diff --git a/.gitignore b/.gitignore
index ee3d72b9ce85ed0673faf083f70c44b1fef0a0b7..b84d884c191ce7ccec3b5d428e3383921b66e0ae 100644
--- a/.gitignore
+++ b/.gitignore
@@ -7,3 +7,4 @@ Stats/.Rhistory
Stats/.Rhistory
Stats/.Rhistory
Stats/.Rhistory
+Whistles/__pycache__/WhistleUtils.cpython-39.pyc
diff --git a/Whistles/1-Identification_of_whistles.py b/Whistles/1-Identification_of_whistles.py
index 906ed0f605c6cff15c5025b70b7ea0dd93974904..0db36477438f939d62e9118ce863575c5afb6470 100644
--- a/Whistles/1-Identification_of_whistles.py
+++ b/Whistles/1-Identification_of_whistles.py
@@ -22,7 +22,7 @@ print("Importation of packages complete!")
#%% Parameters
# Paths
print("\rSetting up parameters...", end="\r")
-audio_f = "./../Audio_data" # Path to recordings
+audio_f = "./../Audio_data" # Path to recordings
csv_f = "./../CSV_data" # Path to data in csv
save_f = "./Trajectories" # Path were results are stored
@@ -99,4 +99,33 @@ for file in range(len(audio_paths)):
f.close()
print(f"\r\tFile {file+1} on {len(audio_paths)}: found {len(values)} whistles", end='\r')
-print("\nDetection of whistles finished!")
\ No newline at end of file
+print("\nDetection of whistles finished!")
+
+#%% Uncomment this section to plot the last audio in loop
+# from WhistleUtils import plot_spectrums
+# final_traj[final_traj != 0] = 1 # binarisation
+
+# # generate bright colors to differenciate trajectories
+# prism = cm.get_cmap('prism', 256)
+# newcolors = prism(np.linspace(0, 1, np.unique(harmonized_traj).shape[0]))
+# pink = np.array([0/256, 0/256, 0/256, 1])
+# newcolors[0, :] = pink
+# newcmp = ListedColormap(newcolors)
+
+# # By default shows the whole audio
+# start = 0
+# stop = spectrum.shape[1]
+
+# # Create figure
+# fig, axs = plot_spectrums([amplitude_to_db(spectrum),
+# max_loc_per_bin_check1,
+# final_traj,
+# harmonized_traj],
+# ['gray_r', 'gray', 'gray', newcmp],
+# titles=['Spectrogram (dB scale)', 'Local maxima selection', 'Extraction of continuous trajectories',
+# 'Exclusion of harmonics'],
+# ylabels=["Frequency"]*4,
+# bins=375, title="")
+# # Update view
+# axs[3].set_xlim(start,stop)
+# plt.show(block=False)
\ No newline at end of file
diff --git a/Whistles/WhistleUtils.py b/Whistles/WhistleUtils.py
index 56b8271a34271d9fe9b223ae8c4ef017c5d893ba..487497485a99817462773eb8071c909e0677bfe1 100755
--- a/Whistles/WhistleUtils.py
+++ b/Whistles/WhistleUtils.py
@@ -17,6 +17,8 @@ from scipy.stats.mstats import gmean
from scipy.spatial import distance
from scipy import interpolate
+import matplotlib.pyplot as plt
+
#%% Functions process
def import_csv(csv_name, folder, useless=True, slash="/"):
"""
@@ -137,7 +139,7 @@ def get_local_maxima(spectrum, spectrum2, hardness, threshold=10e-5):
for each_bin in range(spectrum.shape[1]):
for freq in range(1, spectrum.shape[0]-1):
- if (spectrum1[freq, each_bin] > spectrum2[freq-1, each_bin]) and \
+ if (spectrum[freq, each_bin] > spectrum2[freq-1, each_bin]) and \
(spectrum2[freq, each_bin] > spectrum2[freq+1, each_bin]):
local_max1[freq, each_bin] = 1
if (spectrum[freq, each_bin] > (threshold)):
@@ -385,8 +387,8 @@ def get_category(samples, names, data_frame, category='acoustic'):
Returns
-------
- TYPE
- DESCRIPTION.
+ cat_list : LIST OF STRINGS
+ A list of categories corresponding to inputs.
"""
use_samples = np.array([file[:23] for file in samples])
@@ -425,4 +427,60 @@ def get_category(samples, names, data_frame, category='acoustic'):
== 'AV')[0]
cat_list[NC] = 'NC'
- return cat_list
\ No newline at end of file
+ return cat_list
+
+
+def plot_spectrums(list_of_spectrums, cmaps=[], direction=-1, title="Whistles",
+ bins=1, titles=[], ylabels=[]):
+ """
+ Parameters
+ ----------
+ list_of_spectrums : LIST OF NUMPY ARRAYS
+ List of images that will be plotted, should be a spectrogram
+ or a binary image (with 0s and 1s).
+ All arrays should be of the same shape.
+ cmaps : LIST
+ List that must contain the same number of elements as list_of_spectrums.
+ Each element is either the name of a cmap (e.g. "viridis") or a custom cmap.
+ direction : INT, optionnal
+ Must be 1 or -1. If -1 it inverses the order for frequency display.
+ Default is -1.
+ title : STRING, optionnal
+ Title that will be displayed on top of the plot.
+ bins : FLOAT, optionnal
+ Number of bins (windows in spectrogram) per second
+ titles : LIST OF STRINGS
+ List that must contain the same number of elements as list_of_spectrums.
+ Titles associated with each spectrogram in plot.
+ ylabels : LIST OF STRINGS
+ List that must contain the same number of elements as list_of_spectrums.
+ Name of y-axis for each spectrogram.
+
+ Returns
+ -------
+ fig, axs : MATPLOTLIB OBJECT
+ figure and axis object that contain the plot of all given spectrogram.
+
+ """
+ n = len(list_of_spectrums)
+ fig, axs = plt.subplots(nrows=n, sharex=True, sharey=True, figsize=(15,15))
+
+ if len(cmaps) == 0:
+ cmaps = ['gray_r']*n
+
+ for i in range(n):
+ axs[i].imshow(list_of_spectrums[i][::direction], aspect='auto',
+ interpolation='nearest', cmap=cmaps[i])
+ axs[i].set_yticklabels([])
+ if len(titles) > 0:
+ axs[i].set_title(titles[i], fontsize=30)
+ if len(ylabels) >0:
+ axs[i].set_ylabel(ylabels[i], fontsize=25)
+ axs[i].tick_params(axis='both', which='both', labelsize=20)
+ if bins !=1 :
+ axs[n-1].set_xlabel(f"Time in bins (1 bin = 1/{bins} sec)", fontsize=25)
+ else:
+ axs[n-1].set_xlabel(f"Time in bins)", fontsize=25)
+ fig.suptitle(title)
+ fig.tight_layout(pad=1)
+ return fig, axs
\ No newline at end of file