Merge pull request #9 from rickecon/chaps

Merging

CHANGELOG.md

@@ -5,6 +5,11 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [0.0.4] - 2023-10-27 02:00:00
+
+### Added
+- Updates the Python and Git chapters as well as the corresponding data, images, and code
+
 ## [0.0.3] - 2023-10-23 03:00:00
 
 ### Added
@@ -33,6 +38,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 
 
+[0.0.4]: https://github.com/OpenSourceEcon/CompMethods/compare/v0.0.3...v0.0.4
 [0.0.3]: https://github.com/OpenSourceEcon/CompMethods/compare/v0.0.2...v0.0.3
 [0.0.2]: https://github.com/OpenSourceEcon/CompMethods/compare/v0.0.1...v0.0.2
 [0.0.1]: https://github.com/OpenSourceEcon/CompMethods/compare/v0.0.0...v0.0.1

README.md

@@ -20,5 +20,8 @@ Please use the following citation form for this book.
 General citation to the book:
 * Evans, Richard W., *Computational Methods for Economists using Python*, Open access Jupyter Book, v#.#.#, 2023, https://opensourceecon.github.io/CompMethods/.
 
-Citation to a chapter in the book:
-* Evans, Richard W., "[insert chapter name]", in *Computational Methods for Economists using Python*, Open access Jupyter Book, v#.#.#, 2023, https://opensourceecon.github.io/CompMethods/ + [chapter path].
+Citation to a chapter in the book only authored by Evans:
+* Evans, Richard W., "[insert chapter name]", in *Computational Methods for Economists using Python*, Open access Jupyter Book, v#.#.#, 2023, https://opensourceecon.github.io/CompMethods + [chapter path].
+
+Citation to a chapter in the book only authored by multiple authors:
+* DeBacker, Jason and Richard W. Evans, "[insert chapter name]", in *Computational Methods for Economists using Python*, Open access Jupyter Book, v#.#.#, 2023, https://opensourceecon.github.io/CompMethods + [chapter path].

code/AdvancedNumPy/advanced_numpy.py

@@ -0,0 +1,143 @@
+# advanced_numpy.py
+"""Python Essentials: Advanced NumPy.
+<Name>
+<Class>
+<Date>
+"""
+import numpy as np
+from sympy import isprime
+from matplotlib import pyplot as plt
+
+
+def prob1(A):
+    """Make a copy of 'A' and set all negative entries of the copy to 0.
+    Return the copy.
+
+    Example:
+        >>> A = np.array([-3,-1,3])
+        >>> prob4(A)
+        array([0, 0, 3])
+    """
+    raise NotImplementedError("Problem 1 Incomplete")
+
+
+def prob2(arr_list):
+    """return all arrays in arr_list as one 3-dimensional array
+    where the arrays are padded with zeros appropriately."""
+    raise NotImplementedError("Problem 2 Incomplete")
+
+
+def prob3(func, A):
+    """Time how long it takes to run func on the array A in two different ways,
+    where func is a universal function.
+    First, use array broadcasting to operate on the entire array element-wise.
+    Second, use a nested for loop, operating on each element individually.
+    Return the ratio showing how many times faster array broadcasting is than
+    using a nested for loop, averaged over 10 trials.
+
+    Parameters:
+            func -- array broadcast-able numpy function
+            A -- nxn array to operate on
+    Returns:
+            num_times_faster -- float
+    """
+    raise NotImplementedError("Problem 3 Incomplete")
+
+
+def prob4(A):
+    """Divide each row of 'A' by the row sum and return the resulting array.
+
+    Example:
+        >>> A = np.array([[1,1,0],[0,1,0],[1,1,1]])
+        >>> prob6(A)
+        array([[ 0.5       ,  0.5       ,  0.        ],
+               [ 0.        ,  1.        ,  0.        ],
+               [ 0.33333333,  0.33333333,  0.33333333]])
+    """
+    raise NotImplementedError("Problem 4 Incomplete")
+
+
+# this is provided for problem 5
+def LargestPrime(x, show_factorization=False):
+    # account for edge cases.
+    if x == 0 or x == 1:
+        return np.nan
+
+    # create needed variables
+    forced_break = False
+    prime_factors = []  # place to store factors of number
+    factor_test_arr = np.arange(1, 11)
+
+    while True:
+        # a factor is never more than half the number
+        if np.min(factor_test_arr) > (x // 2) + 1:
+            forced_break = True
+            break
+        if isprime(x):  # if the checked number is prime itself, stop
+            prime_factors.append(x)
+            break
+
+        # check if anythin gin the factor_test_arr are factors
+        div_arr = x / factor_test_arr
+        factor_mask = div_arr - div_arr.astype(int) == 0
+        divisors = factor_test_arr[factor_mask]
+        if divisors.size > 0:  # if divisors exist...
+            if (
+                divisors[0] == 1 and divisors.size > 1
+            ):  # make sure not to select 1
+                i = 1
+            elif (
+                divisors[0] == 1 and divisors.size == 1
+            ):  # if one is the only one don't pick it
+                factor_test_arr = factor_test_arr + 10
+                continue
+            else:  # othewise take the smallest divisor
+                i = 0
+
+            # if divisor was found divide number by it and
+            # repeat the process
+            x = int(x / divisors[i])
+            prime_factors.append(divisors[i])
+            factor_test_arr = np.arange(1, 11)
+        else:  # if no number was found increase the test_arr
+            # and keep looking for factors
+            factor_test_arr = factor_test_arr + 10
+            continue
+
+    if show_factorization:  # show entire factorization if desired
+        print(prime_factors)
+    if forced_break:  # if too many iterations break
+        print(f"Something wrong, exceeded iteration threshold for value: {x}")
+        return 0
+    return max(prime_factors)
+
+
+def prob5(arr, naive=False):
+    """Return an array where every number is replaced be the largest prime
+    in its factorization. Implement two methods. Switching between the two
+    is determined by a bool.
+
+    Example:
+        >>> A = np.array([15, 41, 49, 1077])
+        >>> prob4(A)
+        array([5,41,7,359])
+    """
+    raise NotImplementedError("Problem 5 Incomplete")
+
+
+def prob6(x, y, z, A, optimize=False, split=True):
+    """takes three vectors and a matrix and performs
+    (np.outer(x,y)*z.reshape(-1,1))@A on them using einsum."""
+    raise NotImplementedError("Problem 6 part 1 Incomplete")
+
+
+def naive6(x, y, z, A):
+    """uses normal numpy functions to do what prob5 does"""
+    raise NotImplementedError("Problem 6 part 2 Incomplete")
+
+
+def prob7():
+    """Times and creates plots that generate the difference in
+    speeds between einsum and normal numpy functions
+    """
+    raise NotImplementedError("Problem 7 Incomplete")

code/Exceptions_FileIO/cf_example1.txt

@@ -0,0 +1,2 @@
+A b C
+d E f

code/Exceptions_FileIO/cf_example2.txt

@@ -0,0 +1,3 @@
+Ab Cd
+Ef Gh
+Ij Kl

code/Exceptions_FileIO/exceptions_fileIO.py

@@ -0,0 +1,108 @@
+# exceptions_fileIO.py
+"""Python Essentials: Exceptions and File Input/Output.
+<Name>
+<Class>
+<Date>
+"""
+
+from random import choice
+
+
+# Problem 1
+def arithmagic():
+    """
+    Takes in user input to perform a magic trick and prints the result.
+    Verifies the user's input at each step and raises a
+    ValueError with an informative error message if any of the following occur:
+
+    The first number step_1 is not a 3-digit number.
+    The first number's first and last digits differ by less than $2$.
+    The second number step_2 is not the reverse of the first number.
+    The third number step_3 is not the positive difference of the first two numbers.
+    The fourth number step_4 is not the reverse of the third number.
+    """
+
+    step_1 = input(
+        "Enter a 3-digit number where the first and last "
+        "digits differ by 2 or more: "
+    )
+    step_2 = input(
+        "Enter the reverse of the first number, obtained "
+        "by reading it backwards: "
+    )
+    step_3 = input("Enter the positive difference of these numbers: ")
+    step_4 = input("Enter the reverse of the previous result: ")
+    print(str(step_3), "+", str(step_4), "= 1089 (ta-da!)")
+
+
+# Problem 2
+def random_walk(max_iters=1e12):
+    """
+    If the user raises a KeyboardInterrupt by pressing ctrl+c while the
+    program is running, the function should catch the exception and
+    print "Process interrupted at iteration $i$".
+    If no KeyboardInterrupt is raised, print "Process completed".
+
+    Return walk.
+    """
+
+    walk = 0
+    directions = [1, -1]
+    for i in range(int(max_iters)):
+        walk += choice(directions)
+    return walk
+
+
+# Problems 3 and 4: Write a 'ContentFilter' class.
+class ContentFilter(object):
+    """Class for reading in file
+
+    Attributes:
+        filename (str): The name of the file
+        contents (str): the contents of the file
+
+    """
+
+    # Problem 3
+    def __init__(self, filename):
+        """Read from the specified file. If the filename is invalid, prompt
+        the user until a valid filename is given.
+        """
+
+    # Problem 4 ---------------------------------------------------------------
+    def check_mode(self, mode):
+        """Raise a ValueError if the mode is invalid."""
+
+    def uniform(self, outfile, mode="w", case="upper"):
+        """Write the data to the outfile with uniform case. Include an additional
+        keyword argument case that defaults to "upper". If case="upper", write
+        the data in upper case. If case="lower", write the data in lower case.
+        If case is not one of these two values, raise a ValueError."""
+
+    def reverse(self, outfile, mode="w", unit="word"):
+        """Write the data to the outfile in reverse order. Include an additional
+        keyword argument unit that defaults to "line". If unit="word", reverse
+        the ordering of the words in each line, but write the lines in the same
+        order as the original file. If units="line", reverse the ordering of the
+        lines, but do not change the ordering of the words on each individual
+        line. If unit is not one of these two values, raise a ValueError."""
+
+    def transpose(self, outfile, mode="w"):
+        """Write a transposed version of the data to the outfile. That is, write
+        the first word of each line of the data to the first line of the new file,
+        the second word of each line of the data to the second line of the new
+        file, and so on. Viewed as a matrix of words, the rows of the input file
+        then become the columns of the output file, and viceversa. You may assume
+        that there are an equal number of words on each line of the input file.
+        """
+
+    def __str__(self):
+        """Printing a ContentFilter object yields the following output:
+
+        Source file:            <filename>
+        Total characters:       <The total number of characters in file>
+        Alphabetic characters:  <The number of letters>
+        Numerical characters:   <The number of digits>
+        Whitespace characters:  <The number of spaces, tabs, and newlines>
+        Number of lines:        <The number of lines>
+        """

code/Exceptions_FileIO/hello_world.txt

@@ -0,0 +1,2 @@
+Hello,
+World!

code/Matplotlib1/matplotlib_intro.py

@@ -0,0 +1,92 @@
+# matplotlib_intro.py
+"""Python Essentials: Intro to Matplotlib.
+<Name>
+<Class>
+<Date>
+"""
+
+
+# Problem 1
+def var_of_means(n):
+    """Create an (n x n) array of values randomly sampled from the standard
+    normal distribution. Compute the mean of each row of the array. Return the
+    variance of these means.
+
+    Parameters:
+        n (int): The number of rows and columns in the matrix.
+
+    Returns:
+        (float) The variance of the means of each row.
+    """
+    raise NotImplementedError("Problem 1 Incomplete")
+
+
+def prob1():
+    """Create an array of the results of var_of_means() with inputs
+    n = 100, 200, ..., 1000. Plot and show the resulting array.
+    """
+    raise NotImplementedError("Problem 1 Incomplete")
+
+
+# Problem 2
+def prob2():
+    """Plot the functions sin(x), cos(x), and arctan(x) on the domain
+    [-2pi, 2pi]. Make sure the domain is refined enough to produce a figure
+    with good resolution.
+    """
+    raise NotImplementedError("Problem 2 Incomplete")
+
+
+# Problem 3
+def prob3():
+    """Plot the curve f(x) = 1/(x-1) on the domain [-2,6].
+    1. Split the domain so that the curve looks discontinuous.
+    2. Plot both curves with a thick, dashed magenta line.
+    3. Set the range of the x-axis to [-2,6] and the range of the
+       y-axis to [-6,6].
+    """
+    raise NotImplementedError("Problem 3 Incomplete")
+
+
+# Problem 4
+def prob4():
+    """Plot the functions sin(x), sin(2x), 2sin(x), and 2sin(2x) on the
+    domain [0, 2pi], each in a separate subplot of a single figure.
+        1. Arrange the plots in a 2 x 2 grid of subplots.
+        2. Set the limits of each subplot to [0, 2pi]x[-2, 2].
+        3. Give each subplot an appropriate title.
+        4. Give the overall figure a title.
+        5. Use the following line colors and styles.
+              sin(x): green solid line.
+             sin(2x): red dashed line.
+             2sin(x): blue dashed line.
+            2sin(2x): magenta dotted line.
+    """
+    raise NotImplementedError("Problem 4 Incomplete")
+
+
+# Problem 5
+def prob5():
+    """Visualize the data in FARS.npy. Use np.load() to load the data, then
+    create a single figure with two subplots:
+        1. A scatter plot of longitudes against latitudes. Because of the
+            large number of data points, use black pixel markers (use "k,"
+            as the third argument to plt.plot()). Label both axes.
+        2. A histogram of the hours of the day, with one bin per hour.
+            Label and set the limits of the x-axis.
+    """
+    raise NotImplementedError("Problem 5 Incomplete")
+
+
+# Problem 6
+def prob6():
+    """Plot the function g(x,y) = sin(x)sin(y)/xy on the domain
+    [-2pi, 2pi]x[-2pi, 2pi].
+        1. Create 2 subplots: one with a heat map of g, and one with a contour
+            map of g. Choose an appropriate number of level curves, or specify
+            the curves yourself.
+        2. Set the limits of each subplot to [-2pi, 2pi]x[-2pi, 2pi].
+        3. Choose a non-default color scheme.
+        4. Include a color scale bar for each subplot.
+    """
+    raise NotImplementedError("Problem 6 Incomplete")