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Python: Numpay – P2

November 10, 2019 2 comments


Learning : Python Numpy – P2
Subject: Two Dimensional array and some basic commands

In real mathematics word we mostly using arrays with more than one dimensions, for example with two dimension array we can store a data as

So let’s start, if we want to create an array with 24 number in it starting from 0 to 23 we use the command np.range. as bellow :

 # We are using np.range to create an array of numbers between (0-23) 

m_array = np.arange(24)
print(m_array)
[Output]: 
[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23]
 


And if we want the array to be in a range with certain incriminating amount we may use this command:

 # Create array between 2-3 with 0.1 interval 

m_array = np.arange(2, 3, 0.1)
print(m_array)
[Output]: 
[ 2. , 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9]


Now if we want to create an array say 3×3 fill with random numbers from (0-10) we use random function in numpy as bellow:

 # create 3x3 Array with random numbers 0-10 
m_array = np.random.randint(10, size=(3,3))
print(m_array)
[Output]: 
[[6 0 7]
 [1 9 8]
 [5 8 9]] 



And if we want the random number ranges to be between two numbers we use this command:

# Array 3x3 random values between (10-60)
m_array = np.random.randint(10,60, size=(3,3))
[Output]: 
[[11 23 50]
 [36 44 18]
 [56 24 30]] 


If we want to reshape the array; say from 4×5 (20 element in the array) we can reshape it but with any 20-element size. Here is the code:

# To crate a randome numbers in an array of 4x5 and numbers range 10-60.
m_array = np.random.randint(10,60, size=(4,5))
print(m_array)

# We will reshape the 4x5 to 2x10
new_shape = m_array.reshape(2,10)
print ('\n   Tne new 2x10 array:\n',new_shape)
[Output]:
[[37 11 56 18 42]
 [17 12 22 16 42]
 [47 29 17 47 35]
 [49 55 43 13 11]]

Tne new 2x10 array:
[[37 11 56 18 42 17 12 22 16 42]
 [47 29 17 47 35 49 55 43 13 11]]


Also we can convert a list to an array,

# Convert a list l=([2,4,6,8]) to a 1D array
# l is a list with [2,4,6,8] values.
l=([2,4,6,8])
print('  l= ',l)
# Convert it to a 1D array.
ar = np.array(l)
print('\n  Type of l:',type(l),', Type of ar:',type(ar))
print('  ar = ',ar)

[Output]:
l=  [2, 4, 6, 8] 
Type of: class'list'  , Type of ar: class 'numpy.ndarray'
ar =  [2 4 6 8]


If we want to add a value to all elements in the array, we just write:

# Adding 9 to each element in the array

 
print('ar:',ar)
ar = ar + 9
print('ar after adding 9:',ar)

[Output]:
ar:  [2 4 6 8]
ar after adding 9: [11 13 15 17]


:: numpy Commands::

Command Comments and Outputs
my_array = np.array([1,2,3,4,5]) Create an array with 1 to 5 integer
len(my_array) Get the array length
np.sum(my_array) get the sum of the elements in the array

my_array = np.array([1,2,3,4,5])
print(np.sum(my_array))
[Output]: 15
np.max(my_array) # Get the maximum number in the array
my_array = np.array([1, 2, 3,4,5])
max_num = np.max(my_array)
[Output]: 5
np.min(my_array) # Get the minimum number in the array
my_array = np.array([1, 2, 3,4,5])
min_num = np.min(my_array)
[Output]: 1
my_array = np.ones(5)
Output: [ 1., 1., 1., 1., 1.]
create array of 1s (of length 5)
np.ones(5)
Output: [ 1., 1., 1., 1., 1.]
m_array = np.arange(24)
print(m_array)
# To create an array with 23 number.
[ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23]
m_array = np.arange(2, 3, 0.1)
print(m_array)
# Create an array from 2 to 3 with 0.1 interval value increments.
[ 2. , 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9]
m_array = np.random.randint(10, size=(3,3))
print(m_array)
# Create a 3×3 array with random numbers between (0,10)
[[6 0 7]
[1 9 8]
[5 8 9]]
m_array = np.random.randint(10,60, size=(3,3)) # Create a 3×3 array with random numbers between (10,60)
[[11 23 50]
[36 44 18]
[56 24 30]]
# Create a 4×5 array with random numbers.
m_array = np.random.randint(10,60, size=(4,5))

# Reshape m_array from 4×5 to 2×10
new_shape = m_array.reshape(2,10)
print(m_array)
print(new_shape)

# m_array 4×5
[[37 11 56 18 42]
[17 12 22 16 42]
[47 29 17 47 35]
[49 55 43 13 11]]

# Tne new 2×10 array:
[[37 11 56 18 42 17 12 22 16 42]
[47 29 17 47 35 49 55 43 13 11]]

# convert a list to array:
l=[2,4,6,8]
ar = np.array(l)
# check data type for l and ar:
print(‘\n Type of l:’,type(l),’, Type of ar:’,type(ar))
[Output]:
l = [2, 4, 6, 8]
ar = [2, 4, 6, 8]
Type of l: class ‘list,’, Type of ar: class ‘numpy.ndarray’
# Adding 9 to each element in the array
ar = ar + 9
[11 13 15 17]


:: numpy Sessions ::

Sessions 1 Sessions 2 Sessions 3 Sessions 4




:: Some Code output ::

Create array with 24 numbers (0-23).
Reshape array to 4×6.
Create random array of numbers (0-10), size 3×3.
Reshape 4×5 array to 2×10.
Convert list to array.



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Python: Numpay – P1

November 7, 2019 3 comments


Learning : Python Numpy – P1
Subject: Numpay and some basic commands

In coming several posts I will talk about the numpay library and how to use some of its functions. So first what is numpy? Definition: NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. Also known as powerful package for scientific computing and data manipulation in python. As any library or package in python we need to install it on our device (we will not go through this process)

Basic commands in numpy: First of all we need to import it in our code. so we will use

  import numpy as np


To create a 1 dimensional array we can use verey easy way as:

  # create an array using numpy array function.
my_array = np.array([1, 2, 3,4,5])


Later we will create a random array of numbers in a range.

Now, to get the length of the array we can use len command as


len(my_array)
Output: 5


To get the sum of all elements in the array we use..

np.sum(my_array)


And to get the maximum and minimum numbers in the array we use ..

 # Get the maximum and minimum numbers in the array
my_array = np.array([1, 2, 3,4,5])
np.max(my_array)
[Output]: 5 

np.min(my_array)
[Output]: 1 


Some time we may need to create an array with certain Number of elements only one’s, to do this we can use this commands:

#create array of 1s (of length 5) 
np.ones(5)
Output: [ 1.,  1.,  1.,  1.,  1.]


The default data type will be float, if we want to change it we need to pass the the ‘dtype’ to the command like this :

#create array of 1s (of length 5) as integer: 
np.ones(5, dtype = np.int)
Output: [ 1,  1,  1,  1,  1]


Code output:



So far we work on a one dimensional array, in the next post we will cover some commands that will help us in the arrays with multiple dimensions.



:: numpy Commands::

Command comment
my_array = np.array([1,2,3,4,5]) Create an array with 1 to 5 integer
len(my_array) Get the array length
np.sum(my_array) get the sum of the elements in the array

my_array = np.array([1,2,3,4,5])
print(np.sum(my_array))
[Output]: 15
np.max(my_array) # Get the maximum number in the array
my_array = np.array([1, 2, 3,4,5])
max_num = np.max(my_array)
[Output]: 5
np.min(my_array) # Get the minimum number in the array
my_array = np.array([1, 2, 3,4,5])
min_num = np.min(my_array)
[Output]: 1
my_array = np.ones(5)
Output: [ 1., 1., 1., 1., 1.]
create array of 1s (of length 5)
np.ones(5)
Output: [ 1., 1., 1., 1., 1.]


:: numpy Sessions ::

Sessions 1 Sessions 2 Sessions 3 Sessions 4



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Python and Lindenmayer System – P3

November 5, 2019 Leave a comment


Learning : Lindenmayer System P3
Subject: Drawing Fractal Tree using Python L-System

In the first two parts of the L-System posts (Read Here: P1, P2) we talk and draw some geometric shapes and patterns. Here in this part 3 we will cover only the Fractal Tree and looking for other functions that we may write to add leaves and flowers on the tree.

Assuming that we have the Pattern generating function and l-system drawing function from part one, I will write the rules and attributes to draw the tree and see what we may get.
So, first tree will have:


# L-System Rule to draw ‘Fractal Tree’
# Rule: F: F[+F]F[-F]F
# Angle: 25
# Start With: F
# Iteration : 4


and the output will be this:


If we need to add some flowers on the tree, then we need to do two things, first one is to write a function to draw a flower, then we need to add a variable to our rule that will generate a flower position in the pattern. First let’s write a flower function. We will assume that we may want just to draw a small circles on the tree, or we may want to draw a full open flower, a simple flower will consist of 4 Petals and a Stamen, so our flower drawing function will draw 4 circles to present the Petals and one middle circle as the Stamen. We will give the function a variable to determine if we want to draw a full flower or just a circle, also the size and color of the flowers.

Here is the code ..

font = 516E92
commint = #8C8C8C

Header here
# Functin to draw Flower
def d_flower () :

if random.randint (1,1) == 1 :

# if full_flower = ‘y’ the function will draw a full flower,

# if full_flower = ‘n’ the function will draw only a circle

full_flower = ‘y’

t.penup()

x1 = t.xcor()

y1 = t.ycor()

f_size = 2

offset = 3

deg = 90

if full_flower == ‘y’ :

t.color(‘#FAB0F4’)

t.fillcolor(‘#FAB0F4’)

t.goto(x1,y1)

t.setheading(15)

for x in range (0,4) : # To draw a 4-Petals

t.pendown()

t.begin_fill()

t.circle(f_size)

t.end_fill()

t.penup()

t.right(deg)

t.forward(offset)

t.setheading(15)

t.goto(x1,y1 – offset * 2 + 2)

t.pendown() # To draw a white Stamen

t.color(‘#FFFFF’)

t.fillcolor(‘#FFFFFF’)

t.begin_fill()

t.circle(f_size)

t.end_fill()

t.penup()

else: # To draw a circle as close flower

t.pendown()

t.color(‘#FB392C’)

t.end_fill()

t.circle(f_size)

t.end_fill()

t.penup()

t.color(‘black’)

Then we need to add some code to our rule and we will use variable ‘o’ to draw the flowers, also I will add a random number selecting to generate the flowers density. Here is the code for it ..

In the code the random function will pick a number between (1-5) if it is a 3 then the flower will be drawn. More density make it (1-2), less density (1-20)

And here is the output if we run the l-System using this rule: Rule: F: F[+F]F[-F]Fo

Using the concepts, here is some samples with another Fractal Tree and flowers.

Another Fractal Tree without any Flowers.


Fractal Tree with closed Pink Flowers.


Fractal Tree with closed Red Flowers.


Fractal Tree with open pink Flowers.




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Python and Lindenmayer System – P2

November 3, 2019 1 comment


Learning : Lindenmayer System P2
Subject: Drawing with python using L-System

In the first part of Lindenmayer System L-System post (Click to Read) we had wrote two functions: one to generate the pattern based on the variables and roles, and one to draw lines and rotate based on the pattern we have.

In this part I will post images of what Art we can generate from L-System
the codes will be the L-system that generate the patterns, so the code will include: the Rules, Angle (Right, Left) Iteration and Starting Variable.


L-System: Koch Curve

L-System: Minkowski Sausage

L-System: … but here the Iteration is: 3

L-System: Again … but here the Iteration is: 3

L-System: Square Sierpinski

L-System: Sierpinski Arrowhead.

L-system: Dragon Curve

L-System: Koch Snowflake

L-System:

L-System:


The possibilities to generate the putters and therefore drawing the output is endless, any slightly changes in the iterations or rotation (+ -) angles will take all output to a new levels. In the coming post, I will use the L-system to generate fractal tree and see what we can get from there.



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Python and Lindenmayer System – P1

October 31, 2019 1 comment


Learning : Lindenmayer System P1
Subject: Drawing with python using L-System

First What is Lindenmayer System or L-System? L-System is a system consists of an alphabet of symbols (A, B, C ..) that can be used to make strings, and a collection of rules that expand each symbol into larger string of symbols.

L-system structure: We can put it as Variables, Constants, Axiom, Rules

Variables (V): A, B, C …
constants : We define a symbols that present some movements, such as ‘+’ mean rotate right x degree, ‘F’ mean move forward and so on ..
Axiom : Axiom or Initiator is a string of symbols from Variable (V ) defining the initial state of the system.
Rules : Defining the way variables can be replaced with combinations of constants and other variables.

Sample:
Variables : A, B {we have two variables A and B}
Constants : none
Axiom : A {Start from A}
Rules : (A → AB), (B → A) {convert A to AB, and convert B to A}

So if we start running the Nx is the number the time we run the rules (Iteration).
N0 : A
N1 : AB
N2 : AB A
N3 : AB A AB
N4 : AB A AB AB A
N5 : AB A AB A AB A AB .. an so-on
So in this example after 5 Iteration we will have this pattern (AB A AB A AB A AB)

In this post we will write two functions, one to generate the pattern based on the Variables and Rules we have. Another function to draw the pattern using Python Turtle and based on the Constants we have within the patterns.

The constants that we may use and they are often used as standard are:

F means “Move forward and draw line”.
f means “Move forward Don’t draw line”.
+ means “turn left by ang_L°”.
− means “turn right ang_R°”.
[ means “save position and angle”.
] means “pop position and angle”.
X means “Do nothing”

and sometime you may add your own symbols and and rules.

First Function: Generate the Pattern will take the Axiom (Start symbol) and apply the rules that we have (as our AB sample above). The tricky point here is that the function is changing with each example, so nothing fixed here. In the coming code i am using only one variable F mean (move forward) and + – to left and right rotations. Other patterns may include more variables. once we finished the function will return the new string list.

Generate the Pattern

# Generate the patern
def l_system(s) :

new_s = []

for each in s :

if each == ‘F’:

new_s.append(‘F+F+FF-F’)

else :

new_s.append(each)

return new_s



The second function: Draw the Pattern will take the string we have and draw it based on the commands and rules we have such as if it read ‘F’ then it will move forward and draw line, and if it reads ‘-‘ then it “turn right ang_R°”.
here is the code ..

Draw the Pattern
def draw_l_system(x,y,s,b,ang_L,ang_R):

cp = [] # Current position

t.goto(x,y)

t.setheading(90)

t.pendown()

for each in s:

if each == ‘F’ :

t.forward(b)

if each == ‘f’ :

t.penup()

t.forward(b)

t.pendown()

elif each == ‘+’:

t.left(ang_L)

elif each == ‘-‘:

t.right(ang_R)

elif each == ‘[‘:

cp.append((t.heading(),t.pos()))

elif each == ‘]’:

heading, position = cp.pop()

t.penup()

t.goto(position)

t.setheading(heading)

t.pendown()

t.penup()


Now we will just see a one example of what we may get out from all this, and in the next post P2, we will do more sample of drawing using L-System.


In the image bellow, left side showing the Rules, angles and iterations and on the right side the output after drawing the patters.

Python: Date Validation Function

October 29, 2019 Leave a comment


Learning : Date Validation Function
Subject: Dll’s and Function

In late of 90’s, I start writing DLL files, Dll file or Dynamic Link Library is a file that contain instructions or function that can be used and reused with/by other applications. So if we have a function that we keep using it in most of our programs then we write it in a dll file and re-call it any time we want to.

Writing a function that can be added to a Dll file and will be used by all the team is not a simple as it appeared to be, Dll files often contains more than one functions so we may find ten or twenty functions in there most are related so a DLL file need to be a very well documented and each function has it’s own comments, variables, version number and summary of its task and what it will return back.

In this post we will write Python code for a date validation function, the function will take one argument and will return values as :
1. Function will return False and error message if the passed argument is not a valid date.
2. Function will return True and the date if the date is valid.

Date Validation Function:

# Date validation function
# Variables: This function will take one argument as a user input date.
# Returns: This dunction will return Fals and error_message each itme the user enter a not valid date.
# The functin will return True and the date in case it was correnct.
# The function will returns value as a list.

def valid_date(my_date):

# get the separator

the_separator = []

for each in my_date :

if not each.isdigit():

the_separator.append(each)

# If the user inter other that two separators then the date is invalid.

if len (the_separator) != 2 or (the_separator[0] != the_separator[1]):

error_message = “Date is not valid.”

return False, error_message

d,m,y = (my_date.split(the_separator[0]))

if not d.isdigit() or (int(d) > 31 or int(d) < 1 ):

error_message = ‘Day must be number and between (1-31).’

return False, error_message

if not m.isdigit() or (int(m) > 12 or int(m) < 1 ) :

error_message= ‘Mounth must be number and between (1-12).’

return False, error_message

if not y.isdigit() or len(y) != 4 or int(y) < 1:

error_message = ‘Year must be a 4-digit positive number. ‘

return False, error_message

# convert the days and month to two digits numbers

if len(d) == 1: d =’0′ + d

if len(m) == 1: m =’0′ + m

my_date = d + ‘/’ + m + ‘/’ + y

return True, my_date


So now if we want to call the function and pass the user input to it then examine the returns, we may use the While loop as here..


vd=[False,0]

while vd[0] == False :

my_date = input(‘\n Enter the date as dd/mm/yyyy :’)

vd = valid_date(my_date)

if not vd[0] : print(‘ ‘,vd[1])

print(“\n we have a valid date, it is .. “, vd[1])


… Have fun …



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Python: Drawing Shapes

October 27, 2019 Leave a comment


Learning : Drawing Shapes
Subject: New shapes function

To Draw a Square shape, we need to know the width ( W ) of the square side, and then we draw a line and moving in 90 degree and drawing another line and so on until we finished the 4 side of the square. In the same principle if we want to draw a triangle (equilateral one), we need to know length of its sides and in mathematics we know that in equilateral triangles the angles (corners) are 120 degree, so we draw a line and move in 120 degree and drawing another two sides.

In coming code, we will write a general function in Python to pass the number on sides we want to draw (triangle =3, Square=4,Pentagon = 5, Hexagon =6 .. and so on), the width (size) of the shape and the position (x,y) of the first angle or point.

The Codes:

def d_shape(s_heads,w,x1,y1):

t.goto(x1,y1)

# To get t.right angle

rang = 360 / s_heads

t.pendown()

for x in range (s_heads +1) :

t.forward(w)

t.right(-rang)

t.penup()



Results after using the new function we can pass any number of sides and the function will draw the shape, here are a sample execution of it. .. .. Click to enlarge ..




Now if we call the function number of times equal to it’s heads what we will get ? let’s see . .. Click to enlarge ..


And take a look when we set the numbers to 20. .. Click to enlarge ..



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