Module thunderfish.consistentfishes
Compare fishlists created by the harmonics module in order to create a fishlist with fishes present in all fishlists.
consistent_fishes()
: Compares a list of fishlists and builds a consistent fishlist.plot_consistent_fishes()
: Visualize the algorithm of consisten_fishes().
Expand source code
"""
Compare fishlists created by the harmonics module in order to create a fishlist with
fishes present in all fishlists.
 `consistent_fishes()`: Compares a list of fishlists and builds a consistent fishlist.
 `plot_consistent_fishes()`: Visualize the algorithm of consisten_fishes().
"""
import numpy as np
from .harmonics import fundamental_freqs
def find_consistency(fundamentals, df_th=1.0):
"""
Compares lists of floats to find these values consistent in every list.
(with a certain threshold)
Every value of the first list is compared to the values of the other
lists. The consistency_help array consists in the beginning of ones,
has the same length as the first list and is used to keep the
information about values that are available in several lists. If the
difference between a value of the first list and a value of another
list is below the threshold the entry of the consistency_help array
is added 1 to at the index of the value in the value in the first
list. The indices of the consistency_help array that are equal to
the amount of lists compared are the indices of the values of the
first list that are consistent in all lists. The consistent value
array and the indices are returned.
Parameters

fundamentals: 2D array
List of lists containing the fundamentals of a fishlist.
fundamentals = [ [f1, f1, ..., f1, f1], [f2, f2, ..., f2, f2], ..., [fn, fn, ..., fn, fn] ]
df_th: float
Frequency threshold for the comparison of different fishlists in Hertz. If the fundamental
frequencies of two fishes from different fishlists vary less than this threshold they are
assigned as the same fish.
Returns

consistent_fundamentals: 1D array
List containing all values that are available in all given lists.
index: 1D array
Indices of the values that are in every list relating to the fist list in fishlists.
"""
consistency_help = np.ones(len(fundamentals[0]), dtype=int)
for enu, fundamental in enumerate(fundamentals[0]):
for list in range(1, len(fundamentals)):
if np.sum(np.abs(fundamentals[list]  fundamental) < df_th) > 0:
consistency_help[enu] += 1
index = np.arange(len(fundamentals[0]))[consistency_help == len(fundamentals)]
consistent_fundamentals = fundamentals[0][index]
return consistent_fundamentals, index
def consistent_fishes(fishlists, verbose=0, plot_data_func=None, df_th=1.0, **kwargs):
"""
Compares several fishlists to create a fishlist only containing these fishes present in all these fishlists.
Therefore several functions are used to first extract the fundamental frequencies of every fish in each fishlist,
before comparing them and building a fishlist only containing these fishes present in all fishlists.
Parameters

fishlists: list of list of 2D array
List of fishlists with harmonics and each frequency and power.
fishlists[fishlist][fish][harmonic][frequency, power]
plot_data_func:
Function that visualizes what consistent_fishes() did.
verbose: int
When the value larger than one you get additional shell output.
df_th: float
Frequency threshold for the comparison of different fishlists in Hertz. If the fundamental
frequencies of two fishes from different fishlists vary less than this threshold they are
assigned as the same fish.
**kwargs: dict
Passed on to plot function.
Returns

filtered_fishlist: list of 2D arrays
New fishlist with the same structure as a fishlist in fishlists only
containing these fishes that are available in every fishlist in fishlists.
fishlist[fish][harmonic][frequency, power]
"""
if verbose >= 1:
print('Finding consistent fishes out of %d fishlists ...' % len(fishlists))
fundamentals = fundamental_freqs(fishlists)
if len(fundamentals) == 0:
return []
consistent_fundamentals, index = find_consistency(fundamentals)
# creates a filtered fishlist only containing the data of the fishes consistent in several fishlists.
filtered_fishlist = []
for idx in index:
filtered_fishlist.append(fishlists[0][idx])
if plot_data_func:
plot_data_func(fishlists, filtered_fishlist, **kwargs)
return filtered_fishlist
def plot_consistent_fishes(fishlists, filtered_fishlist, ax, fs):
"""
Creates an axis for plotting all lists and the consistent values marked with a bar.
Parameters

filtered_fishlist: 3D array
Contains power and frequency of these fishes that hve been detected in
several powerspectra using different resolutions.
fishlists: 4D array or 3D array
List of or single fishlists with harmonics and each frequency and power.
fishlists[fishlist][fish][harmonic][frequency, power]
fishlists[fish][harmonic][frequency, power]
ax: axis for plot
Empty axis that is filled with content in the function.
fs: int
Fontsize for the plot.
"""
for list in np.arange(len(fishlists)):
for fish in np.arange(len(fishlists[list])):
ax.plot(list + 1, fishlists[list][fish][0][0], 'k.', markersize=10)
for fish in np.arange(len(filtered_fishlist)):
x = np.arange(len(fishlists)) + 1
y = [filtered_fishlist[fish][0][0] for i in range(len(fishlists))]
if fish == 0:
ax.plot(x, y, 'r', linewidth=10, alpha=0.5, label='consistent in all lists')
else:
ax.plot(x, y, 'r', linewidth=10, alpha=0.5)
ax.set_xlim([0, len(fishlists) + 1])
ax.set_ylabel('value', fontsize=fs)
ax.set_xlabel('list no.', fontsize=fs)
if __name__ == '__main__':
import matplotlib.pyplot as plt
print('Creating one fishlist containing only the fishes that are consistant in several fishlists.')
print('The input structure looks like this:')
print(' fishlists[list][fish][harmonic][frequency, power]')
print('')
print('Usage:')
print(' python m thunderfish.consistentfishes')
print('')
# example 4D array containing of 4 fishlists all haveing 3 fishes with 1 harmonic with frequency and power
fishlists = [[np.array([np.array([350, 0])]), np.array([np.array([700.2, 0])]), np.array([np.array([1050, 0])])],
[np.array([np.array([350.1, 0])]), np.array([np.array([699.8, 0])]), np.array([np.array([250.2, 0])])],
[np.array([np.array([349.7, 0])]), np.array([np.array([700.4, 0])]),
np.array([np.array([1050.2, 0])])],
[np.array([np.array([349.8, 0])]), np.array([np.array([700.5, 0])]),
np.array([np.array([1050.3, 0])])]]
#
fig, ax = plt.subplots()
filtered_fishlist = consistent_fishes(fishlists, verbose=1, plot_data_func=plot_consistent_fishes, ax=ax, fs=12)
plt.show()
# check almost empty fishlist:
fishlists = [[], [np.array([[349.8, 0], [700.5, 0], [1050.3, 0]])], []]
filtered_fishlist = consistent_fishes(fishlists, verbose=1)
print(filtered_fishlist)
# check empty fishlist:
fishlists = [[], []]
filtered_fishlist = consistent_fishes(fishlists, verbose=1)
print(filtered_fishlist)
# check really empty fishlist:
fishlists = []
filtered_fishlist = consistent_fishes(fishlists, verbose=1)
print(filtered_fishlist)
Functions
def consistent_fishes(fishlists, verbose=0, plot_data_func=None, df_th=1.0, **kwargs)

Compares several fishlists to create a fishlist only containing these fishes present in all these fishlists.
Therefore several functions are used to first extract the fundamental frequencies of every fish in each fishlist, before comparing them and building a fishlist only containing these fishes present in all fishlists.
Parameters
fishlists
:list
oflist
of2D array
 List of fishlists with harmonics and each frequency and power. fishlists[fishlist][fish][harmonic][frequency, power]
 plot_data_func:
 Function that visualizes what consistent_fishes() did.
verbose
:int
 When the value larger than one you get additional shell output.
df_th
:float
 Frequency threshold for the comparison of different fishlists in Hertz. If the fundamental frequencies of two fishes from different fishlists vary less than this threshold they are assigned as the same fish.
**kwargs
:dict
 Passed on to plot function.
Returns
filtered_fishlist
:list
of2D arrays
 New fishlist with the same structure as a fishlist in fishlists only containing these fishes that are available in every fishlist in fishlists. fishlist[fish][harmonic][frequency, power]
Expand source code
def consistent_fishes(fishlists, verbose=0, plot_data_func=None, df_th=1.0, **kwargs): """ Compares several fishlists to create a fishlist only containing these fishes present in all these fishlists. Therefore several functions are used to first extract the fundamental frequencies of every fish in each fishlist, before comparing them and building a fishlist only containing these fishes present in all fishlists. Parameters  fishlists: list of list of 2D array List of fishlists with harmonics and each frequency and power. fishlists[fishlist][fish][harmonic][frequency, power] plot_data_func: Function that visualizes what consistent_fishes() did. verbose: int When the value larger than one you get additional shell output. df_th: float Frequency threshold for the comparison of different fishlists in Hertz. If the fundamental frequencies of two fishes from different fishlists vary less than this threshold they are assigned as the same fish. **kwargs: dict Passed on to plot function. Returns  filtered_fishlist: list of 2D arrays New fishlist with the same structure as a fishlist in fishlists only containing these fishes that are available in every fishlist in fishlists. fishlist[fish][harmonic][frequency, power] """ if verbose >= 1: print('Finding consistent fishes out of %d fishlists ...' % len(fishlists)) fundamentals = fundamental_freqs(fishlists) if len(fundamentals) == 0: return [] consistent_fundamentals, index = find_consistency(fundamentals) # creates a filtered fishlist only containing the data of the fishes consistent in several fishlists. filtered_fishlist = [] for idx in index: filtered_fishlist.append(fishlists[0][idx]) if plot_data_func: plot_data_func(fishlists, filtered_fishlist, **kwargs) return filtered_fishlist
def find_consistency(fundamentals, df_th=1.0)

Compares lists of floats to find these values consistent in every list. (with a certain threshold)
Every value of the first list is compared to the values of the other lists. The consistency_help array consists in the beginning of ones, has the same length as the first list and is used to keep the information about values that are available in several lists. If the difference between a value of the first list and a value of another list is below the threshold the entry of the consistency_help array is added 1 to at the index of the value in the value in the first list. The indices of the consistency_help array that are equal to the amount of lists compared are the indices of the values of the first list that are consistent in all lists. The consistent value array and the indices are returned.
Parameters
fundamentals
:2D array
 List of lists containing the fundamentals of a fishlist. fundamentals = [ [f1, f1, …, f1, f1], [f2, f2, …, f2, f2], …, [fn, fn, …, fn, fn] ]
df_th
:float
 Frequency threshold for the comparison of different fishlists in Hertz. If the fundamental frequencies of two fishes from different fishlists vary less than this threshold they are assigned as the same fish.
Returns
consistent_fundamentals
:1D array
 List containing all values that are available in all given lists.
index
:1D array
 Indices of the values that are in every list relating to the fist list in fishlists.
Expand source code
def find_consistency(fundamentals, df_th=1.0): """ Compares lists of floats to find these values consistent in every list. (with a certain threshold) Every value of the first list is compared to the values of the other lists. The consistency_help array consists in the beginning of ones, has the same length as the first list and is used to keep the information about values that are available in several lists. If the difference between a value of the first list and a value of another list is below the threshold the entry of the consistency_help array is added 1 to at the index of the value in the value in the first list. The indices of the consistency_help array that are equal to the amount of lists compared are the indices of the values of the first list that are consistent in all lists. The consistent value array and the indices are returned. Parameters  fundamentals: 2D array List of lists containing the fundamentals of a fishlist. fundamentals = [ [f1, f1, ..., f1, f1], [f2, f2, ..., f2, f2], ..., [fn, fn, ..., fn, fn] ] df_th: float Frequency threshold for the comparison of different fishlists in Hertz. If the fundamental frequencies of two fishes from different fishlists vary less than this threshold they are assigned as the same fish. Returns  consistent_fundamentals: 1D array List containing all values that are available in all given lists. index: 1D array Indices of the values that are in every list relating to the fist list in fishlists. """ consistency_help = np.ones(len(fundamentals[0]), dtype=int) for enu, fundamental in enumerate(fundamentals[0]): for list in range(1, len(fundamentals)): if np.sum(np.abs(fundamentals[list]  fundamental) < df_th) > 0: consistency_help[enu] += 1 index = np.arange(len(fundamentals[0]))[consistency_help == len(fundamentals)] consistent_fundamentals = fundamentals[0][index] return consistent_fundamentals, index
def plot_consistent_fishes(fishlists, filtered_fishlist, ax, fs)

Creates an axis for plotting all lists and the consistent values marked with a bar.
Parameters
filtered_fishlist
:3D array
 Contains power and frequency of these fishes that hve been detected in several powerspectra using different resolutions.
fishlists
:4D array
or3D array
 List of or single fishlists with harmonics and each frequency and power. fishlists[fishlist][fish][harmonic][frequency, power] fishlists[fish][harmonic][frequency, power]
ax
:axis for plot
 Empty axis that is filled with content in the function.
fs
:int
 Fontsize for the plot.
Expand source code
def plot_consistent_fishes(fishlists, filtered_fishlist, ax, fs): """ Creates an axis for plotting all lists and the consistent values marked with a bar. Parameters  filtered_fishlist: 3D array Contains power and frequency of these fishes that hve been detected in several powerspectra using different resolutions. fishlists: 4D array or 3D array List of or single fishlists with harmonics and each frequency and power. fishlists[fishlist][fish][harmonic][frequency, power] fishlists[fish][harmonic][frequency, power] ax: axis for plot Empty axis that is filled with content in the function. fs: int Fontsize for the plot. """ for list in np.arange(len(fishlists)): for fish in np.arange(len(fishlists[list])): ax.plot(list + 1, fishlists[list][fish][0][0], 'k.', markersize=10) for fish in np.arange(len(filtered_fishlist)): x = np.arange(len(fishlists)) + 1 y = [filtered_fishlist[fish][0][0] for i in range(len(fishlists))] if fish == 0: ax.plot(x, y, 'r', linewidth=10, alpha=0.5, label='consistent in all lists') else: ax.plot(x, y, 'r', linewidth=10, alpha=0.5) ax.set_xlim([0, len(fishlists) + 1]) ax.set_ylabel('value', fontsize=fs) ax.set_xlabel('list no.', fontsize=fs)