 Here is a simplified Python code snippet that uses the pydpf-core library to calculate the average elemental stress and plot the results. Please note that this is a basic example and might need adjustments based on your specific use case.

```python
from pydpf_core import *
import numpy as np
import matplotlib.pyplot as plt

# Load the model
model = Model("result_file.dat")

# Get all node IDs in the model
nodes = model.get_nodes()
node_ids = [node.id for node in nodes]

# Find the minimum amount of surrounding elements to get a minimum volume
min_elements = 6  # Adjust this value based on your needs
min_volume_nodes = [node_ids[i:i+min_elements] for i in range(0, len(node_ids)-min_elements+1) if len(set(model.model_elements(node_ids[i:i+min_elements])).nodes) == min_elements]

# Read the volume by element and find the minimum list of elements by node to get the volume check
volumes = {}
for node_group in min_volume_nodes:
    elements = model.model_elements(node_group)
    volume = np.sum([element.volume for element in elements])
    volumes[node_group] = volume

# Create a workflow to compute equivalent stress averaged on elements
workflow = Workflow("stress_workflow")
seqv = workflow.add_sequence("seqv")

# Add inputs and outputs for elemental volume and stress
InputsElementsVolume(seqv, "elements_volume")
InputsElementalVolume(seqv, "elemental_stress")
OutputsElementsVolume(seqv, "elements_volume_out")
OutputsElementalVolume(seqv, "elemental_stress_out")

# Add scoping for elemental stress
scopingA = seqv.add_scoping("scopingA")
scopingA.add_field("elemental_stress", "a")
scopingA.set_should_average(True)

# Add mesh and value for elemental stress
meshA = scopingA.add_mesh("meshA")
meshA.set_elements(seqv.inputs.elements_volume.elements)
valueA = scopingA.add_value("valueA")
valueA.set_expression("a = sqrt(deviatoric_stress(seqv.inputs.elemental_stress))")

# Add outputs for cyclic volume and volume fraction
OutputsCyclicVolume(seqv, "cyclic_volume")
OutputsVolumeFraction(seqv, "volume_fraction")

# Add inputs for cyclic volume
InputsCyclicVolume(seqv, "cyclic_volume_in")
InputsVolumeFraction(seqv, "volume_fraction_in")

# Add sequence to calculate volume fraction
seqv_vol_frac = workflow.add_sequence("seqv_vol_frac")
seqv_vol_frac.add_scoping("scopingB")
seqv_vol_frac.scopingB.add_field("volume_fraction", "f")
seqv_vol_frac.scopingB.set_expression("f = seqv.inputs.cyclic_volume_in.value / seqv.inputs.elements_volume.value")

# Add sequence to calculate sum of stresses
seqv_sum_stress = workflow.add_sequence("seqv_sum_stress")
seqv_sum_stress.add_scoping("scopingC")
seqv_sum_stress.scopingC.add_field("sum_stress", "s")
seqv_sum_stress.scopingC.set_expression("s = dot(seqv.inputs.elements_volume_out.value, seqv.outputs.elemental_stress_out.value)")

# Add sequence to calculate average stress
seqv_avg_stress = workflow.add_sequence("seqv_avg_stress")
seqv_avg_stress.add_scoping("scopingD")
seqv_avg_stress.scopingD.add_field("avg_stress", "avg")
seqv_avg_stress.scopingD.set_expression("avg = s / seqv.inputs.elements_volume_out.value.sum()")

# Run the workflow
workflow.run()

# Extract the results
avg_stress = workflow.outputs.seqv_avg_stress.outputs.avg.value
volumes_avg_stress = {node_group: avg_stress[i]/volume for i, node_group in enumerate(min_volume_nodes)}

# Plot the results
plt.plot(np.array([volume for node_group, volume in volumes_avg_stress.items()]), np.array([value for node_group, value in volumes_avg_stress.items()]))
plt.xlabel("Volume")
plt.ylabel("Average Equivalent Elemental Stress")
plt.show()
```

This code creates a workflow to calculate the average elemental stress, runs it, and plots the results. The `min_volume_nodes` list contains the groups of nodes with the minimum number of surrounding elements, and `volumes_avg_stress` is a dictionary containing the average equivalent elemental stress for each of these groups. The plot shows the relationship between the volume and the average equivalent elemental stress.