week 2 programs

Part Two/2-1-motto.py

@@ -0,0 +1,13 @@
+import os
+
+path = os.path.dirname(os.path.abspath(__file__))
+
+file = open(path+'/'+'motto.txt','w')
+file.write("Fiat Lux!")
+
+
+file.close()
+
+file = open(path+'/'+'motto.txt','a')
+file.write("\nLight Speed!")
+file.close()

Part Two/2-2-Flags.py

@@ -0,0 +1,25 @@
+from matplotlib import image
+from matplotlib import pyplot
+import os
+
+# Read an image file
+path = os.path.dirname(os.path.abspath(__file__))
+wales_flag = path + '/' + 'wales-flag-xs.jpg'
+lenna = path + '/' + 'lenna.bmp'
+bottom = image.imread(lenna)
+top = image.imread(wales_flag)
+# Display image information
+
+
+
+# Add some color boundaries to modify an image array
+edited = bottom.copy()
+for width in range(top.shape[1]):
+    for height in range(top.shape[0]):
+        edited[height][512-250+width] = [
+            (top[height][width][0]),
+            (top[height][width][1]),
+            (top[height][width][2]),
+        ]
+image.imsave(path+'/'+'lenna_with_dragon.jpg', edited)
+pyplot.imshow(edited)

Part Two/2-3-sense-sensibility.py

@@ -0,0 +1,43 @@
+import PyPDF2
+import os
+import string
+import time
+
+start_time = time.time()
+
+# Open PDF file
+path = os.path.dirname(os.path.abspath(__file__))
+file_path = os.path.join(path, 'Sense_and_sensibility.pdf')
+file_handle = open(file_path, 'rb')
+pdfReader = PyPDF2.PdfReader(file_handle)
+
+frequency_table = {}
+
+# Iterating thru pages
+for page_num in range(len(pdfReader.pages)):
+    page_object = pdfReader.pages[page_num]
+    page_text = page_object.extract_text()
+    words = page_text.split("\n")
+    for extracted_string in words:
+        # Clean the selected word
+        list_of_string = extracted_string.split()
+        for chars in list_of_string:
+            if chars.isdigit():
+                pass
+            if chars.isalpha(): 
+                if chars in frequency_table:
+                    frequency_table[chars] += 1
+                else:
+                    frequency_table[chars] = 1
+            else:
+                chars = chars[:-1]
+                if chars in frequency_table:
+                    frequency_table[chars] += 1
+                else:
+                    frequency_table[chars] = 1
+end_time = time.time()
+file_handle.close()
+
+total_distinct_words = len(frequency_table)
+print("Total number of unique words: " + str(total_distinct_words))
+print ("time taken: " + str(end_time-start_time))

Part Two/3-2-MatrixDotProd.py

@@ -0,0 +1,13 @@
+import numpy as np
+
+p1 = np.array([[6,-9,1],[4,24,8]])
+p1result = p1*2
+
+mi = np.eye(2)
+m2result = mi@p1
+
+p2 = np.array([[4,3],[3,2]])
+p3 = np.array([[-2,3],[3,-4]])
+
+rop3p2 = p2@p3
+print(rop3p2)

Part Two/3-3-Slicing.py

@@ -0,0 +1,8 @@
+import numpy as np
+a3 = np.array([list(range(i * 10,i * 10+6)) for i in range(6)])
+print(a3)
+a = a3[:,1]
+b=a3[1, 2:4]
+c=a3[2:4, 4:]
+d=a3[2::2, ::2]
+print(a,b,c,d)

Part Two/3-4.py

@@ -0,0 +1,21 @@
+import numpy as np
+
+def swap_Rows(M,a,b):
+    if a >= M.shape[0] or b >= M.shape[0] or a<0 or b<0:
+        raise IndexError("Row Indicies are out of bounds")
+    temp = M[a].copy()
+    M[[a,b],:]=M[[b,a],:]
+
+
+    return M
+def swap_Columns(M,a,b):
+    if a >= M.shape[1] or b >= M.shape[1] or a<0 or b<0:
+        raise IndexError("Row Indicies are out of bounds")
+    temp = M[:,a].copy()
+    M[:,a]=M[:,b]
+    M[:,b] = temp
+    M[:,[a,b]]=M[:,[b,a]]
+    return M
+
+v = np.array([[0,1,2],[3,4,5]])
+-

Part Two/3-5-MatrixArray.py

@@ -0,0 +1,12 @@
+import numpy as np
+sample_list = [1,2,3,4,5,6,7,8,9,10,11,12]
+def set_array(l,r,c):
+    sample_array = np.array(l)
+    shaped_array = sample_array.reshape(r,c)
+    return(shaped_array)
+
+x=set_array(sample_list,4,3)
+y=set_array(sample_list,3,4)
+
+z=x@y
+print(z)

clock.py

@@ -0,0 +1,57 @@
+## This is course material for Introduction to Python Scientific Programming
+## Example code: matplotlib_clock.py
+## Author: Allen Y. Yang
+##
+## (c) Copyright 2020. Intelligent Racing Inc. Not permitted for commercial use
+
+from datetime import datetime
+import matplotlib.pyplot as plt
+import os
+import numpy as np
+
+# Initialization, define some constant
+path = os.path.dirname(os.path.abspath(__file__))
+filename = path + '/airplane.bmp'
+background = plt.imread(filename)
+
+second_hand_length = 200
+second_hand_width = 2
+minute_hand_length = 150
+minute_hand_width = 6
+hour_hand_length = 100
+hour_hand_width = 10
+
+center = np.array([256, 256])
+def clock_hand_vector(angle, length):
+    return np.array([length * np.sin(angle), -length * np.cos(angle)])
+
+# draw an image background
+fig, ax = plt.subplots()
+ax.set_axis_off()
+while True:
+    plt.imshow(background)
+
+    # First retrieve the time
+    now_time = datetime.now()
+    hour = now_time.hour
+    if hour>12: hour = hour - 12
+    minute = now_time.minute
+    second = now_time.second
+
+    # Calculate end points of hour, minute, second
+    rps = second/60*2*np.pi
+    rpm = (minute + second / 60) / 60 * 2 * np.pi
+    rph = (hour + minute / 60 + second / 3600) / 12 * 2 * np.pi
+    rpgmth = hour + 7/ 24 * 2 * np.pi
+    hour_vector = clock_hand_vector(rph, hour_hand_length)
+    minute_vector = clock_hand_vector(rpm, minute_hand_length)
+    second_vector = clock_hand_vector(rps, second_hand_length)
+    gmt_vector = clock_hand_vector(rpgmth, second_hand_length)
+
+    plt.arrow(center[0], center[1], hour_vector[0], hour_vector[1], head_length = 3, linewidth = hour_hand_width, color = 'black')
+    plt.arrow(center[0], center[1], gmt_vector[0], gmt_vector[1], head_length = 3, linewidth = hour_hand_width, color = 'yellow')
+    plt.arrow(center[0], center[1], minute_vector[0], minute_vector[1], linewidth = minute_hand_width, color = 'black')
+    plt.arrow(center[0], center[1], second_vector[0], second_vector[1], linewidth = second_hand_width, color = 'red')
+
+    plt.pause(0.01)
+    plt.clf()

learning_rates.ipynb

@@ -0,0 +1,25 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#.0001\n",
+    "#.01\n",
+    "#.5\n",
+    "\"\"\"if you choose a value too small you will take forever\"\"\"\n",
+    "\"\"\"if you choose a value too large you might go past the limits of the graph\"\"\"\n",
+    "\"\"\"even if you had infinite time and resources, you should still not choose too small of a value because of local minima.\"\"\""
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

samples/read_image.py

@@ -22,8 +22,7 @@
 plot_data = data.copy()
 for width in range(512):
     for height in range(10):
-        plot_data[height][width] = [255, 0, 0]   # Alternatively plot_data[height][width][:] = [255, 0, 0]
-        plot_data[511-height][width] = [0,0,255]
+
 
 # Write the modified images
 image.imsave(path+'/'+'lenna-mod.jpg', plot_data)

samples/widget_slider.py

@@ -19,8 +19,8 @@
 
 # Create two sliders
 axcolor = 'lightgoldenrodyellow'
-axfreq = plt.axes([0.25, 0.1, 0.65, 0.03], facecolor=axcolor)
-axamp = plt.axes([0.25, 0.15, 0.65, 0.03], facecolor=axcolor)
+axfreq = plt.axes([0.25, 0.1, 0.65, 0.05], facecolor=axcolor)
+axamp = plt.axes([0.25, 0.15, 0.65, 0.05], facecolor=axcolor)
 sfreq = Slider(axfreq, 'Freq', 0.1, 30.0, valinit=f0, valstep=delta_f)
 samp = Slider(axamp, 'Amp', 0.1, 10.0, valinit=a0, valstep=delta_a)