Concept

Python syntax and semantics

Notebooks associés (16)

Introduction: Python and ethical dilemmas

Introduction: Python and ethical dilemmas¶{.anchor-link} {#Introduction:-Python-and-ethical-dilemmas}

Notebook by Athina Papageorgiou Koufidou, Cécile Hardebolle and the Responsible software team (2025). Except where otherwise noted, the content of this notebook is licensed under a {rel="license"}Creative Commons Attribution International License (CC BY 4.0 International).
[](http://creativecommons.org/licenses

Modeling and Analysis of a PN-Junction in Inhomogeneous Semiconductors.

In [1]: import matplotlib.pyplot as plt import matplotlib.ticker as mtick import numpy as np import ipywidgets as widgets import scipy.integrate as integrate from ipywidgets import interact, fixed from scipy.interpolate import interp1d from textwrap import dedent from bokeh.io import push_notebook, show, output_notebook, output_file, curdoc from bokeh.plotting import figure from bokeh.layouts import column, row from bokeh.themes import built_in_themes from bokeh.models import Range1d, BasicTickFormatter, L

Tight-Binding Approximation for 2D Lattices: Square, Triangular, Lieb, and Honeycomb

In [1]: import numpy as np import matplotlib.pyplot as plt

from future import print_function

from ipywidgets import interact, interactive, fixed, interact_manual import ipywidgets as widgets %matplotlib inline In [2]: def band(nkl,kpoints,ham): :param k: wave number nk=32 # Define the position of the original lattice #klines=np.zeros((nkl-1,nk)) n=0 d=np.size(ham([0.0,0.0]),1) evk=np.zeros((nknkl-nk-1,d)) lenk=np.zeros((nknkl-nk-1,d)) for i in range(0,nkl-1)

Basic Example of Anderson Localization in a 1D System

Demonstration of Anderson localization[1]¶ This notebook is intended to show a very basic example of the Anderson localization in one-dimensional system. In [1]: import numpy as np from numpy import linalg as LA import matplotlib.pyplot as plt

from future import print_function

from ipywidgets import interact, interactive, fixed, interact_manual import ipywidgets as widgets %matplotlib inline To show the idea of Anderson localization, we can consider 1D chain of

N

atoms with perio

Phase Contrast Transfer Function

::: {role="main"} ::: {.jp-Cell .jp-MarkdownCell .jp-Notebook-cell} ::: {.jp-Cell-inputWrapper tabindex="0"} ::: {.jp-Collapser .jp-InputCollapser .jp-Cell-inputCollapser} ::: ::: {.jp-InputArea .jp-Cell-inputArea} ::: {.jp-InputPrompt .jp-InputArea-prompt} ::: ::: {.jp-RenderedHTMLCommon .jp-RenderedMarkdown .jp-MarkdownOutput mime-type="text/markdown"}

Phase Contras Transfer Function¶{.anchor-link} {#Phase-Contras-Transfer-Function}

This relatively simple notebook

Data Transformations in Python

404

 __________________________________________________________________

This domain is successfully pointed at WP Engine, but is not configured for an account on our platform. * Did you [1]add this domain to your install? * Did you point DNS to the correct [2]IP address or [3]CNAME? [4]contact us and we can help get your site up and running in no time. __________________________________________________________________ Hosted by [5][AQby4xHTwxtnAAAAAElFTkSuQmCC] References

Introduction to Reciprocal Lattices with Periodic Boundary Conditions.

Real vs. Reciprocal Space in 2D[1]¶ Introduction[2]¶ In this short notebook, we will introduce the lattice with periodic(Born- von Karman) boundary condition. Following the boundary condition, there is a transformation from real lattice to the reciprocal lattice. In the code below, we define a1 and a2 through cartesian vectors. Hence, the reciprocal vectors will be the original rotated by 90 degrees multiplied by 2pi and divided by the area of the unit cell (|a1xa2|) In [1]: i

Illustrating Band Structures in Solids: Free Electrons and Atomic Orbitals

In [1]: import numpy as np from numpy import linalg as LA import matplotlib.pyplot as plt

from future import print_function

from ipywidgets import interact, interactive, fixed, interact_manual import ipywidgets as widgets %matplotlib widget The emergence of band structures[1]¶ If you have questions about this notebook, e-mail Oleg Malanyuk (oleg.malanyuk@epfl.ch) This jupyter notebook is intended to provide a illustration of the band structures in solides, starting from the points of v

Band Structure Investigation of Monolayer and Bilayer Graphene Using the Tight Binding Model

In [1]: import matplotlib.pyplot as plt import numpy as np from mpl_toolkits import mplot3d import itertools %matplotlib widget Band Structure of Mono and Bilayer Graphene[1]¶ If you have questions about this notebook, e-mail Oleg Malanyuk (oleg.malanyuk@epfl.ch) The purpose of this notebook is to investigate the band model of Mono and Bilayer graphene modeled with tight binding model. Tight binding model for monolayer graphene[2]¶ Monolayer graphene is a sheet of carbons aranged in a he

Designing FIR Filters Using the Parks-McClellan Algorithm

The Parks-McClellan Filter Design Method[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

The Parks-McClellan (PM) algorithm is a clever application of advanced polynomial fitting techniques to the problem of FIR filter design. In this notebook we will explore the key ideas behind the method by considering the design of a simple Type-I lowpass filter. NOTE: This notebook uses interactive widgets. If the interactive controls do not work or show up, please fo

Block Processing of Audio Files Using Stateful FIR Filters

Block-processing of audio files[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

This notebook shows a simple way to process audio files (in WAV format) in a block-by-block fashion; this is useful in two cases 1. when you want to process a data stream in real time but you can accept a small processing delay; in this case a buffered approach can yield computational gains 2. when you need to process a large file that does not fit entirely into

Understanding the Haar Basis for Grayscale Image Compression

A Basis for Grayscale Images[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

The concept of "basis" for a vector space is one of the most profound and fruitful ideas in linear algebra. Basis vectors are the "building blocks" that all other vectors are built from; by "disassembling" a vector into a linear combination of basis elements we are able to "look inside" the vector and highlight many of its relevant features. A vector space has an infinite number o

Understanding and Plotting the Discrete Fourier Transform (DFT)

Plotting the DFT[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

In this notebook we will look at the practical issues associated to plotting the DFT and in particular the DFT of real-world signals. We will examine how to map the DFT coefficients to real-world frequencies and we will investigate the frequency resolution of the DFT and the effects of zero padding. In [1]:

first our usual bookkeeping

%matplotlib inline import matplotlib import matplotlib.p

Numerical Precision in DFT Computation

Numerical Precision in DFT Computation[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

In [1]:

first our usual bookkeeping

%matplotlib inline import matplotlib import matplotlib.pyplot as plt import numpy as np In this notebook we will look at some numerical issues associated to the DFT; in particular we we will look at the differences in precision between the "naive" way of computing the DFT and the FFT algorithm. As a quick reminder, the definitions of t

Cylindrical Coordinates Visualization

Important note¶{.anchor-link} {#Important-note}

This notebook is obsolete and not maintained. For an interactive display of cylidri

Spherical Coordinates Visualization

Important note¶{.anchor-link} {#Important-note}

This notebook is obsolete and not maintained. For an interactive display of polar coordinates, please use

def rotation_matrix(d):
    """
    Calculates a rotation matrix given a vector d. The direction of d
    corresponds to the rotation axis. The length of d corresponds to 
    the sin of the angle of rotation.

    Variant of: http://mail.scipy.org/pipermail/numpy-discuss

Graph Chat

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Notebooks associés (16)

Introduction: Python and ethical dilemmas

Introduction: Python and ethical dilemmas¶{.anchor-link} {#Introduction:-Python-and-ethical-dilemmas}

Modeling and Analysis of a PN-Junction in Inhomogeneous Semiconductors.

Tight-Binding Approximation for 2D Lattices: Square, Triangular, Lieb, and Honeycomb

In [1]: import numpy as np import matplotlib.pyplot as plt

from future import print_function

Basic Example of Anderson Localization in a 1D System

from future import print_function

from ipywidgets import interact, interactive, fixed, interact_manual import ipywidgets as widgets %matplotlib inline To show the idea of Anderson localization, we can consider 1D chain of

N

atoms with perio

Phase Contrast Transfer Function

Phase Contras Transfer Function¶{.anchor-link} {#Phase-Contras-Transfer-Function}

This relatively simple notebook

Data Transformations in Python

404

 __________________________________________________________________

Introduction to Reciprocal Lattices with Periodic Boundary Conditions.

Illustrating Band Structures in Solids: Free Electrons and Atomic Orbitals

In [1]: import numpy as np from numpy import linalg as LA import matplotlib.pyplot as plt

from future import print_function

Band Structure Investigation of Monolayer and Bilayer Graphene Using the Tight Binding Model

Designing FIR Filters Using the Parks-McClellan Algorithm

The Parks-McClellan Filter Design Method[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

Block Processing of Audio Files Using Stateful FIR Filters

Block-processing of audio files[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

Understanding the Haar Basis for Grayscale Image Compression

A Basis for Grayscale Images[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

Understanding and Plotting the Discrete Fourier Transform (DFT)

Plotting the DFT[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

first our usual bookkeeping

%matplotlib inline import matplotlib import matplotlib.p

Numerical Precision in DFT Computation

Numerical Precision in DFT Computation[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

In [1]:

first our usual bookkeeping

Cylindrical Coordinates Visualization

Important note¶{.anchor-link} {#Important-note}

This notebook is obsolete and not maintained. For an interactive display of cylidri

Spherical Coordinates Visualization

Important note¶{.anchor-link} {#Important-note}

This notebook is obsolete and not maintained. For an interactive display of polar coordinates, please use

def rotation_matrix(d):
    """
    Calculates a rotation matrix given a vector d. The direction of d
    corresponds to the rotation axis. The length of d corresponds to 
    the sin of the angle of rotation.

    Variant of: http://mail.scipy.org/pipermail/numpy-discuss