Merge pull request #47 from QuantumChemist/fix_unit_tests

More features, improving the unit tests and fixing related issues

autoplex/data/common/flows.py

@@ -8,6 +8,7 @@
     from emmet.core.math import Matrix3D
     from pymatgen.core import Structure
 
+
 from atomate2.forcefields.jobs import (
     ForceFieldRelaxMaker,
     ForceFieldStaticMaker,
@@ -139,9 +140,11 @@ def make(
                     **relax_kwargs,
                 )
                 jobs.append(static_conv_jobs)
+                plots = plot_force_distribution(
+                    cell_factor, static_conv_jobs.output, x_min, x_max, bin_width
+                )
+                jobs.append(plots)
 
-        plots = plot_force_distribution(cell_factor_sequence, x_min, x_max, bin_width)
-        jobs.append(plots)
         return Flow(jobs)  # , plots.output)
 
     @job
@@ -183,7 +186,7 @@ def static_run_and_convert(
                 }
             if self.static_energy_maker is None:
                 self.static_energy_maker = GAPRelaxMaker(
-                    potential_param_file_name=potential_filename,  # task_document_kwargs={'dir_name': os.getcwd()},
+                    potential_param_file_name=potential_filename,
                     relax_cell=False,
                     relax_kwargs=relax_kwargs,
                     steps=1,
@@ -201,4 +204,4 @@ def static_run_and_convert(
             )
             jobs.append(conv_job)
 
-        return Response(replace=Flow(jobs))
+        return Response(replace=Flow(jobs), output=conv_job.output)

autoplex/data/common/jobs.py

@@ -7,7 +7,9 @@
     from emmet.core.math import Matrix3D
     from pymatgen.core import Structure
 
+import os
 import pickle
+from pathlib import Path
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -37,8 +39,8 @@ def convert_to_extxyz(job_output, pkl_file, config_type, factor):
             string of factor to resize cell parameters.
 
     """
-    with open(pkl_file, "rb") as file:
-        traj_obj = pickle.load(file)  # job_output.dir_name +
+    with open(Path(job_output.dir_name) / Path(pkl_file), "rb") as file:
+        traj_obj = pickle.load(file)
     # ForceFieldTaskDocument.from_ase_compatible_result() has no attribute dir_name implemented
     data = to_ase_trajectory(traj_obj=traj_obj)
     data[-1].write("tmp.xyz")
@@ -55,10 +57,13 @@ def convert_to_extxyz(job_output, pkl_file, config_type, factor):
         i.pbc = True
     write("ref_" + factor + ".extxyz", file, append=True)
 
+    return os.getcwd()
+
 
 @job
 def plot_force_distribution(
-    cell_factor_sequence: list[float],
+    cell_factor: float,
+    path,
     x_min: int = 0,
     x_max: int = 5,
     bin_width: float = 0.125,
@@ -68,8 +73,8 @@ def plot_force_distribution(
 
     Parameters
     ----------
-    cell_factor_sequence: list[float]
-        list of factor to resize cell parameters.
+    cell_factor: float
+        factor to resize cell parameters.
     x_min: int
         minimum value for the plot x-axis.
     x_max: int
@@ -82,19 +87,21 @@ def plot_force_distribution(
     plt.ylabel("Count")
     bins = np.arange(x_min, x_max + bin_width, bin_width)
     plot_total = []
-    for cell_factor in cell_factor_sequence:
-        plot_data = []
-        with open("ref_" + str(cell_factor).replace(".", "") + ".extxyz") as file:
-            for line in file:
-                # Split the line into columns
-                columns = line.split()
-
-                # Check if the line has exactly 10 columns
-                if len(columns) == 10:
-                    # Extract the last three columns
-                    data = columns[-3:]
-                    norm_data = np.linalg.norm(data, axis=-1)
-                    plot_data.append(norm_data)
+
+    # TODO split data collection and plotting
+
+    plot_data = []
+    with open(path + "/ref_" + str(cell_factor).replace(".", "") + ".extxyz") as file:
+        for line in file:
+            # Split the line into columns
+            columns = line.split()
+
+            # Check if the line has exactly 10 columns
+            if len(columns) == 10:
+                # Extract the last three columns
+                data = columns[-3:]
+                norm_data = np.linalg.norm(data, axis=-1)
+                plot_data.append(norm_data)
 
         plt.hist(plot_data, bins=bins, edgecolor="black")
         plt.title(f"Data for factor {cell_factor}")