2.6.5

findpeaks/__init__.py

@@ -23,7 +23,7 @@
 
 __author__ = 'Erdogan Tasksen'
 __email__ = '[email protected]'
-__version__ = '2.6.4'
+__version__ = '2.6.5'
 
 # module level doc-string
 __doc__ = """

findpeaks/examples.py

@@ -9,6 +9,33 @@
 import matplotlib.pyplot as plt
 # from findpeaks import findpeaks
 
+# %%
+# Import library
+from findpeaks import findpeaks
+# Initialize findpeaks with cearus method.
+# The default setting is that it only return peaks-vallyes with at least 5% difference. We can change this using params
+# fp = findpeaks(method='caerus',  params={'minperc': 10, 'window': 50})
+fp = findpeaks(method='caerus')
+# Import example data
+X = fp.import_example('facebook')
+# Fit
+results = fp.fit(X)
+# Make the plot
+fp.plot()
+
+# %%
+
+from findpeaks import findpeaks
+# Data
+X = [1153,672,501,1068,1110,574,135,23,3,47,252,812,1182]
+# Initialize
+fp = findpeaks(lookahead=1)
+results = fp.fit(X)
+# Plot
+fp.plot()
+results.get('df')
+
+
 # %% Issue29
 
 # Import library
@@ -258,7 +285,7 @@
 # fp = findpeaks(method='caerus', params_caerus={'minperc': 5, 'window': 50})
 fp = findpeaks(method='caerus', params={'minperc': 5, 'window': 50})
 results = fp.fit(X)
-
+fp.plot()
 
 # %% Issue 13
 # https://github.com/erdogant/findpeaks/issues/13
@@ -366,7 +393,7 @@
 results = fp.fit(X)
 fp.plot()
 
-fp = findpeaks(method="caerus", interpolate=None, params={'minperc': 100}, verbose=verbose)
+fp = findpeaks(method="caerus", interpolate=None, params={'minperc': 50, 'window':50}, verbose=verbose)
 # Make fit
 results = fp.fit(X)
 ax = fp.plot()

findpeaks/findpeaks.py

@@ -20,13 +20,13 @@
 from urllib.parse import urlparse
 
 # #### DEBUG ONLY ####
-# import stats as stats
-# from stats import disable_tqdm
-# import interpolate as interpolate
+import stats as stats
+from stats import disable_tqdm
+import interpolate as interpolate
 # #####################
-import findpeaks.stats as stats
-from findpeaks.stats import disable_tqdm
-import findpeaks.interpolate as interpolate
+# import findpeaks.stats as stats
+# from findpeaks.stats import disable_tqdm
+# import findpeaks.interpolate as interpolate
 
 
 # #####################
@@ -346,7 +346,9 @@ def peaks1d(self, X, x=None, method='peakdetect', height=0):
             # Post processing for the topology method
             result['topology'] = stats._post_processing(X, Xraw, result['valley'], result['peak'], self.interpolate, 1)
         elif method == 'caerus':
-            cs = caerus(**self.params)
+            caerus_params = self.params.copy()
+            if caerus_params.get('delta') is not None: caerus_params.pop('delta')
+            cs = caerus(**caerus_params)
             result = cs.fit(X, return_as_dict=True, verbose=self.verbose)
             # Post processing for the caerus method
             result['caerus'] = stats._post_processing(X, Xraw,

findpeaks/stats.py

@@ -6,24 +6,24 @@
 # Licence: MIT
 # ----------------------------------------------------
 
-import findpeaks.union_find as union_find
-from findpeaks.filters.lee import lee_filter
-from findpeaks.filters.lee_enhanced import lee_enhanced_filter
-from findpeaks.filters.lee_sigma import lee_sigma_filter
-from findpeaks.filters.kuan import kuan_filter
-from findpeaks.filters.frost import frost_filter
-from findpeaks.filters.median import median_filter
-from findpeaks.filters.mean import mean_filter
+# import findpeaks.union_find as union_find
+# from findpeaks.filters.lee import lee_filter
+# from findpeaks.filters.lee_enhanced import lee_enhanced_filter
+# from findpeaks.filters.lee_sigma import lee_sigma_filter
+# from findpeaks.filters.kuan import kuan_filter
+# from findpeaks.filters.frost import frost_filter
+# from findpeaks.filters.median import median_filter
+# from findpeaks.filters.mean import mean_filter
 
 # #### DEBUG ONLY ####
-# import union_find as union_find
-# from filters.lee import lee_filter
-# from filters.lee_enhanced import lee_enhanced_filter
-# from filters.lee_sigma import lee_sigma_filter
-# from filters.kuan import kuan_filter
-# from filters.frost import frost_filter
-# from filters.median import median_filter
-# from filters.mean import mean_filter
+import union_find as union_find
+from filters.lee import lee_filter
+from filters.lee_enhanced import lee_enhanced_filter
+from filters.lee_sigma import lee_sigma_filter
+from filters.kuan import kuan_filter
+from filters.frost import frost_filter
+from filters.median import median_filter
+from filters.mean import mean_filter
 # ######################
 
 from scipy.ndimage.morphology import generate_binary_structure, binary_erosion
@@ -570,6 +570,8 @@ def _post_processing(X, Xraw, min_peaks, max_peaks, interpolate, lookahead, labx
         idx_peaks, _ = zip(*max_peaks)
         idx_peaks = np.array(list(idx_peaks)).astype(int)
         idx_valleys, _ = zip(*min_peaks)
+        # Add first and last row
+        # idx_valleys = np.array(idx_valleys)
         idx_valleys = np.append(np.array(list(idx_valleys)), len(X) - 1).astype(int)
         idx_valleys = np.append(0, idx_valleys)