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Changed find_nearest_peak

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Diana 2024-10-27 12:37:00 +01:00
parent 09a86f5d6f
commit 4a7e963c03
1 changed files with 16 additions and 8 deletions
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24
code/useful_functions.py
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@ -18,10 +18,10 @@ def all_coming_together(freq_array, power_array, points_list, categories, num_ha
color = colors[i]
# Calculate the integral for the point
integral, local_mean = calculate_integral_2(freq_array, power_array, point, delta)
integral, local_mean = calculate_integral_2(freq_array, power_array, point)
# Check if the point is valid
valid = valid_integrals(integral, local_mean, point, threshold)
valid = valid_integrals(integral, local_mean, point)
if valid:
# Prepare harmonics if the point is valid
harmonics, color_map, category_harm = prepare_harmonic(point, category, num_harmonics, color)
@ -148,10 +148,11 @@ def calculate_integral_2(freq, power, peak_freq, delta=2.5):
local_mean : float
The local mean value (adjacent integrals).
"""
# Calculate integral around the nearest peak
# Calculate integral around the peak frequency
indices = (freq >= peak_freq - delta) & (freq <= peak_freq + delta)
integral = np.trapz(power[indices], freq[indices])
# Calculate local mean from adjacent ranges
left_indices = (freq >= peak_freq - 5 * delta) & (freq < peak_freq - delta)
right_indices = (freq > peak_freq + delta) & (freq <= peak_freq + 5 * delta)
@ -162,7 +163,6 @@ def calculate_integral_2(freq, power, peak_freq, delta=2.5):
return integral, local_mean
def contrast_sorting(sams, con_1 = 20, con_2 = 10, con_3 = 5, stim_count = 3, stim_dur = 2):
'''
sorts the sams into three contrasts
@ -269,7 +269,8 @@ def find_AM(eodf, nyquist, stimulus_frequency):
AM = t2[np.argmin(np.abs(x_values - stimulus_frequency))]
return AM
def find_nearest_peak(freq, power, point, threshold=0.5e-6, peak_search_range=10):
def find_nearest_peak(freq, power, point, peak_search_range=30, threshold=None):
"""
Find the nearest peak within a specified range around a given point.
@ -283,27 +284,34 @@ def find_nearest_peak(freq, power, point, threshold=0.5e-6, peak_search_range=10
The harmonic frequency for which to find the nearest peak.
peak_search_range : float, optional
Range in Hz to search for peaks around the specified point. The default is 30.
threshold : float, optional
Minimum height of peaks to consider. If None, no threshold is applied.
Returns
-------
peak_freq : float
The frequency of the nearest peak within the specified range.
The frequency of the nearest peak within the specified range, or the input point if no peak is found.
"""
# Define the range for peak searching
search_indices = (freq >= point - peak_search_range) & (freq <= point + peak_search_range)
# Find peaks in the specified range
peaks, _ = find_peaks(power[search_indices], height=threshold)
peaks, properties = find_peaks(power[search_indices], height=threshold)
# Adjust peak indices to match the original frequency array
peaks_freq = freq[search_indices][peaks]
if peaks_freq.size == 0:
# No peaks detected, return the input point
return point
# Find the nearest peak to the specified point
nearest_peak_index = np.argmin(np.abs(peaks_freq - point))
peak_freq = peaks_freq[nearest_peak_index]
return peak_freq
def firing_rate(binary_spikes, dt = 0.000025, box_width = 0.01):
'''
Calculates the firing rate from binary spikes