Add numpy type hints example

Author: gjbex

source-code/typing/README.md

@@ -8,6 +8,7 @@ errors.
 Type checking can be done using [mypy](http://mypy-lang.org/index.html).
 
 ## What is it?
+1. `mypy.ini`: mypy configuration file.
 1. `correct.py`: code that has type annotations, and no type errors.
 1. `incorrect_01.py`: code that has type annotations, and passes a string
     to a function that expects an `int`.
@@ -33,3 +34,5 @@ Type checking can be done using [mypy](http://mypy-lang.org/index.html).
 1. `typed_duck_typing_false_positive.py`: example code illustrating
    duck typing using type hints for which mypy 0.910 generates a
    false positive.
+1. `numpy_typing.py`: illustration of a script using both numpy and
+   matplotlib with type hints.

source-code/typing/mypy.ini

@@ -0,0 +1,7 @@
+[mypy]
+strict = True
+plugins = numpy.typing.mypy_plugin
+
+[mypy-matplotlib.*]
+ignore_missing_imports = True
+ignore_errors = True

source-code/typing/numpy_typing.py

@@ -0,0 +1,58 @@
+#!/usr/bin/env python
+
+import argparse
+import matplotlib.pyplot as plt
+import numpy as np
+import numpy.typing as npt
+
+
+def generate_input(a: float | np.float32 | np.float64,
+                   b: float | np.float32 | np.float64,
+                   n: int | np.int32 | np.int64) -> npt.NDArray[np.float64]:
+    '''Generate x-values in given range
+
+    Parameters
+    ----------
+    a: float
+        lower bound
+    b: float
+        upper bound
+    n: int
+        number of points to generate
+
+    Returns
+    -------
+    np.NDarray
+        generated x-values
+    '''
+    return np.linspace(a, b, n)
+
+
+def gaussian(x: npt.NDArray[np.float64], mu: float, sigma: float) -> npt.NDArray[np.float64]:
+    y: npt.NDArray[np.float64] = np.exp(-0.5*(x - mu)**2/sigma)/np.sqrt(2.0*np.pi*sigma)
+    return y
+
+
+def plot_function(x: npt.NDArray[np.float64], y: npt.NDArray[np.float64]) -> None:
+    plt.plot(x, y)
+    plt.show()
+    return
+
+
+if __name__ == '__main__':
+    arg_parser = argparse.ArgumentParser(description='numpy type checking')
+    arg_parser.add_argument('--mu', type=float, default=0.0,
+                            help='mean value')
+    arg_parser.add_argument('--sigma', type=float, default=1.0,
+                            help='standard deviation')
+    arg_parser.add_argument('--n', type=int, default=10,
+                            help='number of points')
+    arg_parser.add_argument('--plot', action='set_true',
+                            help='show plot')
+    options = arg_parser.parse_args()
+    x = generate_input(-3.0, 3.0, options.n)
+    y = gaussian(x, options.mu, options.sigma)
+    if options.plot:
+        plot_function(x, y)
+    else:
+        print(y)