diff --git a/ctaplot/ana/ana.py b/ctaplot/ana/ana.py
index 5b12e3f..92eba78 100644
--- a/ctaplot/ana/ana.py
+++ b/ctaplot/ana/ana.py
@@ -374,7 +374,7 @@ def bias(true, reco):
     -------
     float
     """
-    if not len(true) == len(reco):
+    if len(true) != len(reco):
         raise ValueError("both arrays should have the same size")
     if len(true) == 0:
         return 0
@@ -517,11 +517,7 @@ def resolution_per_bin(x, y_true, y_reco,
                               )
                    )
 
-    if isinstance(res[0], u.Quantity):
-        res = u.Quantity(res)
-    else:
-        res = np.array(res)
-
+    res = u.Quantity(res) if isinstance(res[0], u.Quantity) else np.array(res)
     return x_bins, res
 
 
@@ -987,9 +983,8 @@ def logbin_mean(x_bin):
     """
     if not isinstance(x_bin, u.Quantity):
         return 10 ** ((np.log10(x_bin[:-1]) + np.log10(x_bin[1:])) / 2.)
-    else:
-        unit = x_bin.unit
-        return (10 ** ((np.log10(x_bin[:-1].to_value(unit)) + np.log10(x_bin[1:].to_value(unit))) / 2.)) * unit
+    unit = x_bin.unit
+    return (10 ** ((np.log10(x_bin[:-1].to_value(unit)) + np.log10(x_bin[1:].to_value(unit))) / 2.)) * unit
 
 
 @u.quantity_input(true_x=u.m, reco_x=u.m, true_y=u.m, reco_y=u.m)
@@ -1288,11 +1283,7 @@ def bias_per_bin(true, reco, x, relative_scaling_method=None, bins=10):
         mask = bin_index == ii
         b.append(relative_bias(true[mask], reco[mask], relative_scaling_method=relative_scaling_method))
 
-    if isinstance(b[0], u.Quantity):
-        b = u.Quantity(b)
-    else:
-        b = np.array(b)
-
+    b = u.Quantity(b) if isinstance(b[0], u.Quantity) else np.array(b)
     return x_bins, b
 
 
diff --git a/ctaplot/plots/plots.py b/ctaplot/plots/plots.py
index 48214c7..72fb6ad 100644
--- a/ctaplot/plots/plots.py
+++ b/ctaplot/plots/plots.py
@@ -315,8 +315,7 @@ def plot_multiplicity_hist(multiplicity, ax=None, outfile=None, quartils=False,
     xmin = multiplicity.min()
     xmax = multiplicity.max()
 
-    if 'label' not in kwargs:
-        kwargs['label'] = 'Telescope multiplicity'
+    kwargs.setdefault('label', 'Telescope multiplicity')
 
     n, bins, patches = ax.hist(multiplicity, bins=(xmax - xmin), range=(xmin, xmax), rwidth=0.7, align='left', **kwargs)
     ax.xaxis.set_major_locator(MaxNLocator(integer=True))
@@ -446,8 +445,7 @@ def plot_effective_area_cta_requirement(cta_site, ax=None, **kwargs):
     cta_req = ana.cta_requirement(cta_site)
     e_cta, ef_cta = cta_req.get_effective_area()
 
-    if not 'label' in kwargs:
-        kwargs['label'] = "CTA requirement {}".format(cta_site)
+    kwargs.setdefault('label', "CTA requirement {}".format(cta_site))
 
     with quantity_support():
         ax.plot(e_cta, ef_cta, **kwargs)
@@ -514,8 +512,7 @@ def plot_sensitivity_cta_requirement(cta_site, ax=None, **kwargs):
     cta_req = ana.cta_requirement(cta_site)
     e_cta, ef_cta = cta_req.get_sensitivity()
 
-    if not 'label' in kwargs:
-        kwargs['label'] = "CTA requirement {}".format(cta_site)
+    kwargs.setdefault('label', "CTA requirement {}".format(cta_site))
 
     with quantity_support():
         ax.plot(e_cta, ef_cta, **kwargs)
@@ -550,8 +547,7 @@ def plot_sensitivity_cta_performance(cta_site, ax=None, **kwargs):
     e_cta, ef_cta = cta_perf.get_sensitivity()
     e_bin = cta_perf.energy_bins
 
-    if not 'label' in kwargs:
-        kwargs['label'] = "CTA performance {}".format(cta_site)
+    kwargs.setdefault('label', "CTA performance {}".format(cta_site))
 
     with quantity_support():
         ax.errorbar(e_cta, ef_cta, xerr=u.Quantity([e_cta - e_bin[:-1], e_bin[1:] - e_cta]), **kwargs)
@@ -722,8 +718,7 @@ def plot_angular_resolution_cta_requirement(cta_site, ax=None, **kwargs):
     cta_req = ana.cta_requirement(cta_site)
     e_cta, ar_cta = cta_req.get_angular_resolution()
 
-    if not 'label' in kwargs:
-        kwargs['label'] = "CTA requirement {}".format(cta_site)
+    kwargs.setdefault('label', "CTA requirement {}".format(cta_site))
 
     with quantity_support():
         ax.plot(e_cta, ar_cta, **kwargs)
@@ -758,8 +753,7 @@ def plot_angular_resolution_cta_performance(cta_site, ax=None, **kwargs):
     cta_req = ana.cta_performance(cta_site)
     e_cta, ar_cta = cta_req.get_angular_resolution()
 
-    if not 'label' in kwargs:
-        kwargs['label'] = "CTA performance {}".format(cta_site)
+    kwargs.setdefault('label', "CTA performance {}".format(cta_site))
 
     ax.plot(e_cta, ar_cta, **kwargs)
     ax.set_xscale('log')
@@ -804,8 +798,8 @@ def plot_impact_parameter_resolution_per_energy(true_x, reco_x, true_y, reco_y,
 def plot_impact_map(impact_x, impact_y, tel_x, tel_y, tel_types=None,
                     ax=None,
                     outfile=None,
-                    hist_kwargs={},
-                    scatter_kwargs={},
+                    hist_kwargs=None,
+                    scatter_kwargs=None,
                     ):
     """
     Map of the site with telescopes positions and impact points heatmap
@@ -824,13 +818,16 @@ def plot_impact_map(impact_x, impact_y, tel_x, tel_y, tel_types=None,
     """
     ax = plt.gca() if ax is None else ax
 
+    hist_kwargs = {} if hist_kwargs is None else hist_kwargs
+    scatter_kwargs = {} if scatter_kwargs is None else scatter_kwargs
+
     hist_kwargs.setdefault('bins', 40)
     unit = impact_x.value
     ax.hist2d(impact_x.to_value(unit), impact_y.to_value(unit), **hist_kwargs)
     pcm = ax.get_children()[0]
     plt.colorbar(pcm, ax=ax)
 
-    if not len(tel_x) == len(tel_y):
+    if len(tel_x) != len(tel_y):
         raise ValueError("tel_x and tel_y should have the same length")
 
     scatter_kwargs.setdefault('s', 50)
@@ -838,15 +835,12 @@ def plot_impact_map(impact_x, impact_y, tel_x, tel_y, tel_types=None,
     if tel_types and 'color' not in scatter_kwargs and 'c' not in scatter_kwargs:
         scatter_kwargs['color'] = tel_types
         assert (len(tel_types) == len(tel_x)), "tel_types and tel_x should have the same length"
-        with quantity_support():
-            ax.scatter(tel_x, tel_y, **scatter_kwargs)
     else:
         if 'color' not in scatter_kwargs and 'c' not in scatter_kwargs:
             scatter_kwargs['color'] = 'black'
         scatter_kwargs['marker'] = '+' if 'marker' not in scatter_kwargs else scatter_kwargs['marker']
-        with quantity_support():
-            ax.scatter(tel_x, tel_y, **scatter_kwargs)
-
+    with quantity_support():
+        ax.scatter(tel_x, tel_y, **scatter_kwargs)
     ax.axis('equal')
     if outfile is not None:
         plt.savefig(outfile, bbox_inches="tight", format='png', dpi=200)
@@ -871,7 +865,7 @@ def plot_energy_bias(true_energy, reco_energy, ax=None, bins=None, **kwargs):
     -------
     ax: `matplotlib.pyplot.axes`
     """
-    if not len(true_energy) == len(reco_energy):
+    if len(true_energy) != len(reco_energy):
         raise ValueError("simulated and reconstructured true_energy arrrays should have the same length")
 
     ax = plt.gca() if ax is None else ax
@@ -971,8 +965,7 @@ def plot_energy_resolution_cta_requirement(cta_site, ax=None, **kwargs):
     cta_req = ana.cta_requirement(cta_site)
     e_cta, ar_cta = cta_req.get_energy_resolution()
 
-    if not 'label' in kwargs:
-        kwargs['label'] = "CTA requirement {}".format(cta_site)
+    kwargs.setdefault('label', "CTA requirement {}".format(cta_site))
 
     ax.set_ylabel(r"$(\Delta energy/energy)_{68}$")
     ax.set_xlabel(rf'$E_R$ [{e_cta.unit.to_string("latex")}]')
@@ -1005,8 +998,7 @@ def plot_energy_resolution_cta_performance(cta_site, ax=None, **kwargs):
     cta_req = ana.cta_performance(cta_site)
     e_cta, ar_cta = cta_req.get_energy_resolution()
 
-    if not 'label' in kwargs:
-        kwargs['label'] = "CTA performance {}".format(cta_site)
+    kwargs.setdefault('label', "CTA performance {}".format(cta_site))
 
     ax.set_ylabel(r"$(\Delta energy/energy)_{68}$")
     ax.set_xlabel(rf'$E_R$ [{e_cta.unit.to_string("latex")}]')
@@ -1127,10 +1119,9 @@ def plot_migration_matrix(x, y, ax=None, colorbar=False, xy_line=False, hist2d_a
     >>> plot_migration_matrix(x, y, colorbar=True, hist2d_args=dict(norm=matplotlib.colors.LogNorm()))
     In this example, the colorbar will be log normed
     """
-    if hist2d_args is None:
-        hist2d_args = {}
-    if line_args is None:
-        line_args = {}
+
+    hist2d_args = {} if hist2d_args is None else hist2d_args
+    line_args = {} if line_args is None else line_args
 
     if 'bins_x' not in hist2d_args:
         hist2d_args['bins'] = 50
@@ -1559,8 +1550,7 @@ def plot_roc_curve(true_type, reco_proba,
     if auc_score < 0.5:
         auc_score = 1 - auc_score
 
-    if 'label' not in kwargs:
-        kwargs['label'] = "auc score = {:.3f}".format(auc_score)
+    kwargs.setdefault('label', "auc score = {:.3f}".format(auc_score))
 
     fpr, tpr, thresholds = metrics.roc_curve(true_type,
                                              reco_proba,
@@ -1813,8 +1803,7 @@ def plot_any_resource(filename, columns_xy=None, ax=None, **kwargs):
 
     data = load_any_resource(filename)
 
-    if 'label' not in kwargs:
-        kwargs['label'] = filename
+    kwargs.setdefault('label', filename)
     ax.plot(data[columns_xy[0]], data[columns_xy[1]], **kwargs)
 
     return ax
diff --git a/ctaplot/plots/style.py b/ctaplot/plots/style.py
index 9b7cce4..8dfc56c 100644
--- a/ctaplot/plots/style.py
+++ b/ctaplot/plots/style.py
@@ -12,7 +12,7 @@ def check_latex():
     -------
     bool: True if a LaTeX distribution could be found
     """
-    return not find_executable('latex') is None
+    return find_executable('latex') is not None
 
 
 @contextmanager