fix typos ambiguous variable name

Author: janosh

.pre-commit-config.yaml

@@ -20,7 +20,6 @@ repos:
     rev: 4.0.1
     hooks:
       - id: flake8
-        args: [--max-line-length=125]
 
   - repo: https://github.com/pre-commit/pre-commit-hooks
     rev: v4.3.0

atomate/vasp/analysis/linear_response.py

@@ -253,29 +253,32 @@ def det_deriv(matrix, i, j):
     jacobians = [[] for i in range(m)]
 
     det = np.linalg.det(matrix)
-    for i in range(m):
-        for j in range(n):
-            mji = np.delete(np.delete(matrix, j, 0), i, 1)
-            minor = (-1) ** (i + j) * np.linalg.det(mji)
+    for idx in range(m):
+        for jdx in range(n):
+            mji = np.delete(np.delete(matrix, jdx, 0), idx, 1)
+            minor = (-1) ** (idx + jdx) * np.linalg.det(mji)
 
             j_matrix = np.zeros([m, n])
-            for k in range(m):
-                for l in range(n):
-                    det_p = det_deriv(matrix, k, l)
+            for kdx in range(m):
+                for ldx in range(n):
+                    det_p = det_deriv(matrix, kdx, ldx)
 
-                    if k == j or l == i:
+                    if kdx == jdx or ldx == idx:
                         minor_p = 0.0
                     else:
-                        kk, ll = k - 1 if k > j else k, l - 1 if l > i else l
-                        minor_p = (-1) ** (i + j) * det_deriv(mji, kk, ll)
+                        kk, ll = (
+                            kdx - 1 if kdx > jdx else kdx,
+                            ldx - 1 if ldx > idx else ldx,
+                        )
+                        minor_p = (-1) ** (idx + jdx) * det_deriv(mji, kk, ll)
 
-                    j_matrix[k, l] = (minor_p * det - minor * det_p) / det**2
+                    j_matrix[kdx, ldx] = (minor_p * det - minor * det_p) / det**2
 
-            jacobians[i].append(j_matrix)
+            jacobians[idx].append(j_matrix)
 
             j_vec = np.reshape(j_matrix, [m * n, 1])
             sigma_f = np.sum(np.dot(np.transpose(j_vec), np.dot(matrix_covar, j_vec)))
-            matrixinv_var[i, j] = sigma_f
+            matrixinv_var[idx, jdx] = sigma_f
 
     return matrixinv, matrixinv_var, jacobians
 

docs/_sources/running_workflows.rst.txt

@@ -139,7 +139,7 @@ In the same directory as the POSCAR, create a Python script named ``mgo_bandstru
     # create the Workflow
     wf = wf_bandstructure(struct)
 
-    # finally, instatiate the LaunchPad and add the workflow to it
+    # finally, instantiate the LaunchPad and add the workflow to it
     lpad = LaunchPad.auto_load() # loads this based on the FireWorks configuration
     lpad.add_wf(wf)
 
@@ -188,7 +188,7 @@ Simply add the following Python script (``bs-analysis.py``) to your folder, **ch
     # use the get_dos method of the database to get the pymatgen CompleteDOS for that task id
     uniform_bs_entry = atomate_db.collection.find_one({'task_label': 'nscf uniform', 'formula_pretty': 'MgO'})
     complete_dos = atomate_db.get_dos(uniform_bs_entry['task_id'])
-    # Instatiate a DosPlotter and plot the DOS.
+    # instantiate a DosPlotter and plot the DOS.
     # Comment out the get_plot and uncomment save_plot if you have no GUI frontend to plot to.
     dos_plotter = DosPlotter()
     dos_plotter.add_dos_dict(complete_dos.get_element_dos())
@@ -203,7 +203,7 @@ Simply add the following Python script (``bs-analysis.py``) to your folder, **ch
     # use the get_band_structure method of the database to get the pymatgen BandStructureSymmLine for that task id
     line_bs_entry = atomate_db.collection.find_one({'task_label': 'nscf line', 'formula_pretty': 'MgO'})
     bandstructure = atomate_db.get_band_structure(line_bs_entry['task_id'])
-    # Instatiate a bandstructure plotter and plot the bandstructure.
+    # instantiate a bandstructure plotter and plot the bandstructure.
     # You can uncomment out the get_plot if you have a GUI frontend to plot to.
     bs_plotter = BSPlotter(bandstructure)
     bs_plotter.get_plot()

docs_rst/changelog.rst

@@ -273,7 +273,7 @@ atomate Changelog
 **v0.4.5**
 
 * *extensive* code review, code cleanup, and improved code docs - with some minor name refactoring
-* new builders: dielectric, structureanalysis (currently gives dimensionality of structure)
+* new builders: dielectric, structure analysis (currently gives dimensionality of structure)
 * rewrite powerups as in-place with cleaner syntax
 * improved installation tutorial (B. Bocklund)
 * improve/fix/reorganize some unit tests
@@ -296,7 +296,7 @@ atomate Changelog
 * Add StdErrorHandler to handlers (A. Jain)
 * Auto-detect and remove line_mode parameter in MMVaspDB (A. Jain)
 * added unit tests
-* misc cleanup, refactoring, and doc udpates
+* misc cleanup, refactoring, and doc updates
 * misc bugfixes
 
 
@@ -351,7 +351,7 @@ atomate Changelog
 **v0.2**
 
 * BoltzTraP transport workflows (A. Jain)
-* major builder improvements (merge multiple collections, progressbar, config, more...)
+* major builder improvements (merge multiple collections, progress bar, config, more...)
 * use FrozenJobErrorHandler by default (A. Jain)
 * add basic configuration overrides for preset workflows (A. Jain)
 * misc improvements and bugfixes (A. Jain, K. Mathew)

docs_rst/creating_workflows.rst

@@ -223,9 +223,9 @@ In the above code example, we start by importing the classes and functions we'll
 
 Lines 41-51 is where we define the optimization Firework. First we check if a vasp_input_set_relax parameter was passed, if not we default to MPRelaxSet and update that set if the ``user_kpoints_settings`` parameter was passed. It's common to see a similar parameter for ``user_incar_settings``. On line 49 we create our list of Fireworks (``fws``) with the ``OptimizeFW`` that we imported. Take note that this is the only Firework we pass our structure to, which allows for more flexibility. More on this later.
 
-Lines 52-61 we do a similar thing with the ``MPStaticSet`` from pymatgen that we did for the ``MPRelaxSet``. Then in lines 63-71, we loop through each of the deformations passed (as a list of 2-dimensional lists describing deformation matricies) and instantiate ``TransmuterFW`` with that deformation as the ``transformation_params``. For each type of transformation you use (``DeformStructureTransformation``) here, you will need to look at what parameters that class takes and use the right keyword, which is ``deformation`` in this case. Another example is the ``SupercellTransformation`` takes a transformation parameter called ``scale``. Pay close attention that on line 69 we are adding the ``OptimizeFW`` (from ``fws[0]``) as the parent for all of these Fireworks so they can run in parallel.
+Lines 52-61 we do a similar thing with the ``MPStaticSet`` from pymatgen that we did for the ``MPRelaxSet``. Then in lines 63-71, we loop through each of the deformations passed (as a list of 2-dimensional lists describing deformation matrices) and instantiate ``TransmuterFW`` with that deformation as the ``transformation_params``. For each type of transformation you use (``DeformStructureTransformation``) here, you will need to look at what parameters that class takes and use the right keyword, which is ``deformation`` in this case. Another example is the ``SupercellTransformation`` takes a transformation parameter called ``scale``. Pay close attention that on line 69 we are adding the ``OptimizeFW`` (from ``fws[0]``) as the parent for all of these Fireworks so they can run in parallel.
 
-Next on lines 73-76 we taking a *Firetask* and wrapping it in a pure Firework object from FireWorks. This demonstrates the modularity and customizability that FireWorks allows, which favors composing existing objects over writing custom ones for each level of abstraction. We are passing the same sort of parameters to this Firetask that we have been passing, which allows you to correctly infer that Fireworks themselves propogate relevant parameters down to their Firetasks. Again, we are setting the parents of this analysis Firework to all of the Fireworks in our list except the first one (the ``OptimizeFW``). This ensure that the analysis does not run until *all* of our transformed structures have finished running.
+Next on lines 73-76 we taking a *Firetask* and wrapping it in a pure Firework object from FireWorks. This demonstrates the modularity and customizability that FireWorks allows, which favors composing existing objects over writing custom ones for each level of abstraction. We are passing the same sort of parameters to this Firetask that we have been passing, which allows you to correctly infer that Fireworks themselves propagate relevant parameters down to their Firetasks. Again, we are setting the parents of this analysis Firework to all of the Fireworks in our list except the first one (the ``OptimizeFW``). This ensure that the analysis does not run until *all* of our transformed structures have finished running.
 
 Finally we use a vanilla FireWorks ``Workflow`` object to pull in all our Fireworks, update the name of the Workflow and return the object. From here you can write a script similar to the :ref:`running workflows tutorial` and pass in the correct variables to get a workflow to add to the LaunchPad. In this workflow, pay attention to the ``vasp_cmd`` parameter and ``db_file`` parameters to get the correct behavior. The preset workers will default these to your FireWorker's environment variables, but you will have to handle that manually here. To use your environment variables, pass in ``'>>vasp_cmd<<'`` and ``'>>db_file<<'`` for each of these parameters, respectively. More on this behavior in the `env_chk`_ section.
 
@@ -254,7 +254,7 @@ Powerups (:py:mod:`atomate.vasp.powerups`) enable modifications to be made to wo
 
 Some useful powerups that affect the behavior of VASP are
 
-* ``add_modify_incar``: Update the INCAR of Fireworks specifed by (partially matched) name at runtime
+* ``add_modify_incar``: Update the INCAR of Fireworks specified by (partially matched) name at runtime
 * ``set_fworker``: specify certain FireWorkers for workflows. Useful for FireWorkers tuned for high-memory or high-precision jobs
 * ``modify_to_soc``: makes all of the VASP calculations that match the constraints take spin orbit coupling into account
 * ``remove_custodian``, ``use_custodian``, ``run_fake_vasp``: Choose to run VASP with or without custodian (or not at all, useful for debugging)
@@ -279,7 +279,7 @@ Workflows in atomate are powerful for getting science done quickly because they
 * Ensure more consistent and easier usage of INCAR parameters you use often, such as setting a high ``NEDOS`` INCAR parameter
 * Set FireWorkers up for low and high precision jobs, or normal and high-memory jobs on the same computing resource.
 
-To use ``env_chk``, you don't have to do anything explicity, just pass ``'>>db_file<<'``, ``'>>vasp_cmd<<'``, ``'>>incar_update<<'`` to any parameter that supports ``env_chk``.
+To use ``env_chk``, you don't have to do anything explicitly, just pass ``'>>db_file<<'``, ``'>>vasp_cmd<<'``, ``'>>incar_update<<'`` to any parameter that supports ``env_chk``.
 
 Currently supported ``env_chk`` variables are:
 

docs_rst/installation.rst

@@ -16,7 +16,7 @@ This guide will get you up and running in an environment for running high-throug
 
 Details about how atomate is designed can be found in the `atomate paper`_ and an overview of how these different pieces interact are in a `Slideshare presentation`_. Running and writing your own workflows are covered in later tutorials. For now, these topics will be covered in enough depth to get you set up and to help you know where to troubleshoot if you are having problems.
 
-It is assumed that you are comfortable with basic Linux shell commands and navigation. If not, `Linux Journey`_ and `Linux Command`_ breifly cover enough to get you started. It will also be helpful if you are familiar with Python, but it is not strictly required for installation.
+It is assumed that you are comfortable with basic Linux shell commands and navigation. If not, `Linux Journey`_ and `Linux Command`_ briefly cover enough to get you started. It will also be helpful if you are familiar with Python, but it is not strictly required for installation.
 
 Note that this installation tutorial is VASP-centric since almost all functionality currently in atomate pertains to VASP.
 
@@ -618,9 +618,9 @@ Q: I made a mistake using reservation mode, how do I cancel my job?
 
         lpad rerun_fws -i 1
 
-    where `-i 1` means to make perfom the operations on the FireWork at index 1. Run ``lpad -h`` to see all of the options.
+    where `-i 1` means to make perform the operations on the FireWork at index 1. Run ``lpad -h`` to see all of the options.
 
-The non-reservation mode for qlaunching requires a little less maintenance with certain tradeoffs, which are detailed in the FireWorks documentation.
+The non-reservation mode for ``qlaunch`` requires a little less maintenance with certain tradeoffs, which are detailed in the FireWorks documentation.
 
 Q: I honestly tried everything I can to solve my problem. I still need help!
 ----------------------------------------------------------------------------

docs_rst/running_workflows.rst

@@ -139,7 +139,7 @@ In the same directory as the POSCAR, create a Python script named ``mgo_bandstru
     # create the Workflow
     wf = wf_bandstructure(struct)
 
-    # finally, instatiate the LaunchPad and add the workflow to it
+    # finally, instantiate the LaunchPad and add the workflow to it
     lpad = LaunchPad.auto_load() # loads this based on the FireWorks configuration
     lpad.add_wf(wf)
 
@@ -188,7 +188,7 @@ Simply add the following Python script (``bs-analysis.py``) to your folder, **ch
     # use the get_dos method of the database to get the pymatgen CompleteDOS for that task id
     uniform_bs_entry = atomate_db.collection.find_one({'task_label': 'nscf uniform', 'formula_pretty': 'MgO'})
     complete_dos = atomate_db.get_dos(uniform_bs_entry['task_id'])
-    # Instatiate a DosPlotter and plot the DOS.
+    # instantiate a DosPlotter and plot the DOS.
     # Comment out the get_plot and uncomment save_plot if you have no GUI frontend to plot to.
     dos_plotter = DosPlotter()
     dos_plotter.add_dos_dict(complete_dos.get_element_dos())
@@ -203,7 +203,7 @@ Simply add the following Python script (``bs-analysis.py``) to your folder, **ch
     # use the get_band_structure method of the database to get the pymatgen BandStructureSymmLine for that task id
     line_bs_entry = atomate_db.collection.find_one({'task_label': 'nscf line', 'formula_pretty': 'MgO'})
     bandstructure = atomate_db.get_band_structure(line_bs_entry['task_id'])
-    # Instatiate a bandstructure plotter and plot the bandstructure.
+    # instantiate a bandstructure plotter and plot the bandstructure.
     # You can uncomment out the get_plot if you have a GUI frontend to plot to.
     bs_plotter = BSPlotter(bandstructure)
     bs_plotter.get_plot()

setup.cfg

@@ -24,3 +24,6 @@ profile = black
 
 [tool:pytest]
 addopts = --ignore=atomate/qchem/test_files
+
+[codespell]
+ignore-words-list = mater,nin