # Ensure the line has 4 parts: ID, X, Y, Z    
+                for i in range(0,num_nodes-8 ):
+                    node_idsz.append(int(parts[i])) 
+            #next_line = next(lines_iter).strip()   # this is only required if the next line contains more node ids in case of hexhedral elements
+            #node_ids += [int(x) for x in next_line.split()]
+            
+                # print(element_id, node_idsz)
+                cells_detail.append(element_id+body_id+node_idsz) 
+
+
+
+    # Sort nodes and cells
+    nodes.sort(key=lambda x: x[0])
+    cells_detail.sort(key=lambda x: x[0])
+
+    # Remove duplicates
+    cells_detail = [list(item) for item in dict.fromkeys(tuple(cell) for cell in cells_detail)]
+
+    # Extract 4-node face from each cell (can adjust as needed)
+    cells = [[cell[2], cell[3], cell[4], cell[6]] for cell in cells_detail]
+
+    return nodes, cells
+"""
+def read_result_file(result_file_path, encoding='utf-8'):
+    parameters = []
+    with open(result_file_path, mode='r', encoding=encoding) as file:
+        if result_file_path.endswith(".csv"):
+            reader = csv.reader(file)
+            next(reader)  # Skip header
+            for row in reader:
+                parameters.append(float(row[-1]))
+        elif result_file_path.endswith(".txt"):
+            for line in file:
+                if "Node Number" in line:
+                    continue
+                columns = line.split()
+                try:
+                    parameters.append(float(columns[-1]))
+                except ValueError:
+                    continue
+    return parameters
+
+def main(folder_path):
+    folder_base_name = os.path.basename(folder_path).replace("_data", "")
+    dat_file_path = os.path.join(folder_path, f"{folder_base_name}.dat")
+    fatigue_life_path = os.path.join(folder_path, f"{folder_base_name}.txt")
+    
+    dat_file_path = "path/to/your/dat_file.dat"
+    fatigue_life_path = "path/to/your/fatigue_life.txt"
+
+    nodes = read_dat_file(dat_file_path)
+    life = read_result_file(fatigue_life_path)
+
+    # Do something with the data
+    print("Nodes:")
+    for node in nodes:
+        print(node)
+
+    print("\nLife:")
+    for param in life:
+        print(param)
diff --git a/Fatigue_Life/Visuize/visualize.py b/Fatigue_Life/Visuize/visualize.py
new file mode 100644
index 0000000000000000000000000000000000000000..ed3d3b40a6e7e07efecc5255dec9c1824ba5a344
--- /dev/null
+++ b/Fatigue_Life/Visuize/visualize.py
@@ -0,0 +1,65 @@
+from read_node import read_dat_file, read_result_file
+import os
+
+import numpy as np
+import pyvista as pv
+folder_path = r"D:\AnK\FatigueNet\Fatigue_Life\datasets\Raw data\shaft_high\life_D15_d5_r1"
+folder_base_name = os.path.basename(folder_path).replace("_data", "")
+dat_file_path = os.path.join(folder_path, f"{folder_base_name}.dat")
+fatigue_life_path = os.path.join(folder_path, f"{folder_base_name}.txt")
+
+#dat_file_path = "path/to/your/dat_file.dat"
+#fatigue_life_path = "path/to/your/fatigue_life.txt"
+
+positions,cells = read_dat_file(dat_file_path)
+fatigue_life = read_result_file(fatigue_life_path)
+#print(positions)
+#print(fatigue_life)
+
+# Step 3: Log scale for better contrast
+log_fatigue_life = np.log10(fatigue_life)
+
+# Step 4: Create point cloud
+point_cloud = pv.PolyData(positions)
+point_cloud["Fatigue Life (log10)"] = log_fatigue_life
+
+# Step 5: Alternative approach - create glyphs from points
+# This is often more reliable for point-based visualizations
+sphere_source = pv.Sphere(radius=0.15)
+glyphs = point_cloud.glyph(geom=sphere_source, scale=False)
+
+# Step 6: Plotting
+plotter = pv.Plotter()
+
+# Add spheres with color mapping
+plotter.add_mesh(
+    glyphs,
+    scalars="Fatigue Life (log10)",
+    cmap="viridis",
+    opacity=1.0,
+    show_edges=False
+)
+
+# Add scalar bar with better formatting
+plotter.add_scalar_bar(
+    title="log₁₀(Fatigue Life)",
+    n_labels=6,
+    fmt="%.1f"
+)
+
+# Set background color for better contrast
+plotter.set_background('white')
+
+# Set camera position for better view
+plotter.camera_position = 'iso'
+
+# Add axes for reference
+plotter.add_axes()
+
+# Show the plot
+plotter.show()
+
+# Print some debug info
+print(f"Created {len(positions)} spheres")
+print(f"Fatigue life range: {fatigue_life.min():.0e} to {fatigue_life.max():.0e}")
+print(f"Log fatigue life range: {log_fatigue_life.min():.2f} to {log_fatigue_life.max():.2f}")
\ No newline at end of file
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