NumPy Integration with SciPy: Exercises, Practice and Solutions
This resource offers a total of 95 NumPy Integration with SciPy problems for practice. It includes 19 main exercises, each accompanied by solutions, detailed explanations, and four related problems.
The following exercises focus on integrating NumPy with SciPy for statistical analysis, signal processing, optimization, and machine learning. They demonstrate how SciPy extends NumPy's capabilities, making it easier to perform complex mathematical, scientific, and engineering computations efficiently.
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1. Random Array Statistical Properties
Write a NumPy program that creates a NumPy array of random numbers and uses SciPy to compute the statistical properties (mean, median, variance) of the array.
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2. Discrete Fourier Transform with fftpack
Write a NumPy program to generate a 2D array and performs a discrete Fourier transform using SciPy's fftpack module.
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3. Linear Algebra Operations with SciPy
Write a NumPy program that creates a NumPy array and uses SciPy to solve a linear algebra problem. For example, finding the determinant, inverse, and eigenvalues of a matrix.
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4. Interpolation with SciPy's Interpolate Module
Write a NumPy program to generate a set of data points using NumPy and perform interpolation using SciPy's interpolate module.
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5. Signal Processing on Time Series Data
Write a NumPy program to create a time series dataset and apply SciPy's signal processing functions to filter the data.
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6. Curve Fitting with SciPy's curve_fit
Write a NumPy program to create a set of sample data and fit a curve using SciPy's curve_fit function.
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7. Hypothesis Testing with SciPy Stats
Write a NumPy program to generate random samples and perform a hypothesis test using SciPy's stats module.
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8. Solving ODEs with SciPy
Write a Numpy program to create a NumPy array and use SciPy to solve a system of ordinary differential equations (ODEs).
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9. Multidimensional Scaling (MDS)
Write a Numpy program to generate a 3D dataset and perform multidimensional scaling (MDS) using SciPy.
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10. Sparse Matrix Operations with SciPy
Write a NumPy program to create a large sparse matrix and perform sparse matrix operations using SciPy's sparse module.
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11. Hierarchical Clustering with SciPy
Write a NumPy program to generate random data and perform clustering using SciPy's hierarchical clustering methods.
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12. Distance Metrics Computation
Write a NumPy program to create a dataset and compute various distance metrics (Euclidean, Manhattan, etc.) using SciPy.
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13. Rename Field in Structured Array
Write a NumPy program to rename the 'height' field to 'stature' in the structured array with fields for 'name' (string), 'age' (integer), and 'height' (float).
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14. Optimization with SciPy's Optimize Module
Write a NumPy program to generate a set of points and perform optimization using SciPy's optimize module to find the minimum of a function..
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15. Image Processing with SciPy ndimage
Write a NumPy program to create a NumPy array and use SciPy's ndimage module to perform image processing tasks, such as filtering and edge detection.
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16. Statistical Tests with SciPy Stats
Write a NumPy program to generate synthetic data using NumPy and apply SciPy's stats module to perform various statistical tests (t-test, chi-square test).
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17. Solving PDEs on a 2D Grid
Write a NumPy program to create a 2D grid of data points and solve a partial differential equation (PDE) using SciPy's integrated module.
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18. Geometric Transformations with SciPy ndimage
Write a Numpy program to generate a dataset and perform SciPy's ndimage geometric transformations (rotation, shift, zoom).
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19. Maximum Likelihood Estimation with SciPy Optimize
Write a NumPy program to generate a set of data and fit a statistical model using SciPy's optimize module for maximum likelihood estimation (MLE).
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