Introduction to programmation using the Python language

Introduction to programmation using thePython language

Rémi MarchalInorganic Theoretical Chemistry group, ISCR, Rennes

remi.marchal@univ-rennes1.frJanuary, 28th 2019

First hints

IntroductionHistoryWhat is python ?Why learning and using Python ?Some basic rules

VariablesWhat is it ?How ?Variable types

FunctionsWhat is it ?Some functions

ModulesWhat is it ?Import modules

Outline

1. Introduction

2. Variables

3. Functions

4. Modules

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Outline

1. Introduction

2. Variables

3. Functions

4. Modules

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Outline

1. Introduction1.1 History1.2 What is python ?1.3 Why learning and using Python ?1.4 Some basic rules

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A bit of history

1991 : Guido Van Rossum starts to developthe Python programming language.2001 : Creation of the Python SoftwareFoundation, a non-profit organization aimingat foster development of the Pythoncommunity.2009 : Creation of Python3.

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Outline

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What is python ?

Quesaco ?

▶ Python is an Object-oriented language. Is allowsyou to create and manipulate easily some objects

▶ It is an interpreted language, so no compilationneeded

First hints

What is python ?

Quesaco ?▶ Python is an Object-oriented language. Is allows

you to create and manipulate easily some objects

▶ It is an interpreted language, so no compilationneeded

First hints

What is python ?

Quesaco ?▶ Python is an Object-oriented language. Is allows

you to create and manipulate easily some objects▶ It is an interpreted language, so no compilation

needed

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Outline

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Why Python ?

AdvantagesThere is several advantages in using Python

▶ Strong developer community so a lot of librariesready to be used

▶ A large user community so a lot of forum andtutorial available on the web

▶ Several graphical libraries available

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Why Python ?

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Why Python ?

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Why Python ?

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2 ways to write program in python

Through the interpreter

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Through a script

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Which way to choose ?

It depends what you want to do.▶ If you just want to do a quite small calculation,

you should use the interpreter▶ If you want to write a quite long program, use the

script▶ If you want to write a program and execute it

several times, use the script

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Which way to choose ?It depends what you want to do.

▶ If you just want to do a quite small calculation,you should use the interpreter

▶ If you want to write a quite long program, use thescript

▶ If you want to write a program and execute itseveral times, use the script

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Outline

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Basics rules

What to avoid ?When writing a program in python, there is somebasics rules that you should follow :

▶ Take care about the indentation▶ Avoid infinite loops▶ THINK BEFORE CODING

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Outline

1. Introduction

2. Variables

3. Functions

4. Modules

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Outline

2. Variables2.1 What is a variable ?2.2 How to define variables and to use it ?2.3 The different types of variables

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What is a variable and why to use it ?

What is a variable ?

▶ A variable is a little place in the Memory of ourprogram and of your computer where you codeshould be able to store data.You can model your computer as a cabinet with alot of drawer, each of them able to store avariable. When you need to access a variable, youjust need to open the proper drawer

▶ Indeed, it is great to be able to make somemathematical operation but if you are not able tostore the result somewhere it is useless.

So no way to write a code without variables

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What is a variable ?▶ A variable is a little place in the Memory of our

program and of your computer where you codeshould be able to store data.You can model your computer as a cabinet with alot of drawer, each of them able to store avariable. When you need to access a variable, youjust need to open the proper drawer

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Outline

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How to create and use variables in Python ?

How to create a variable and address a value ?

In the Python language, it is something extremelysimple to do.Indeed, you just have to write something like this :variable_name=value

ExampleLet assume that you want to create a variable namednb in which you want to store the value 5. Thus, youjust have to write this :nb=5

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How to create a variable and address a value ?In the Python language, it is something extremelysimple to do.

Indeed, you just have to write something like this :variable_name=value

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How to create a variable and address a value ?In the Python language, it is something extremelysimple to do.Indeed, you just have to write something like this :variable_name=value

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How to create a variable and address a value ?In the Python language, it is something extremelysimple to do.Indeed, you just have to write something like this :variable_name=value

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Outline

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The different types of variables

Variable typesBasically, there is 3 main type of variables :

▶ The integer (int in Python)▶ The floating ponts (float in Python)▶ The string (str in Python)

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Outline

1. Introduction

2. Variables

3. Functions

4. Modules

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Outline

3. Functions3.1 What is it ?3.2 Some useful intrinsic Python functions

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What is a function ?A function is a group of instruction that allows you toachieve specific tasks.To call them you just have to use the followingsyntax :name_of_the_function(parameters)It exists several intrinsic functions in Python, some ofthem discussed below.

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Outline

3. Functions3.1 What is it ?3.2 Some useful intrinsic Python functions

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The print function

printThis function allows you to display either some text orthe value of a variable on the screen.The syntax of this function is the following :print(what_you_want_to_print)

Example

Python scripta=5.3b=1.2c=a+bprint(a,’+’,b,’=’,c)

Result5.3 + 1.2 = 6.5

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The print function

Example

Result5.3 + 1.2 = 6.5

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The print function

Example

Result5.3 + 1.2 = 6.5

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The type function

typeThis function returns the type of a variable.Its syntax is :type(nom_of_the_variable)

Example

Python scriptstring=’text’floating=4.5integer=4print(type(string))print(type(floating))print(type(integer))

Result<class ’str’><class ’float’><class ’int’>

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The type function

Example

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The type function

Example

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variable type conversions

Convert a variable to floating pointThis can be done using the float() Python function.

Example

Python scriptinteger=4string=’5’floating=float(integer)print(floating)floating=float(string)print(floating)

Result4.05.0

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Example

Result4.05.0

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Example

Result4.05.0

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Convert a variable to an integerThis can be done using the int() Python function.

Example

Python scriptfloating=4.9string=’5’integer=int(floating)print(integer)integer=int(string)print(floating)

Result45

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Example

Result45

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Example

Result45

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Convert a variable to a stringThis can be done using the str() Python function.

Example

Python scriptfloating=4.9integer=5string=str(floating)print(string)string=str(integer)print(string)

Result4.95

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Example

Result4.95

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Example

Result4.95

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Store keyboard entries into a variable

keyboard entryThis can be done using the input() Python function.ATTENTION : this keyboard entry will beinterpreted as a string

Example

Python scripta=input(”enter a value”)

a=float(a)print(”a square= ”,a**2)

Resultenter a value 2.5

a square= 6.25

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Example

a square= 6.25

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Example

a square= 6.25

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Example

Python scripta=input(”enter a value”)a=float(a)print(”a square= ”,a**2)

a square= 6.25

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Example

Python scripta=input(”enter a value”)a=float(a)print(”a square= ”,a**2)

Resultenter a value 2.5a square= 6.25

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Outline

1. Introduction

2. Variables

3. Functions

4. Modules

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Outline

4. Modules4.1 What is it ?4.2 Import modules

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What is a module ?

Definition of a moduleA module is basically a piece of code that have beenencapsulated in a file. The variables and functions thatare related to this module are also encapsulated in thefile.Thus, one have just to call the module in order to useits functionalities.

Why to use modules ?There is a lot of different modules that have beendeveloped in Python and it is quite easy to install anduse them.

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Outline

4. Modules4.1 What is it ?4.2 Import modules

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How to import modules ?

Various methodsIt exists basically 3 ways to import modules1. The basic import method2. Import a module and rename it3. The partial import method

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The basic import methodTo import a module, you can use the following syntaxin your python script :import module_nameUsing this method, all the functions included in themodule are imported. To use one of them, you have touse the following syntax :module_name.function_name

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The basic import method : ExampleLets try to compute the exponential of 0.0. Theexponential function is included in the math module.

Python scripta=0.0res=exp(a)

import mathres=math.exp(a)print(res)

ResultTraceback (most recentcall last) :File ”t.py”, line 2, in<module>res=exp(a)NameError : name ’exp’is not defined

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Python scripta=0.0res=exp(a)import mathres=math.exp(a)print(res)

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Python scripta=0.0res=exp(a)import mathres=math.exp(a)print(res)

ResultTraceback (most recentcall last) :File ”t.py”, line 2, in<module>res=exp(a)NameError : name ’exp’is not defined1.0

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Import a module and rename itThis method is more or less the same as the basicmethod. However, you can change the name of themodule using the following syntaximport module_name as new_name

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Import a module and rename it : ExampleLets try to compute the exponential of 0.0. Theexponential function is included in the math module.

Python scriptimport math as maa=0.0res=ma.exp(a)print(res)

Result1.0

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Result1.0

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Result1.0

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The partial import methodInstead of importing the whole module, you canimport only a specific function of it using the followingsyntax :from module_name import function_nameFor example, if you only need the exp function of themath module, you can do :from math import exp

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The partial import method : ExampleLets try to compute the exponential of 0.0. Theexponential function is included in the math module.

Python scriptfrom math import expa=0.0res=exp(a)print(res)

Result1.0

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Result1.0

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Result1.0

Conditional statements and loops

Conditions and loops

Conditional StatementsWhat is it ?IndentationThe various conditional statements

LoopsWhat is it ?Repeating loopConditional loopStop a loop

Outline

1. Conditional Statements

2. Loops

Outline

1. Conditional Statements1.1 What is it ?1.2 Indentation1.3 The various conditional statements

What is conditional statements ?

DefinitionConditional statements is something widely used.Indeed, it allows you to execute a part of the codeonly under specific conditions

Conditional operatorssymbol signification< Strictly inferior> Strictly superior⩽ Inferior or equal⩾ Superior or equal== equal!= different

What is conditional statements ?

DefinitionConditional statements is something widely used.Indeed, it allows you to execute a part of the codeonly under specific conditions

Conditional operatorssymbol signification< Strictly inferior> Strictly superior⩽ Inferior or equal⩾ Superior or equal== equal!= different

Outline

Indentation

What is indentation ?After writing your conditional statement, one shouldintroduce spaces at the beginning of each line in thepart of the code that should be executed if thecondition is fulfill. This amount of space should be thesame for each linesThis is what we call indentation.

Example with algorithma=3b=2If a > b

write a is higher than bwrite b is lower than a

Here, the last 2 lines have been indented (addingspace at the beginning)

Indentation

What is indentation ?After writing your conditional statement, one shouldintroduce spaces at the beginning of each line in thepart of the code that should be executed if thecondition is fulfill. This amount of space should be thesame for each linesThis is what we call indentation.

Example with algorithma=3b=2If a > b

write a is higher than bwrite b is lower than a

Here, the last 2 lines have been indented (addingspace at the beginning)

Outline

The minimal conditional statement (if )

The simple if statementThis allows you to execute some instructions only if acondition if fulfill.The syntax is the following :if condition :

What to do if the condition is fulfill

Python scripta=4.2if a>0 :

print(”a is positive”)

Resulta is positive

The complete conditional (if, elif, else)

The complete conditional statementThis allows you to execute some instructions only if acondition if fulfill and another part if the condition isnot fulfill .The syntax is the following :if condition :

What to do if the condition is fulfillelse :

What to do if the condition is not fulfillIt is also possible to introduce other conditions usingelif.

Example

print(”a is positive”)elif a==0 :

print(”a is zero”)else :

print(”a is negative”)

Resulta is positive

Example

print(”a is positive”)elif a==0 :

print(”a is zero”)else :

print(”a is negative”)

Resulta is positive

Outline

1. Conditional Statements

2. Loops

Outline

2. Loops2.1 What is it ?2.2 Repeating loop2.3 Conditional loop2.4 Stop a loop

What is a loop ?

Definition of a loopLoop is an highly important concept in programming.Indded, it allows you to repeat some operations agiven amount of time.

Loop typesIt exists 2 main type of loops :1. Repeating loops2. Conditional loops

What is a loop ?

Definition of a loopLoop is an highly important concept in programming.Indded, it allows you to repeat some operations agiven amount of time.

Loop typesIt exists 2 main type of loops :1. Repeating loops2. Conditional loops

Outline

Repeating loops

Why and how ?This kind of loop is what I will call the classical one.It allows you to repeat given operations from a startingvalue to an end value with specific increments.The syntax is the following :for i in range(starting_i,last_i,increment) :

What to repeatThe last value of a loop is exclusive (will not be used).If you don’t specify the value for the increment, it willuse the default one which is 1.ATTENTION : Don’t forget the indentation

Repeating loops

Repeating loops : First example

Python scriptfor i in range(0,6) :

print(i)

Result012345

Repeating loops : Second example

Python scriptfor i in range(0,6,2) :

print(i)

Result024

Repeating loops

print(i)

Result012345

print(i)

Result024

Repeating loops

print(i)

Result012345

print(i)

Result024

Repeating loops

print(i)

Result012345

print(i)

Result024

Outline

Conditional loops

The while loopThe aim of this loop is to repeat a part of the codeuntil a given condition is fulfill.The syntax is the following :while condition :

What_to_doATTENTION : If the condition is never fulfill,you will end up with an infinite loop and theprogram will never stop

Conditional loops : example

Python scripta=0while a<4 :

print(i)a=a+1

Result0123

Conditional loops

print(i)a=a+1

Result0123

Conditional loops

print(i)a=a+1

Result0123

Outline

Stop a loop

The break statementThis statement aims at stopping a loop.The syntax is the following (assuming you are inside aloop) :break

break : example

print(i)if i>10 :

Result024681012

Stop a loop

break : example

print(i)if i>10 :

Result024681012

Stop a loop

break : example

print(i)if i>10 :

Result024681012

The notion of lists in Python

Introduction

Define a list

Some rules about lists

Create a listCreate a list with predefined valuesCreate an empty list

Adding elements to a listAt the end of a listInsert an element at a specific positionList concatenationRemove an elementBrowse a list

Outline

1. Introduction

2. Define a list

3. Some rules about lists

4. Create a list

5. Adding elements to a list

Introduction

Define a list

What is a list ?

DefinitionLists in Python is something essential. Indeed, they areused to store several data in the same variable. Thisvariable is then called a list and contains severalelements, each of them characterized by a list-index.It is also possible to create list of lists.

Introduction

Define a list

Outline

1. Introduction

2. Define a list

4. Create a list

Introduction

Define a list

How a define a list ?

SyntaxThere is 2 ways to define an empty list :

▶ Either using the syntax :variable=list()▶ Or this one : variable=[ ]

Introduction

Define a list

Outline

1. Introduction

2. Define a list

4. Create a list

Introduction

Define a list

List Rules

Rules1. The first index of a list is always 02. A given element of a list should be called with ”[

]”. For example, if you want to access the 2nd

element of a list called list1, you should call it likethis : list1[1] (remember, the index of the firstelement is 0)

3. Don’t try to make additions directly of 2 lists(don’t write list3=list2+list1). If you want to doit, it is safer to make additions elements byelements

4. You can easily know the size (number ofelements) of a list using the len statement (forexample, len(list1) will render the number ofelements of the list list1)

Introduction

Define a list

Outline

1. Introduction

2. Define a list

4. Create a list

Introduction

Define a list

Outline

4. Create a list4.1 Create a list with predefined values4.2 Create an empty list

Introduction

Define a list

create a list with predefined values

How to do it ?To create a list from an already known set of values,the syntax is the following :list_name=[values_seperated_by_commas]

Example

Python scriptlist1=[0.1,0.2,0.3]print(list1)

Result[0.1,0.2,0.3]

Introduction

Define a list

Example

Result[0.1,0.2,0.3]

Introduction

Define a list

Example

Result[0.1,0.2,0.3]

Introduction

Define a list

Outline

4. Create a list4.1 Create a list with predefined values4.2 Create an empty list

Introduction

Define a list

create an empty list

How to do it ?To create an empty list, the widely used syntax is thefollowing :list_name=[ ]

Example

Python scriptlist1=[ ]print(list1)

Result[ ]

Introduction

Define a list

Example

Result[ ]

Introduction

Define a list

Example

Result[ ]

Introduction

Define a list

Outline

1. Introduction

2. Define a list

4. Create a list

Introduction

Define a list

Outline

5. Adding elements to a list5.1 At the end of a list5.2 Insert an element at a specific position5.3 List concatenation5.4 Remove an element5.5 Browse a list

Introduction

Define a list

Adding elements at the end of a list

How to do it ?This can be done by appending an existing list. Thesyntax is the following :list_name.append(new_value_to_add_at_the_end)

Example

Python scriptlist1=[ ]for i in range(0,4) :

list1.append(i)print(list1)

list1.append(4)print(list1)

Result[0,1,2,3]

[0,1,2,3,4]

Introduction

Define a list

Example

Result[0,1,2,3]

[0,1,2,3,4]

Introduction

Define a list

Example

Result[0,1,2,3]

[0,1,2,3,4]

Introduction

Define a list

Example

list1.append(i)print(list1)list1.append(4)print(list1)

Result[0,1,2,3]

[0,1,2,3,4]

Introduction

Define a list

Example

list1.append(i)print(list1)list1.append(4)print(list1)

Result[0,1,2,3][0,1,2,3,4]

Introduction

Define a list

Outline

Introduction

Define a list

Insert an element at a given position in thelist

How to do it ?To do it, one should use the insert function. Thesyntax is the following :list_name.insert(position,value)

Example

Python scripta=[0,1,2,4]print(a)

a.insert(3,3.0)print(a)

Result[0,1,2,4]

[0,1,2,3.0,4]

Introduction

Define a list

Example

Result[0,1,2,4]

[0,1,2,3.0,4]

Introduction

Define a list

Example

Result[0,1,2,4]

[0,1,2,3.0,4]

Introduction

Define a list

Example

Python scripta=[0,1,2,4]print(a)a.insert(3,3.0)print(a)

Result[0,1,2,4]

[0,1,2,3.0,4]

Introduction

Define a list

Example

Python scripta=[0,1,2,4]print(a)a.insert(3,3.0)print(a)

Result[0,1,2,4][0,1,2,3.0,4]

Introduction

Define a list

Outline

Introduction

Define a list

List concatenation

How to do it ?There is 3 ways to it :1. The extend method :

list1.extend(list2)2. The ”+” method :

list1=list1+list23. The ”+=” method :

list1+=list2

Example extend method

Python scriptlist1=[0,1,2,3]list2=[4,5,6,7]list1.extend(list2)print(list1)

Result[0,1,2,3,4,5,6,7]

Introduction

Define a list

List concatenation

list1+=list2

Result[0,1,2,3,4,5,6,7]

Introduction

Define a list

List concatenation

list1+=list2

Result[0,1,2,3,4,5,6,7]

Introduction

Define a list

List concatenation

list1+=list2

Example ”+” method

Python scriptlist1=[0,1,2,3]list2=[4,5,6,7]list3=list1+list2print(list3)

Result[0,1,2,3,4,5,6,7]

Introduction

Define a list

List concatenation

list1+=list2

Result[0,1,2,3,4,5,6,7]

Introduction

Define a list

List concatenation

list1+=list2

Result[0,1,2,3,4,5,6,7]

Introduction

Define a list

List concatenation

list1+=list2

Example ”+=” method

Python scriptlist1=[0,1,2,3]list2=[4,5,6,7]list1+=listt2print(list1)

Result[0,1,2,3,4,5,6,7]

Introduction

Define a list

List concatenation

list1+=list2

Result[0,1,2,3,4,5,6,7]

Introduction

Define a list

List concatenation

list1+=list2

Result[0,1,2,3,4,5,6,7]

Introduction

Define a list

Outline

Introduction

Define a list

Remove an element of a list

How to do it ?There is 2 ways to it depending if you want to removean index or a value :

▶ If you want to remove an index :del list_name[index_to_remove]

▶ If you want to remove a value :list_name.remove(value_to_remove)It will only remove the value one time if itappears several times in the list.

Introduction

Define a list

Example with del

Python scriptlist1=[0,1,2,3,1]list1.del[2]print(list1)

Result[0,1,3,1]

Example with remove

Python scriptlist1=[0,1,2,3,1]list1.remove(1)print(list1)

Result[0,2,3,1]

Introduction

Define a list

Example with del

Result[0,1,3,1]

Example with remove

Result[0,2,3,1]

Introduction

Define a list

Example with del

Result[0,1,3,1]

Example with remove

Result[0,2,3,1]

Introduction

Define a list

Example with del

Result[0,1,3,1]

Example with remove

Result[0,2,3,1]

Introduction

Define a list

Example with del

Result[0,1,3,1]

Example with remove

Result[0,2,3,1]

Introduction

Define a list

Outline

Introduction

Define a list

Browse a list

How to do it ?There is 2 ways to it :

▶ Using a loop starting from index 0 to the size ofthe list

▶ Using a loop over all the list elements

Example : index loop

Python scriptlist1=[0,1,2]for i in range(0,len(list1)) :

print(list1[i])

Result012

Introduction

Define a list

Browse a list

print(list1[i])

Result012

Introduction

Define a list

Browse a list

print(list1[i])

Result012

Introduction

Define a list

Browse a list

Example : loop over list elements

Python scriptlist1=[0,1,2]for i in list1 :

print(list1[i])

Result012

Introduction

Define a list

Browse a list

print(list1[i])

Result012

Introduction

Define a list

Browse a list

print(list1[i])

Result012

Reading and writing files

Read and write

Reading filesIntroductionGeneral philosophyOne method

Writing in a file

Outline

1. Reading files

2. Writing in a file

Read and write

Writing in a file

Outline

1. Reading files1.1 Introduction1.2 General philosophy1.3 One method for reading files

Read and write

Writing in a file

Why to read files ?

▶ It is an extremely important concept in scientificprogramming

▶ Indeed, most of our calculation need input dataand it’s easier to read them from input files

▶ It is also of prime importance if you aim atpost-treatment program development

Read and write

Writing in a file

Why to read files ?

Why ?▶ It is an extremely important concept in scientific

programming

▶ Indeed, most of our calculation need input dataand it’s easier to read them from input files

Read and write

Writing in a file

Why to read files ?

programming▶ Indeed, most of our calculation need input data

and it’s easier to read them from input files

Read and write

Writing in a file

Why to read files ?

programming▶ Indeed, most of our calculation need input data

and it’s easier to read them from input files▶ It is also of prime importance if you aim at

post-treatment program development

Read and write

Writing in a file

Introduction

Advantages in Python

▶ Despite Python is an interpreted language andthus slower than compiled languages such as C orFortran, one of the main advantage of usingPython is that it’s quite easy to open and readfiles with it.

▶ Indeed, this task is quite difficult in Fortran and C▶ That’s why most of the post-treatment program

are written in both Python (for data extraction)and Fortran or C (for the calculation part).

Read and write

Writing in a file

Introduction

Advantages in Python▶ Despite Python is an interpreted language and

thus slower than compiled languages such as C orFortran, one of the main advantage of usingPython is that it’s quite easy to open and readfiles with it.

Read and write

Writing in a file

Introduction

▶ Indeed, this task is quite difficult in Fortran and C

▶ That’s why most of the post-treatment programare written in both Python (for data extraction)and Fortran or C (for the calculation part).

Read and write

Writing in a file

Introduction

Read and write

Writing in a file

Outline

Read and write

Writing in a file

Reading file in Python

Main idea▶ The idea is to browse an entire file and to store

its contains in a list, each of the list elementsbeing either a word or a line.

▶ This list will be then browsed in order to extractonly the informations that are relevant for theneeded calculation.

An essential ruleAttention : Whatever the method used, reading a filewill lead to string variable. Thus, one should notforget to convert them to integers or floating pointsbefore doing any calculation.

Read and write

Writing in a file

Read and write

Writing in a file

Read and write

Writing in a file

Read and write

Writing in a file

Outline

Read and write

Writing in a file

The open method

What is it ?This method for reading files is based on the openintrinsic Python function.

Read and write

Writing in a file

The open method : How ?

The modus operandi

1. Apply the function open with its readlinesfunctionality to a file

2. Store the result in a list.

Read and write

Writing in a file

The modus operandi1. Apply the function open with its readlines

functionality to a file

2. Store the result in a list.

Read and write

Writing in a file

The modus operandi1. Apply the function open with its readlines

functionality to a file2. Store the result in a list.

Read and write

Writing in a file

First example

The ”test” file1 2 3 4 56 7 8 9 1011 12 13 14

First example

Python scriptf=open(”test”).readlines()print(f)

Result[1 2 3 4 5 \n,6 7 89 10 \n, 11 12 1314]

Thus, each of the list element are lines. So howto create lists with only words and not lines.

Read and write

Writing in a file

First example

The ”test” file1 2 3 4 56 7 8 9 1011 12 13 14

First example

Result[1 2 3 4 5 \n,6 7 89 10 \n, 11 12 1314]

Read and write

Writing in a file

First example

The ”test” file1 2 3 4 56 7 8 9 1011 12 13 14

First example

Result[1 2 3 4 5 \n,6 7 89 10 \n, 11 12 1314]

Read and write

Writing in a file

First example

The ”test” file1 2 3 4 56 7 8 9 1011 12 13 14

First example

Result[1 2 3 4 5 \n,6 7 89 10 \n, 11 12 1314]

Read and write

Writing in a file

Splitting lines into words

the str.split methodWe would like now to read a file and store it as a listof lists, each of the lists being a line and each of thelists elements words.For this, we can use the str.split functionality.

Read and write

Writing in a file

str.split example

The ”test” file1 2 3 4 56 7 8 9 1011 12 13 14

str.split example

Python scriptl1=[ ]f=open(”test”).readlines()# browse each linefor i in range(0,len(f)) :

l2=[ ]# browse each word of the line

for j in range(0,len(str.split(f[i]))) :l2.append(str.split(f[i])[j])

l1.append(l2)

Result[[1,2,3,4,5],[6,7,8,9,10],[11,12,13,14]]

Read and write

Writing in a file

str.split example

The ”test” file1 2 3 4 56 7 8 9 1011 12 13 14

str.split example

l1.append(l2)

Result[[1,2,3,4,5],[6,7,8,9,10],[11,12,13,14]]

Read and write

Writing in a file

str.split example

The ”test” file1 2 3 4 56 7 8 9 1011 12 13 14

str.split example

l1.append(l2)

Result[[1,2,3,4,5],[6,7,8,9,10],[11,12,13,14]]

Read and write

Writing in a file

Outline

1. Reading files

2. Writing in a file

Read and write

Writing in a file

How ?This is based on the use of the intrinsic write Pythonfunction

line breakThis is done by writing : ’\n’

Read and write

Writing in a file

modus operandi

1. Call the open function on a new file and the ”w”format

2. Write inside everything you want using thefunctionality write

3. Close the file with the functionality close

Read and write

Writing in a file

modus operandi1. Call the open function on a new file and the ”w”

format

2. Write inside everything you want using thefunctionality write

Read and write

Writing in a file

format2. Write inside everything you want using the

functionality write

Read and write

Writing in a file

format2. Write inside everything you want using the

functionality write3. Close the file with the functionality close

Read and write

Writing in a file

Writing files : Example

First example

Python scripta=[[First,line],[Second,line]]f=open(”test”,”w”)for i in range(0,len(a)) :

for j in range(0,len(a[i]) :f.write(a[i][j])

f.write(”\n”)f.close()

File ”test”First lineSecond line

Read and write

Writing in a file

First example

Read and write

Writing in a file

First example

The Numpy module

Présentation

Trigonometric functions

MatricesCreate Matrices and vectorsScalar productMatrices productTranspose matrixMatrix determinantMatrix inversion

Equation systemLinear equation systemMatrix diagonalization

Outline

1. Présentation

2. Trigonometric functions

3. Matrices

4. Solve Equation system

The Numpy module

Présentation

The Numpy module : Presentation

What is it ?This module allows you to

▶ Use trigonometric functions▶ Make some calculations on matrices▶ Solve equations systems

The Numpy module

Présentation

Outline

1. Présentation

3. Matrices

The Numpy module

Présentation

Numpy : Trigonometric functions

Which of them ?▶ Cosine (numpy.cos) et Arccos (numpy.arccos)▶ Sinus (numpy.sin) et Arcsin (numpy.arcsin)▶ Tangent (numpy.tan) et Arctan (numpy.arctan)

Attention : These functions are all in radian (It existthe function numpy.pi for the pi number)

The Numpy module

Présentation

The Numpy module

Présentation

The Numpy module

Présentation

Example

Python scriptimport numpy as npa=0.0b=np.pi/2.0c=np.pi/3.0print(a,b,c)

cosa=np.cos(a)cosb=np.cos(b)cosc=np.cos(c)print(np.arccos(cosa))print(np.arccos(cosb))print(np.arccos(cosc))

Result0.0 1.57 1.04

1.0 6.12e-17 0.500.01.5701.04

The Numpy module

Présentation

Example

Result0.0 1.57 1.04

1.0 6.12e-17 0.500.01.5701.04

The Numpy module

Présentation

Example

Result0.0 1.57 1.04

1.0 6.12e-17 0.500.01.5701.04

The Numpy module

Présentation

Example

Python scriptimport numpy as npa=0.0b=np.pi/2.0c=np.pi/3.0print(a,b,c)cosa=np.cos(a)cosb=np.cos(b)cosc=np.cos(c)

print(np.arccos(cosa))print(np.arccos(cosb))print(np.arccos(cosc))

Result0.0 1.57 1.04

1.0 6.12e-17 0.500.01.5701.04

The Numpy module

Présentation

Example

Python scriptimport numpy as npa=0.0b=np.pi/2.0c=np.pi/3.0print(a,b,c)cosa=np.cos(a)cosb=np.cos(b)cosc=np.cos(c)

print(np.arccos(cosa))print(np.arccos(cosb))print(np.arccos(cosc))

Result0.0 1.57 1.041.0 6.12e-17 0.50

0.01.5701.04

The Numpy module

Présentation

Example

Python scriptimport numpy as npa=0.0b=np.pi/2.0c=np.pi/3.0print(a,b,c)cosa=np.cos(a)cosb=np.cos(b)cosc=np.cos(c)print(np.arccos(cosa))print(np.arccos(cosb))print(np.arccos(cosc))

Result0.0 1.57 1.041.0 6.12e-17 0.50

0.01.5701.04

The Numpy module

Présentation

Example

Python scriptimport numpy as npa=0.0b=np.pi/2.0c=np.pi/3.0print(a,b,c)cosa=np.cos(a)cosb=np.cos(b)cosc=np.cos(c)print(np.arccos(cosa))print(np.arccos(cosb))print(np.arccos(cosc))

Result0.0 1.57 1.041.0 6.12e-17 0.500.01.5701.04

The Numpy module

Présentation

Outline

1. Présentation

3. Matrices

The Numpy module

Présentation

Outline

3. Matrices3.1 Create Matrices and vectors3.2 Scalar product3.3 Matrices product3.4 Transpose matrix3.5 Matrix determinant3.6 Matrix inversion

The Numpy module

Présentation

Create vectors with zeros

The numpy.zeros functionThis function of the Numpy module allows to createzeros floating points vectors (or matrices) of specificsizes

Syntax : a=numpi.zeros(m)a will be a zeros vector of size m

Example

Python scriptimport numpy as npa=np.zeros(4)print(a)

Result[0. 0. 0. 0.]

The Numpy module

Présentation

Syntax : a=numpi.zeros(m)a will be a zeros vector of size m

Example

Result[0. 0. 0. 0.]

The Numpy module

Présentation

The numpy.zeros functionThis function of the Numpy module allows to createzeros floating points vectors (or matrices) of specificsizesSyntax : a=numpi.zeros(m)a will be a zeros vector of size m

Example

Result[0. 0. 0. 0.]

The Numpy module

Présentation

Example

Result[0. 0. 0. 0.]

The Numpy module

Présentation

Example

Result[0. 0. 0. 0.]

The Numpy module

Présentation

Create vectors with given values

The numpy.array functionThis function allows to create vectors (or matrices)from an already known series of values

Syntax : a=numpi.array([values]).Each values should be separated by comas.a will be a vector that contains the given values

Example

Python scriptimport numpy as npa=np.array([1.0,1.1,1.2])print(a)

Result[1.0 1.1 1.2]

The Numpy module

Présentation

Syntax : a=numpi.array([values]).Each values should be separated by comas.a will be a vector that contains the given values

Example

Result[1.0 1.1 1.2]

The Numpy module

Présentation

The numpy.array functionThis function allows to create vectors (or matrices)from an already known series of valuesSyntax : a=numpi.array([values]).Each values should be separated by comas.a will be a vector that contains the given values

Example

Result[1.0 1.1 1.2]

The Numpy module

Présentation

Example

Result[1.0 1.1 1.2]

The Numpy module

Présentation

Example

Result[1.0 1.1 1.2]

The Numpy module

Présentation

Create matrices with zeros

Syntax : a=numpi.zeros((m,n)).a will be a zeros matrix of size m by n

Example

Python scriptimport numpy as npa=np.zeros((2,3))print(a)

Result[[0. 0. 0.][0. 0. 0.]]

The Numpy module

Présentation

Syntax : a=numpi.zeros((m,n)).a will be a zeros matrix of size m by n

Example

Result[[0. 0. 0.][0. 0. 0.]]

The Numpy module

Présentation

The numpy.zeros functionThis function of the Numpy module allows to createzeros floating points vectors (or matrices) of specificsizesSyntax : a=numpi.zeros((m,n)).a will be a zeros matrix of size m by n

Example

Result[[0. 0. 0.][0. 0. 0.]]

The Numpy module

Présentation

Example

Result[[0. 0. 0.][0. 0. 0.]]

The Numpy module

Présentation

Example

Result[[0. 0. 0.][0. 0. 0.]]

The Numpy module

Présentation

Create matrices with given values

Syntax : a=numpi.array([[values1],[values2]).Each values should be separated by comas.a will be a 2 line matrix containing the given values

Example

Python scriptimport numpy as npa=np.array([[1.0,1.1,1.2],[2.0,2.1,2.2]])print(a)

Result[[1.2 1.1 1.2][2.0 2.1 2.2]]

The Numpy module

Présentation

Syntax : a=numpi.array([[values1],[values2]).Each values should be separated by comas.a will be a 2 line matrix containing the given values

Example

Result[[1.2 1.1 1.2][2.0 2.1 2.2]]

The Numpy module

Présentation

The numpy.array functionThis function allows to create vectors (or matrices)from an already known series of valuesSyntax : a=numpi.array([[values1],[values2]).Each values should be separated by comas.a will be a 2 line matrix containing the given values

Example

Result[[1.2 1.1 1.2][2.0 2.1 2.2]]

The Numpy module

Présentation

Example

Result[[1.2 1.1 1.2][2.0 2.1 2.2]]

The Numpy module

Présentation

Example

Result[[1.2 1.1 1.2][2.0 2.1 2.2]]

The Numpy module

Présentation

Outline

The Numpy module

Présentation

Scalar product

numpy.dotThis Numpy function allows to compute scalar productbetween 2 vectors

Syntaxc=numpy.dot(a,b)c will be a scalar, result of the scalar product of a byb.

Example

Python scriptimport numpy as npa=np.array([1,2,3])b=[4,5,6]c=np.dot(a,b)print(c)

Result32

The Numpy module

Présentation

Scalar product

Example

Result32

The Numpy module

Présentation

Scalar product

Example

Result32

The Numpy module

Présentation

Scalar product

Example

Result32

The Numpy module

Présentation

Scalar product

Example

Result32

The Numpy module

Présentation

Outline

The Numpy module

Présentation

Produit matriciel

numpy.dotThis Numpy function allows also to multiply matrices.

Syntaxc=numpy.dot(a,b).c is a matrix that the result of the multiplication of apar b

Example

Python scriptimport numpy as npa=np.array([[1,2,3],[4,5,6]])c=np.array([[4],[2],[1]])print(np.dot(a,c))

Result[[11][32]]

The Numpy module

Présentation

Produit matriciel

Example

Result[[11][32]]

The Numpy module

Présentation

Produit matriciel

Example

Result[[11][32]]

The Numpy module

Présentation

Produit matriciel

Example

Result[[11][32]]

The Numpy module

Présentation

Produit matriciel

Example

Result[[11][32]]

The Numpy module

Présentation

Outline

The Numpy module

Présentation

Transpose matrix

.TThis numpy function allows to transpose matrices.

Syntaxc=a.Tc is the transpose matrix of a

Example

Python scriptimport numpy as npa=np.array([[1,2,3],[4,5,6]])print(a)

print(a.T)

Result[[1 2 3][4 5 6]]

[[1 4][2 4][3 6]]

The Numpy module

Présentation

Transpose matrix

Example

print(a.T)

Result[[1 2 3][4 5 6]]

[[1 4][2 4][3 6]]

The Numpy module

Présentation

Transpose matrix

Example

print(a.T)

Result[[1 2 3][4 5 6]]

[[1 4][2 4][3 6]]

The Numpy module

Présentation

Transpose matrix

Example

print(a.T)

Result[[1 2 3][4 5 6]]

[[1 4][2 4][3 6]]

The Numpy module

Présentation

Transpose matrix

Example

print(a.T)

Result[[1 2 3][4 5 6]]

[[1 4][2 4][3 6]]

The Numpy module

Présentation

Transpose matrix

Example

Python scriptimport numpy as npa=np.array([[1,2,3],[4,5,6]])print(a)print(a.T)

Result[[1 2 3][4 5 6]]

[[1 4][2 4][3 6]]

The Numpy module

Présentation

Transpose matrix

Example

Python scriptimport numpy as npa=np.array([[1,2,3],[4,5,6]])print(a)print(a.T)

Result[[1 2 3][4 5 6]][[1 4][2 4][3 6]]

The Numpy module

Présentation

Outline

The Numpy module

Présentation

Matrix determinant

numpy.linalg.detThis numpy function allows to compute thedeterminant of a matrix.

Syntaxc=numpy.linalg.det(a)c will be the determinant of the squared matrix a.

Example

Python scriptimport numpy as npfrom numpy.linalg import deta=np.array([[1,2],[3,4]])print(det(a))

Result-2.00

The Numpy module

Présentation

Matrix determinant

Example

Result-2.00

The Numpy module

Présentation

Matrix determinant

Example

Result-2.00

The Numpy module

Présentation

Matrix determinant

Example

Result-2.00

The Numpy module

Présentation

Matrix determinant

Example

Result-2.00

The Numpy module

Présentation

Outline

The Numpy module

Présentation

Matrix inversion

numpy.linalg.invTis Numpy function allows to invert squared matrix.

Syntaxc=numpy.linalg.inv(a)c will be the inverted a matrix.

Example

Python scriptimport numpy as npfrom numpy.linalg import inva=np.array([[1,2],[3,4]])print(inv(a))

Result[[−2.00 1.0][1.5 − 0.5]]

The Numpy module

Présentation

Matrix inversion

Example

Result[[−2.00 1.0][1.5 − 0.5]]

The Numpy module

Présentation

Matrix inversion

Example

Result[[−2.00 1.0][1.5 − 0.5]]

The Numpy module

Présentation

Matrix inversion

Example

Result[[−2.00 1.0][1.5 − 0.5]]

The Numpy module

Présentation

Matrix inversion

Example

Result[[−2.00 1.0][1.5 − 0.5]]

The Numpy module

Présentation

Outline

1. Présentation

3. Matrices

The Numpy module

Présentation

Outline

4. Solve Equation system4.1 Linear equation system4.2 Matrix diagonalization

The Numpy module

Présentation

Linear equation system

numpy.linalg.solveThis Numpy function allows to solve linear equationsystems.

Syntaxec=numpy.linalg.solve(a,b) where a is the coefficientmatrix and b a vector.

The Numpy module

Présentation

The Numpy module

Présentation

The Numpy module

Présentation

Solve Equation system

ExampleLets solve the linear equation system{

3x + y = 9x + 2y = 8

Python scriptimport numpy as npfrom numpy.linalg import solvea=np.array([[3,1],[1,2]])b=np.array([9,8])print(solve(a,b))

Result[2 3]

Solutions are x=2 and y=3

The Numpy module

Présentation

3x + y = 9x + 2y = 8

Result[2 3]

The Numpy module

Présentation

3x + y = 9x + 2y = 8

Result[2 3]

The Numpy module

Présentation

3x + y = 9x + 2y = 8

Result[2 3]

The Numpy module

Présentation

Outline

4. Solve Equation system4.1 Linear equation system4.2 Matrix diagonalization

The Numpy module

Présentation

Matrix diagonalization

numpy.linalg.eigThis Numpy function will output the eigenvalues andeigenvectors of a matrix

SyntaxE, V=numpy.linalg.eig(a)E will contain the eigenvalues of a and V itseigenvectors.

The Numpy module

Présentation

The Numpy module

Présentation

The Numpy module

Présentation

Example

Python scriptimport numpy as npfrom numpy.linalg import eigA=np.array([[1,1,-2],[-1,2,1],[0,1,-1]])D, V = eig(A)print(D)

Result[2. 1. -1.]

[[3.015e − 01 −8.017e −01 7.071e − 01][9.045e − 01 −5.345e −01 2.435e − 17][3.015e − 01 −2.672e −01 7.071e − 01]]

The Numpy module

Présentation

Example

Result[2. 1. -1.]

[[3.015e − 01 −8.017e −01 7.071e − 01][9.045e − 01 −5.345e −01 2.435e − 17][3.015e − 01 −2.672e −01 7.071e − 01]]

The Numpy module

Présentation

Example

Result[2. 1. -1.]

[[3.015e − 01 −8.017e −01 7.071e − 01][9.045e − 01 −5.345e −01 2.435e − 17][3.015e − 01 −2.672e −01 7.071e − 01]]

The Numpy module

Présentation

Example

Result[2. 1. -1.][[3.015e − 01 −8.017e −01 7.071e − 01][9.045e − 01 −5.345e −01 2.435e − 17][3.015e − 01 −2.672e −01 7.071e − 01]]

Graphical representationThe matplotlib module

The matplolib module

IntroductionDefinitionstructure

2D plotsScatter pointsCourbesCurves+markers

Multiple plotsOn the same graphOn 2 graphs

TitlesGraph titleAxis titles

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Outline

1. Introduction

2. 2D plots

3. Multiple plots

4. Titles

5. Legend

6. Axis range

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Outline

1. Introduction1.1 Definition1.2 Structure of a program

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Definition

Matplotlib : What is it ?Matplotlib is a Python module which, combined withthe Numpy and Scipy module, is an extremelypowerful tools for plotting and visualizing data .The Matplotlib module have several advantages :

▶ free of charge▶ easy to use▶ extensible▶ One of the biggest developer community▶ etc

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Outline

1. Introduction1.1 Definition1.2 Structure of a program

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Matplotlib : Structure of a program

Structure d’un programmeA program with plot is most athe structured in the followingfashion :

1. Import the pyplotfunctionality of matplotlib

2. The program part thatmake the calculations

3. Call of a pyplot function4. Ask the plot to be

displayed

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Structure d’un programmeA program with plot is most athe structured in the followingfashion :

1. Import the pyplotfunctionality of matplotlib

displayed

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Structure d’un programmeA program with plot is most athe structured in the followingfashion :1. Import the pyplot

functionality of matplotlib

displayed

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functionality of matplotlib2. The program part that

make the calculations

displayed

Legend

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make the calculations3. Call of a pyplot function

4. Ask the plot to bedisplayed

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Axis range

make the calculations3. Call of a pyplot function4. Ask the plot to be

displayed

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Outline

1. Introduction

2. 2D plots

3. Multiple plots

4. Titles

5. Legend

6. Axis range

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Outline

2. 2D plots2.1 Scatter points2.2 Courbes2.3 Curves+markers

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Matplotlib : Scatter points

Scatter pointsTo plot Y as a function of X, use the followingsyntax :plt.scatter(X,Y)

Example

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Scatter points : Some optionsChange the marker styleUse the option marker=Change the marker sizeUse the option s= (20 is the default)Change the marker colorUse the option c=

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Scatter points : The various markers style

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Scatter points : the various marker colorsvalue color’b’ blue’g’ green’r’ red’c’ cyan’m’ magenta’y’ yellow’k’ black’w’ white

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Scatter points : Some options : Example

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Scatter points : CustomizationOn could also define marker colors and sizes for eachpoints using lists :(ATTENTION : the size of these lists should be thesame as the data lists)

Example

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Matplotlib : Curves

CurvesTo plot Y as a function of X, use the followingsyntax :plt.plot(X,Y)

Example

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Matplotlib : Curves

Example

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Matplotlib : Curves

Example

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Matplotlib : Curves

Curves : Some optionsChange the linestyleUse the option linestyle=Change the linewidthUse the option linewidth=Change the line colorUse the option color=

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Matplotlib : Curves

Curves : Some optionsChange the linestyleUse the option linestyle=Change the linewidthUse the option linewidth=Change the line colorUse the option color=

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Matplotlib : Curves

Curves : The various line colorsvalue color’b’ blue’g’ green’r’ red’c’ cyan’m’ magenta’y’ yellow’k’ black’w’ white

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Matplotlib : Curves

Curves : The various line stylesvalue linestyle’ :’ doted’-.’ doted and dashed’–’ dashed

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Matplotlib : Curves

Curves : Some options : Example

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Matplotlib : Curves

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Matplotlib : Curves

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Outline

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Matplotlib : Curves+markers

Curves+markersIt is possible to combine both curves and scatterpoints.To do so, use the curves plot method and add themarker= option.

Example

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Curves+markers : Some optionsChange the marker colorUse the option markeredgecolor= and markerfacecolorChange marker sizeUse the option markersize=

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Curves+markers : Some optionsChange the marker colorUse the option markeredgecolor= and markerfacecolorChange marker sizeUse the option markersize=

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Curves+markers : Some options : Example

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Outline

1. Introduction

2. 2D plots

3. Multiple plots

4. Titles

5. Legend

6. Axis range

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Outline

3. Multiple plots3.1 On the same graph3.2 On 2 graphs

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Matplotlib : Multiples plot

2 plotsIf you want to have 2 curves on the same plot, usetwice the plot function

Example

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Outline

3. Multiple plots3.1 On the same graph3.2 On 2 graphs

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Matplotlib : Multiple plots

2 plotsIf you want to have 2 curves on 2 different graphs, usethe subplot function

Different type of subplots▶ X common axis▶ Y common axis▶ X and Y common axis▶ No common axis

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Matplotlib : Multiple plots

2 plotsIf you want to have 2 curves on 2 different graphs, usethe subplot function

Different type of subplots▶ X common axis▶ Y common axis▶ X and Y common axis▶ No common axis

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Matplotlib : Multiples plots : X common axis

SyntaxUse the subplot function with the syntax :f, ax = plt.subplots(2,sharex=True) where 2 specifythat you want 2 graphs.

Example

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Matplotlib : Multiples plots : Y common axis

SyntaxUse the subplot function with the syntax :f, (ax1,ax2) = plt.subplots(1,2,sharex=True) where 1and 2 specify that you want 1 graph vertically and 2horizontally.

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Matplotlib : Multiples plots : X and Ycommon axis

SyntaxUse the subplot function with the syntax :f, ax = plt.subplots(2,sharex=True, sharey=True)where 2 specify that you want 2 graphs.

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Matplotlib : Multiples plots : No commonaxis

SyntaxUse the subplot function with the syntax :f, ax = plt.subplots(2) where 2 specify that you want2 graphs.

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Outline

1. Introduction

2. 2D plots

3. Multiple plots

4. Titles

5. Legend

6. Axis range

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Outline

4. Titles4.1 Graph title4.2 Axis titles

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Graph title : single graph

Add a title to a graphTo add a graph title, use the following syntax :plt.title(title_name)

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Graph title : Subplots

Add a subplot titleTo a dd a global graph title, use :suptitle(title_name)To add a subplot title, use :set_title(title_name)

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Outline

4. Titles4.1 Graph title4.2 Axis titles

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Axis title : Single graph

Add axix titlesTo add axis titles, use :plt.xlabel(X_axis_title) and plt.ylabel(Y_axis_title)

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Axis titles : Subplots

Add axis titlesTo add axis titles, use :set_xlabel(X_axis_title) et set_ylabel(Y_axis_title)

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Outline

1. Introduction

2. 2D plots

3. Multiple plots

4. Titles

5. Legend

6. Axis range

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Axis range

Legend : single graphique

Add a legendTo add a legend, use :label= option for each plot and plt.legend to showlegend.

Example

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legend : Subplots

Add a legendPTo add a legend to each subplots, use :label= option for each plot and .legend to showlegends.

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legend : Subplots

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legend : Subplots

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Outline

1. Introduction

2. 2D plots

3. Multiple plots

4. Titles

5. Legend

6. Axis range

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Axis range : Single graphique

Define X and Y rangeTo define X and Y ranges, use :xlim=(min,max) and ylim=(min,max).

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Axis range : Subplots

Define X and Y rangePTo define X and Y ranges, use :set_xlim=(min,max) and set_ylim=(min,max) foreach subplots.

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3D plots with matplotlib

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Outline

1. Import modules

2. Curves

3. Scatter points

4. Wireframe plot

5. Surface plot

6. 2D Plots

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Matplotlib3D : Import modules

As for 2DAs for 2D graphs, you should import pyplot :import matplotlib.pyplot as plt

Addition module for 3DFor 3D plots, you should also import the mplot3Dfunction of the mpl_toolkits module :from mpl_toolkits.mplot3d import Axes3D

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

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Matplotlib 3D

Import modules

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Nuages de points

Wireframe

Surface

Matplotlib3D : Specific syntax

Create a figureYou should create a particular interface for the figurespecifying that it will be a 3D figure :fig = plt.figure()ax = fig.gca(projection=’3d’)

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Matplotlib3D : Specific syntax

Create a figureYou should create a particular interface for the figurespecifying that it will be a 3D figure :fig = plt.figure()ax = fig.gca(projection=’3d’)

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Outline

1. Import modules

2. Curves

3. Scatter points

4. Wireframe plot

5. Surface plot

6. 2D Plots

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Matplotlib3D : Curves

plot 3D curvesIt works exactly as for 2D except that you should give3 data lists :plt.plot(X,Y,Z)

Example

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Example

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Example

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Outline

1. Import modules

2. Curves

3. Scatter points

4. Wireframe plot

5. Surface plot

6. 2D Plots

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Matplotlib3D : Scatter points

3D Scatter pointsIt works exactly as for 2D except that you should give3 data lists :plt.scatter(X,Y,Z)

Example

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Example

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Example

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Outline

1. Import modules

2. Curves

3. Scatter points

4. Wireframe plot

5. Surface plot

6. 2D Plots

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Matplotlib3D : Wireframe

Wireframe plotsTo do this, use :plt.wireframe(X,Y,Z)

Example

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Example

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Example

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Outline

1. Import modules

2. Curves

3. Scatter points

4. Wireframe plot

5. Surface plot

6. 2D Plots

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Matplotlib3D : Surface

Surface plotYou should use the following syntax :plt.surface(X,Y,Z)

Example

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Example

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Example

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Matplotlib3D : Surface plot

With a color gradientYou can do it using the cmap=cm.colorwarm option :plt.surface(X,Y,Z, cmap=cm.colorwarm)

Example

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Example

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Example

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Outline

1. Import modules

2. Curves

3. Scatter points

4. Wireframe plot

5. Surface plot

6. 2D Plots

Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

Matplotlib3D : 2D plots

Plot 2DThis can be done by removing a direction (z forexample) :ax.plot(x, y, zs=0, zdir=’z’)

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Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

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Matplotlib 3D

Import modules

Courbes

Nuages de points

Wireframe

Surface

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Introduction to programmation using the Python language

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