Black the code with line length of 100

Change-Id: I5c0885459d8996bd22c7c698120052e13c872310

doc/source/conf.py

@@ -146,16 +146,12 @@ def maybe_skip_member(app, what, name, obj, skip, options):
         try:
             package, module, *path = name.split(".")
             root_package = IMPORT_MAPPING[package]
-            actual_module = importlib.import_module(
-                root_package.__name__ + "." + module
-            )
+            actual_module = importlib.import_module(root_package.__name__ + "." + module)
             task = getattr(actual_module, path[-2])
             actual_obj = getattr(task, path[-1])
             if isinstance(actual_obj, luigi.Parameter):
                 if hasattr(actual_obj, "description") and actual_obj.description:
-                    help_str, param_type, choices, interval, optional = _process_param(
-                        actual_obj
-                    )
+                    help_str, param_type, choices, interval, optional = _process_param(actual_obj)
                     if optional:
                         help_str = "(optional) " + help_str
                     if param_type is not None:

src/morphval/cli.py

@@ -25,9 +25,7 @@ def get_parser():
         required=True,
         help="full path to directory for the validation results",
     )
-    parser.add_argument(
-        "-c", "--config", required=True, help="full path to yaml config file"
-    )
+    parser.add_argument("-c", "--config", required=True, help="full path to yaml config file")
     parser.add_argument(
         "--example-config",
         action="store_true",

src/morphval/common.py

@@ -111,9 +111,7 @@ def get_agg_fig():
 
 def center_population(population):
     """Return a new population where all cells have been translated to their soma origins."""
-    morphs = [
-        geom.transform.translate(n, -np.asarray(n.soma.center)) for n in population
-    ]
+    morphs = [geom.transform.translate(n, -np.asarray(n.soma.center)) for n in population]
     return Population(morphs, name=population.name)
 
 
@@ -218,18 +216,10 @@ def plot_normalized_neurons(
         test_comp_pop = get_components_population(test_population, comp)
         xlim, ylim = compute_bounding_box(ref_comp_pop, test_comp_pop)
 
-        desc = progress_bar_label(
-            "Reference {}", pretty_name(comp_dict[comp]), notebook_desc
-        )
-        ref_plot_paths[comp] = plot_population(
-            ref_output_dir, ref_comp_pop, xlim, ylim, desc
-        )
-        desc = progress_bar_label(
-            "Test {}", pretty_name(comp_dict[comp]), notebook_desc
-        )
-        test_plot_paths[comp] = plot_population(
-            test_output_dir, test_comp_pop, xlim, ylim, desc
-        )
+        desc = progress_bar_label("Reference {}", pretty_name(comp_dict[comp]), notebook_desc)
+        ref_plot_paths[comp] = plot_population(ref_output_dir, ref_comp_pop, xlim, ylim, desc)
+        desc = progress_bar_label("Test {}", pretty_name(comp_dict[comp]), notebook_desc)
+        test_plot_paths[comp] = plot_population(test_output_dir, test_comp_pop, xlim, ylim, desc)
 
     return ref_plot_paths, test_plot_paths
 

src/morphval/validation.py

@@ -11,9 +11,7 @@
 
 DICTDATA = dict.fromkeys(["name", "data_type", "data", "labels"])
 
-DICTALLDATA = dict.fromkeys(
-    ["datasets", "description", "charts", "version", "result", "type"]
-)
+DICTALLDATA = dict.fromkeys(["datasets", "description", "charts", "version", "result", "type"])
 
 DESCR = (
     "Morphology validation against reference morphologies. "
@@ -39,9 +37,7 @@ def extract_hist(data, bins=20):
     """
     bin_data, edges = np.histogram(data, bins, normed=True)
 
-    edges_centers = [
-        float(Decimal("%.2f" % e)) for e in list((edges[1:] + edges[:-1]) / 2)
-    ]
+    edges_centers = [float(Decimal("%.2f" % e)) for e in list((edges[1:] + edges[:-1]) / 2)]
 
     return list(bin_data), list(edges_centers)
 
@@ -107,13 +103,9 @@ def write_all(validation_data, reference_data, component, feature, name, config)
         config=config, name=name, component=component, feature=feature
     )
 
-    valid = write_hist(
-        data=validation_data, feature=feature, name=name + "-test", bins=bins
-    )
+    valid = write_hist(data=validation_data, feature=feature, name=name + "-test", bins=bins)
 
-    refer = write_hist(
-        data=reference_data, feature=feature, name=name + "-reference", bins=bins
-    )
+    refer = write_hist(data=reference_data, feature=feature, name=name + "-reference", bins=bins)
 
     results, status = stat_test(
         validation_data, reference_data, test=test, fargs=thresh, val_crit=val_crit

src/morphval/validation_main.py

@@ -18,9 +18,7 @@
 
 
 _distribution = pkg_resources.get_distribution("synthesis-workflow")
-TEMPLATES = (
-    Path(_distribution.get_resource_filename("morphval", "morphval")) / "templates"
-)
+TEMPLATES = Path(_distribution.get_resource_filename("morphval", "morphval")) / "templates"
 TEMPLATE_FILE = (TEMPLATES / "report_template.jinja2").as_posix()
 SUMMARY_TEMPLATE_FILE = (TEMPLATES / "report_summary_template.jinja2").as_posix()
 
@@ -48,9 +46,7 @@ def count_passing_validations(features):
     Returns:
         returns tuple(feature_pass, features_total)
     """
-    num_pass = sum(
-        v["validation_criterion"]["status"] == "PASS" for v in features.values()
-    )
+    num_pass = sum(v["validation_criterion"]["status"] == "PASS" for v in features.values())
     return num_pass, len(features)
 
 
@@ -91,9 +87,7 @@ def do_validation(validation_config, ref_population, test_population):
         results[component_name] = component_results = collections.OrderedDict()
         morphometrics[component_name] = component_metrics = {}
         for feature_name, feature_config in features.items():
-            component_results[
-                feature_name
-            ] = feature_results = collections.OrderedDict()
+            component_results[feature_name] = feature_results = collections.OrderedDict()
 
             test_data, ref_data = validation.extract_feature(
                 test_population, ref_population, component_name, feature_name
@@ -104,18 +98,12 @@ def do_validation(validation_config, ref_population, test_population):
                 "ref": ref_data,
             }
 
-            feature_results["test_summary_statistics"] = compute_summary_statistics(
-                test_data
-            )
-            feature_results["ref_summary_statistics"] = compute_summary_statistics(
-                ref_data
-            )
+            feature_results["test_summary_statistics"] = compute_summary_statistics(test_data)
+            feature_results["ref_summary_statistics"] = compute_summary_statistics(ref_data)
 
             test_name = feature_config["stat_test"]
 
-            feature_results[
-                "statistical_tests"
-            ] = test_results = compute_statistical_tests(
+            feature_results["statistical_tests"] = test_results = compute_statistical_tests(
                 test_data,
                 ref_data,
                 feature_config["stat_test"],
@@ -134,19 +122,13 @@ def write_morphometrics(output_dir, morphometrics):
     for component_name, features in morphometrics.items():
         for feature_name, feature_metrics in features.items():
             for kind in ("test", "ref"):
-                dir_name = os.path.join(
-                    output_dir, component_name, "morphometrics", kind
-                )
+                dir_name = os.path.join(output_dir, component_name, "morphometrics", kind)
                 save_csv(dir_name, feature_name, feature_metrics[kind])
 
 
-def create_morphometrics_histograms(
-    output_dir, morphometrics, config, notebook_desc=None
-):
+def create_morphometrics_histograms(output_dir, morphometrics, config, notebook_desc=None):
     """Create histograms based on morphometrics."""
-    m_items = common.add_progress_bar(
-        morphometrics.items(), "[{}] Histograms", notebook_desc
-    )
+    m_items = common.add_progress_bar(morphometrics.items(), "[{}] Histograms", notebook_desc)
     for component_name, features in m_items:
         figure_dir = os.path.join(output_dir, component_name, "figures")
 
@@ -279,9 +261,7 @@ def validate_features(self, cell_figure_count=100, nb_jobs=-1, joblib_verbose=0)
         """Validate all features."""
         self.results = results = collections.OrderedDict()
 
-        batch_size = 1 + int(
-            len(self.config) / (nb_jobs if nb_jobs > 0 else cpu_count())
-        )
+        batch_size = 1 + int(len(self.config) / (nb_jobs if nb_jobs > 0 else cpu_count()))
 
         for res_mtype, res, ref_p, test_p in Parallel(
             nb_jobs,
@@ -293,12 +273,8 @@ def validate_features(self, cell_figure_count=100, nb_jobs=-1, joblib_verbose=0)
                 mtype,
                 config,
                 self.output_dir / mtype,
-                self.ref_files.loc[
-                    self.ref_files["mtype"] == mtype, "filepath"
-                ].tolist(),
-                self.test_files.loc[
-                    self.test_files["mtype"] == mtype, "filepath"
-                ].tolist(),
+                self.ref_files.loc[self.ref_files["mtype"] == mtype, "filepath"].tolist(),
+                self.test_files.loc[self.test_files["mtype"] == mtype, "filepath"].tolist(),
                 cell_figure_count,
                 False,
             )
@@ -308,9 +284,7 @@ def validate_features(self, cell_figure_count=100, nb_jobs=-1, joblib_verbose=0)
             self.ref_plots[res_mtype] = ref_p
             self.test_plots[res_mtype] = test_p
 
-        self.results_file = common.dump2json(
-            self.output_dir, "validation_results", results
-        )
+        self.results_file = common.dump2json(self.output_dir, "validation_results", results)
         return self.results_file
 
     def generate_report_data(self, mtype):
@@ -349,16 +323,12 @@ def generate_report_data(self, mtype):
 
         tt["num_pass"] = total_num_pass
         tt["num_features"] = total_num_features
-        tt["pass_percentage"] = "{:5.2f}".format(
-            (100.0 * total_num_pass) / total_num_features
-        )
+        tt["pass_percentage"] = "{:5.2f}".format((100.0 * total_num_pass) / total_num_features)
 
         return tt
 
     @staticmethod
-    def merge_results_features(
-        mtype, component, feature_name, feature_config, feature_results
-    ):
+    def merge_results_features(mtype, component, feature_name, feature_config, feature_results):
         """Merge result features."""
         stat_test = feature_config["stat_test"]
         stat_test_results = feature_results["statistical_tests"][stat_test]["results"]
@@ -393,9 +363,7 @@ def merge_results_features(
 
         return ret
 
-    def write_report(
-        self, validation_report=True, template_file=TEMPLATE_FILE, prefix="report-"
-    ):
+    def write_report(self, validation_report=True, template_file=TEMPLATE_FILE, prefix="report-"):
         """For each mtype in the results, write out its report.
 
         Args:
@@ -410,9 +378,7 @@ def write_report(
 
         output_files = []
         for mtype in self.results:
-            output_text = self.render_mtype_report(
-                template_file, mtype, validation_report
-            )
+            output_text = self.render_mtype_report(template_file, mtype, validation_report)
             output_files.append(os.path.join(report_dir, prefix + mtype + ".html"))
             with open(output_files[-1], "w") as outputFile:
                 outputFile.write(output_text)
@@ -436,9 +402,7 @@ def render_mtype_report(self, template_file, mtype, validation_report):
         template = load_template(template_file)
         templateText = self.generate_report_data(mtype)
 
-        config_file = common.dump2json(
-            self.output_dir, "validation_config", self.config
-        )
+        config_file = common.dump2json(self.output_dir, "validation_config", self.config)
 
         templateVars = {
             "output_title": "Validation report: " + mtype,

src/synthesis_workflow/circuit.py

@@ -42,9 +42,7 @@ def halve_atlas(annotated_volume, axis=0, side=LEFT):
     for coord in range(3):
         if axis == coord:
             slices_[coord] = (
-                slice(0, middle)
-                if side == RIGHT
-                else slice(middle, annotated_volume.shape[axis])
+                slice(0, middle) if side == RIGHT else slice(middle, annotated_volume.shape[axis])
             )
         else:
             slices_[coord] = slice(0, annotated_volume.shape[coord])
@@ -72,9 +70,7 @@ def create_atlas_thickness_mask(atlas_dir):
     for i, max_thickness in enumerate(max_thicknesses, 1):
         ph = atlas.load_data(f"[PH]{i}", memcache=True)
         with np.errstate(invalid="ignore"):
-            invalid_thickness = (ph.raw[..., 1] - ph.raw[..., 0]) > (
-                max_thickness + tolerance
-            )
+            invalid_thickness = (ph.raw[..., 1] - ph.raw[..., 0]) > (max_thickness + tolerance)
         too_thick = np.logical_or(too_thick, invalid_thickness)
 
         L.info(
@@ -88,9 +84,7 @@ def create_atlas_thickness_mask(atlas_dir):
         np.round(100 * too_thick[isocortex_mask].mean(), 3),
     )
 
-    return brain_regions.with_data(
-        np.logical_and(~too_thick, isocortex_mask).astype(np.uint8)
-    )
+    return brain_regions.with_data(np.logical_and(~too_thick, isocortex_mask).astype(np.uint8))
 
 
 def build_circuit(
@@ -167,9 +161,7 @@ def circuit_slicer(cells, n_cells, mtypes=None, planes=None, hemisphere=None):
         # between each pair of planes, select n_cells
         return pd.concat(
             [
-                slice_n_cells(
-                    get_cells_between_planes(cells, plane_left, plane_right), n_cells
-                )
+                slice_n_cells(get_cells_between_planes(cells, plane_left, plane_right), n_cells)
                 for plane_left, plane_right in tqdm(
                     zip(planes[:-1:3], planes[2::3]), total=int(len(planes) / 3)
                 )
@@ -240,9 +232,7 @@ def create_planes(
             _n_points,
         )
     else:
-        raise Exception(
-            f"Please set plane_type to 'aligned' or 'centerline', not {plane_type}."
-        )
+        raise Exception(f"Please set plane_type to 'aligned' or 'centerline', not {plane_type}.")
 
     # create all planes to match slice_thickness between every two planes
     centerline_len = np.linalg.norm(np.diff(centerline, axis=0), axis=1).sum()

src/synthesis_workflow/fit_utils.py

@@ -66,12 +66,8 @@ def clean_outliers(
 
     # Detect outliers
     errs = np.array([np.abs(p(ix) - y[i]) for i, ix in enumerate(x)])
-    x_clean = np.delete(
-        x, [np.where(errs > np.percentile(np.sort(errs), outlier_percentage))][0]
-    )
-    y_clean = np.delete(
-        y, [np.where(errs > np.percentile(np.sort(errs), outlier_percentage))][0]
-    )
+    x_clean = np.delete(x, [np.where(errs > np.percentile(np.sort(errs), outlier_percentage))][0])
+    y_clean = np.delete(y, [np.where(errs > np.percentile(np.sort(errs), outlier_percentage))][0])
 
     return x_clean, y_clean
 
@@ -106,9 +102,7 @@ def fit_path_distance_to_extent(
     return popt[0], 0
 
 
-def get_path_distance_from_extent(
-    slope: float, intercept: float, extent: float
-) -> float:
+def get_path_distance_from_extent(slope: float, intercept: float, extent: float) -> float:
     """Returns a path distance for an input extent according to fitted function.
 
     The function is given by the equation: