feat: 1522 l2 notes

cs2109s/labs/ps0/ps0.py

@@ -538,9 +538,8 @@ def average_increase_in_cases(n_cases_increase, n_adj_entries_avg=7):
     '''
 
     sd_win = np.lib.stride_tricks.sliding_window_view(n_cases_increase, 2 * n_adj_entries_avg + 1, axis=1)
-    avg = np.mean(sd_win, axis=2)
+    avg = np.floor(np.mean(sd_win, axis=2))
     res = np.pad(avg, ((0, 0), (n_adj_entries_avg, n_adj_entries_avg)), 'constant', constant_values=(np.nan, np.nan))
-    print(res)
     return res
 
 
@@ -552,7 +551,7 @@ def test_26():
     assert(np.array_equal(actual, expected, equal_nan=True))
 
 
-test_26()
+# test_26()
 
 # Task 2.7
 def is_peak(n_cases_increase_avg, n_adj_entries_peak=7):
@@ -605,9 +604,23 @@ def is_peak(n_cases_increase_avg, n_adj_entries_peak=7):
     Hint: to determine `n_adj_entries_avg` from `n_cases_increase_avg`,
     `np.count_nonzero` and `np.isnan` may be helpful.
     '''
+    # get the number of paddings to add (count nans and / 2)
+    paddings = int(np.count_nonzero(np.isnan(n_cases_increase_avg[0])) / 2)
+    nanless = n_cases_increase_avg[:, paddings: -paddings]
+    # find peaks (get the sliding window)
+    sd_win = np.lib.stride_tricks.sliding_window_view(nanless, 2 * n_adj_entries_peak + 1, axis=1)
+    mids = sd_win[:, :, n_adj_entries_peak]
+    left_vals = np.max(sd_win[:, :, :n_adj_entries_peak], axis=2)
+    right_vals = np.max(sd_win[:, :, n_adj_entries_peak+1:], axis=2)
+    peaks = (mids > left_vals) & (mids >= right_vals)
 
-    # TODO: add your solution here and remove `raise NotImplementedError`
-    raise NotImplementedError
+    means = np.nanmean(nanless, axis=1)[:, np.newaxis] * 0.1
+
+    significant = mids > means
+
+    result = np.logical_and(peaks, significant)
+    res = np.pad(result, ((0, 0), (paddings+n_adj_entries_peak, paddings+ n_adj_entries_peak)), 'constant', constant_values=(False, False))
+    return res
 
 
 def test_27():
@@ -627,7 +640,7 @@ def test_27():
                         [False, False, False, False, False, False, False, False, False]])
     assert np.all(actual2 == expected2)
 
-#test_27()
+test_27()
 
 def visualise_increase(n_cases_increase, n_cases_increase_avg=None):
     '''