Peak finding (find_peaks) in SciPy - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Find peaks in a simple signal

What is the output of the following code that finds peaks in a signal array?

SciPy

import numpy as np
from scipy.signal import find_peaks

signal = np.array([0, 2, 1, 3, 0, 1, 2, 1, 0])
peaks, _ = find_peaks(signal)
print(peaks.tolist())

A [1, 3, 5, 6]

B [0, 3, 6]

C [2, 4, 7]

D [1, 3, 6]

💡 Hint

Peaks are points higher than their immediate neighbors.

The peaks are at indices 1 (value 2), 3 (value 3), and 6 (value 2) because these points are greater than their neighbors.

❓ data_output

intermediate

Count peaks with minimum height

Given the signal array, how many peaks have a height of at least 3?

SciPy

import numpy as np
from scipy.signal import find_peaks

signal = np.array([1, 3, 7, 1, 2, 6, 0, 1])
peaks, properties = find_peaks(signal, height=3)
print(len(peaks))

A 3

B 2

C 4

D 1

💡 Hint

Check which peaks have values >= 3.

Peaks are at indices 2 (7) and 5 (6), both >= 3, so count is 2.

❓ visualization

advanced

Visualize peaks with minimum distance

Which plot correctly shows peaks found with a minimum distance of 3 between them?

SciPy

import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import find_peaks

signal = np.array([0, 2, 1, 3, 0, 1, 2, 1, 0])
peaks, _ = find_peaks(signal, distance=3)
plt.plot(signal)
plt.plot(peaks, signal[peaks], "x")
plt.show()

A Plot with peaks marked at indices 0, 3, and 6

B Plot with peaks marked at indices 1, 3, and 6

C Plot with peaks marked at indices 1 and 6 only

D Plot with peaks marked at indices 3 and 6 only

💡 Hint

Minimum distance means peaks must be at least 3 indices apart.

Peaks at indices 1 and 6 are at least 3 apart. Peak at 3 is too close to 1, so it is excluded.

🔧 Debug

advanced

Identify error in peak finding code

What error does the following code produce?

SciPy

import numpy as np
from scipy.signal import find_peaks

signal = [1, 2, 3, 2, 1]
peaks, properties = find_peaks(signal, height='high')

A ValueError: height must be a number or tuple of numbers

B No error, returns peaks at indices [2]

C SyntaxError: invalid syntax

D TypeError: '>' not supported between instances of 'str' and 'int'

💡 Hint

Check the type of the height parameter.

The height parameter expects a number or tuple, but a string 'high' is given, causing a ValueError.

🚀 Application

expert

Find peaks with multiple conditions

Which option correctly finds peaks in the signal that have a height of at least 2 and a prominence of at least 1?

SciPy

import numpy as np
from scipy.signal import find_peaks

signal = np.array([0, 2, 1, 3, 0, 1, 2, 1, 0])
peaks, properties = find_peaks(signal, height=2, prominence=1)
print(peaks.tolist())

A [3, 6]

B [1, 3]

C [1, 3, 6]

D [1, 6]

💡 Hint

Prominence measures how much a peak stands out from its surroundings.

Peaks at indices 3 and 6 meet both height >= 2 and prominence >= 1 conditions.

Practice

1. What does the find_peaks function in scipy do?

easy

A. It finds local maxima (peaks) in a 1D array of data.

B. It sorts the data in ascending order.

C. It calculates the average value of the data.

D. It removes all negative values from the data.

Solution

1. Step 1: Understand the purpose of find_peaks

   The function is designed to identify points in data where values are higher than their neighbors, called peaks.

2. Step 2: Compare options with function behavior

   Only It finds local maxima (peaks) in a 1D array of data. correctly describes this behavior; others describe unrelated operations.

3. Final Answer:

   It finds local maxima (peaks) in a 1D array of data. -> Option A

4. Quick Check:

   find_peaks locates peaks = D [OK]

Hint: Remember: find_peaks finds highs, not sorting or averaging [OK]

Common Mistakes:

• Confusing peak finding with sorting data
• Thinking it calculates statistics like mean
• Assuming it filters values instead of locating peaks

2. Which of the following is the correct way to import and use find_peaks from scipy.signal?

easy

A. import find_peaks from scipy.signal
peaks = find_peaks(data)

B. from scipy.signal import find_peaks
peaks = find_peaks(data)

C. from scipy import find_peaks
peaks = find_peaks(data)

D. import scipy.signal.find_peaks
peaks = find_peaks(data)

Solution

1. Step 1: Recall correct import syntax in Python

   Python uses 'from module import function' to import specific functions.

2. Step 2: Match syntax with options

   from scipy.signal import find_peaks peaks = find_peaks(data) uses correct syntax. Options A, C, and D have invalid import statements.

3. Final Answer:

   from scipy.signal import find_peaks\npeaks = find_peaks(data) -> Option B

4. Quick Check:

   Correct import syntax = B [OK]

Hint: Use 'from module import function' for specific imports [OK]

Common Mistakes:

• Using 'import function from module' which is invalid
• Trying to import from wrong module path
• Using dot notation in import statement incorrectly

3. Given the code below, what will be the output of peaks?

import numpy as np
from scipy.signal import find_peaks

data = np.array([0, 2, 1, 3, 0, 1, 2, 1])
peaks, _ = find_peaks(data, height=2)
print(peaks)

medium

A. [3]

B. [1 3]

C. [1 3 6]

D. [2 5]

Solution

1. Step 1: Identify peaks in the data array

   Data values: [0, 2, 1, 3, 0, 1, 2, 1]. Peaks are points higher than neighbors: indices 1 (2), 3 (3), and 6 (2).

2. Step 2: Apply height=2 filter

   Peaks with height >= 2 are kept. Index 1 (2 >= 2), 3 (3 >= 2), 6 (2 >= 2), so indices 1, 3, 6 remain.

3. Final Answer:

   [1 3 6] -> Option C

4. Quick Check:

   Peaks with height >= 2 = [1 3 6] [OK]

Hint: Check peak values against height filter carefully [OK]

Common Mistakes:

• Thinking height filter requires strictly greater than threshold (it's >=)
• Misidentifying peak positions
• Ignoring the height parameter

4. The following code is intended to find peaks at least 3 units apart, but it returns more peaks than expected. What is the error?

import numpy as np
from scipy.signal import find_peaks

data = np.array([1, 3, 2, 4, 3, 5, 2])
peaks = find_peaks(data, 3)
print(peaks)

medium

A. The distance parameter is not applied because it should be passed as a keyword argument.

B. The distance parameter is applied correctly; the issue is with the data array.

C. The code is missing parentheses around the print argument.

D. The find_peaks function does not support the distance parameter.

Solution

1. Step 1: Check how distance parameter is passed

   In find_peaks, distance must be passed as a keyword argument, e.g., distance=3.

2. Step 2: Analyze the code

   The code passes 3 positionally after data, which sets height=3 instead of distance=3. Thus distance is not applied, returning all local peaks [1,3,5] instead of filtered [1,5].

3. Step 3: Verify output type

   find_peaks returns a tuple (indices, properties). Printing peaks directly prints the tuple, which may confuse.

4. Final Answer:

   The distance parameter is not applied because it should be passed as a keyword argument. -> Option A

5. Quick Check:

   distance must be keyword argument = C [OK]

Hint: Always pass distance as keyword argument: distance=number [OK]

Common Mistakes:

• Passing distance as positional argument
• Expecting find_peaks to return only indices
• Misunderstanding output format of find_peaks

5. You have noisy sensor data and want to find peaks that are at least 5 units high and at least 10 samples apart. Which find_peaks call correctly applies these conditions?

import numpy as np
from scipy.signal import find_peaks

sensor_data = np.random.rand(100) * 10

# Which call is correct?

hard

A. peaks = find_peaks(sensor_data, height=(5, None), distance=10)

B. peaks = find_peaks(sensor_data, height=5, distance=10)

C. peaks, _ = find_peaks(sensor_data, min_height=5, min_distance=10)

D. peaks, _ = find_peaks(sensor_data, height=5, distance=10)

Solution

1. Step 1: Understand parameter usage in find_peaks

   Height is specified with 'height=5' to find peaks at least 5 units high. Distance is specified with 'distance=10' to ensure peaks are at least 10 samples apart.

2. Step 2: Evaluate each option

   peaks, _ = find_peaks(sensor_data, height=5, distance=10) correctly uses height and distance parameters and unpacks the tuple output. peaks = find_peaks(sensor_data, height=5, distance=10) misses unpacking. peaks, _ = find_peaks(sensor_data, min_height=5, min_distance=10) uses invalid parameter names. peaks = find_peaks(sensor_data, height=(5, None), distance=10) uses a tuple for height which is valid but unnecessary here.

3. Final Answer:

   peaks, _ = find_peaks(sensor_data, height=5, distance=10) -> Option D

4. Quick Check:

   Use height and distance keywords, unpack output = A [OK]

Hint: Use height= and distance= with unpacking for correct results [OK]

Common Mistakes:

• Using wrong parameter names like min_height
• Not unpacking the tuple returned by find_peaks
• Passing height as a tuple unnecessarily