From ac7c430c8041f10d42cdf5291182ecc4d9eacd9b Mon Sep 17 00:00:00 2001
From: Dan Howe <d.howe@wrl.unsw.edu.au>
Date: Thu, 19 May 2022 11:05:59 +0200
Subject: [PATCH] Don't clobber 'i'

---
 .../probabilistic_assessment.py               | 24 +++++++++----------
 1 file changed, 12 insertions(+), 12 deletions(-)

diff --git a/probabilistic-analysis/probabilistic_assessment.py b/probabilistic-analysis/probabilistic_assessment.py
index 55439d8..64d0164 100644
--- a/probabilistic-analysis/probabilistic_assessment.py
+++ b/probabilistic-analysis/probabilistic_assessment.py
@@ -691,23 +691,23 @@ def process(beach_name, beach_scenario, n_runs, start_year, end_year,
                     dump_df = dump_df[::100]  # Only output every 100th row
                     dump_df.to_csv(csv_name, float_format='%g')
 
-                    for i, c in enumerate(dump_df.columns[3:]):
-                        ax[i, j].plot(dump_df.index,
+                    for k, c in enumerate(dump_df.columns[3:]):
+                        ax[k, j].plot(dump_df.index,
                                       dump_df[c],
                                       '.',
                                       color='#aaaaaa',
                                       alpha=0.1,
                                       markersize=2)
-                        ax[i, j].spines['right'].set_visible(False)
-                        ax[i, j].spines['top'].set_visible(False)
+                        ax[k, j].spines['right'].set_visible(False)
+                        ax[k, j].spines['top'].set_visible(False)
                         if j == 0:
-                            ax[i, 0].yaxis.set_label_coords(-0.4, 0.5)
+                            ax[k, 0].yaxis.set_label_coords(-0.4, 0.5)
                             label = c.replace('(', '\n(')
-                            ax[i, 0].set_ylabel(label,
+                            ax[k, 0].set_ylabel(label,
                                                 va='top',
                                                 linespacing=1.5)
 
-                    ax[i, j].set_xlabel('Encounter probability (%)',
+                    ax[k, j].set_xlabel('Encounter probability (%)',
                                         labelpad=10)
                     ax[0, j].set_title(year)
 
@@ -769,7 +769,7 @@ def process(beach_name, beach_scenario, n_runs, start_year, end_year,
 
                 baseline = r[:, 1]
                 sdd = storm_demand_dist[:, 1]
-                for i in range(len(slr)):
+                for k in range(len(slr)):
                     pe = [
                         matplotlib.patheffects.Stroke(linewidth=5,
                                                       foreground='#ffffff',
@@ -777,8 +777,8 @@ def process(beach_name, beach_scenario, n_runs, start_year, end_year,
                         matplotlib.patheffects.Normal()
                     ]
 
-                    ax[3, 0].plot([years[i], years[i]],
-                                  [baseline[i], baseline[i] + sdd[i]],
+                    ax[3, 0].plot([years[k], years[k]],
+                                  [baseline[k], baseline[k] + sdd[k]],
                                   c='C0',
                                   path_effects=pe)
 
@@ -786,7 +786,7 @@ def process(beach_name, beach_scenario, n_runs, start_year, end_year,
                 r_max = (baseline + sdd).max()
                 ax[3, 0].axhline(y=r_max, c='C3', linestyle=':')
 
-                i = len(years) - 1
+                k = len(years) - 1
                 for a in ax[:, 0]:
                     a.set_xlim(right=years[-1])
 
@@ -810,7 +810,7 @@ def process(beach_name, beach_scenario, n_runs, start_year, end_year,
                 ax[0, 0].set_title((f'Probabilistic trajectories\n'
                                     f'(first 100 out of {n_runs:,} runs)'))
                 ax[0, 1].set_title(
-                    f'Probability\ndistribution\nin year {years[i]}')
+                    f'Probability\ndistribution\nin year {years[k]}')
                 ax[0, 0].set_ylabel('Sea level (m)', labelpad=10)
                 ax[1, 0].set_ylabel('Bruun recession (m)', labelpad=10)
                 ax[2, 0].set_ylabel('Underlying recession (m)', labelpad=10)