Larch is an open-source library and set of applications for processing and analyzing X-ray absorption and fluorescence spectroscopy data and X-ray fluorescence and diffraction image data from synchrotron beamlines. It is especially focussed on X-ray absorption fine-structure spectroscopy (XAFS) including X-ray absorption near-edge spectroscopy (XANES) and extended X-ray absorption fine-structure spectroscopy (EXAFS). It also supports visualization and analysis tools for X-ray fluorescence (XRF) spectra and XRF and X-ray diffraction (XRD) images as collected at scanning X-ray microprobe beamlines.
Larch is written in Python, making heavy use of the excellent scientific python libraries (numpy, scipy, h5py, matplotlib,and many more). Larch can be used as a Python library for processing and analyzing X-ray spectroscopy and imaging data. In addition, the applications built with it also use a built-in Python-like macro language for interactive and batch processing. This domain-specific language is intended to be very easy to use for novices while also being complete enough to automate data processing and analysis and to encourage and facilitate a gentle transition to transition from GUI-only analyses to scripted and programmatic analysis of larger data sets. This macro language also allows Larch to be run as a service, interacting with other processes or languages via XML-RPC, and so be used by the popular Demeter XAFS application suite.
Larch is distributed under an open-source license that is nearly identical to the BSD license. It is under active and open development centered at the GeoScoilEnviroCARS sector of Center for Advanced Radiation Sources at the University of Chicago has been supported by the US National Science Foundation - Earth Sciences (EAR-1128799), and Department of Energy GeoSciences (DE-FG02-94ER14466). In addition, funding specifically for Larch was granted by the National Science Foundation - Advanced CyberInfrastructure (ACI-1450468).
The best citable reference for Larch is M. Newville, Larch: An Analysis Package For XAFS And Related Spectroscopies. Journal of Physics: Conference Series, 430:012007 (2013).
These applications installed with Larch, in addition to a basic Python library. Here, GUI = Graphical User Interface, CLI = Command Line Interface, and beta indicates a work in progress. The Dioptas program is written and maintained by Clemens Prescher, and included with Larch.
|larch||CLI||simple shell command-line interface|
|Larch GUI||GUI||enhanced command-line interface with data browser|
|XAS Viewer||GUI||XAFS Processing and Analysis: XANES pre-edge peak fitting, linear analysis, PCA/LASSO, EXAFS extraction|
|GSE Map Viewer||GUI||XRF Map Viewer for GSECARS X-ray microprobe data.|
|XRF Display||GUI||Display and analyze XRF Spectra.|
|Dioptas||GUI||Display XRD images, calibrate to XRD patterns.|
|feff6l||CLI||Feff 6 EXAFS calculations|
|feff8l||CLI||Feff 8 EXAFS calculations (no XANES)|
|qtrixs||GUI beta||Display RIXS planes, take profiles|
|1D XRD Viewer||GUI beta||Display and work with 1-D XRD patterns|
|2D XRD Viewer||GUI beta||Display XRD images|
#python #data-science #data-analysis
Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.
Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is
Syntax: x = lambda arguments : expression
Now i will show you some python lambda function examples:
#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map
No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas.
By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities.
Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly.
Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.
Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions.
Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events.
Simple to read and compose
Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building.
The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties.
Utilized by the best
Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player.
Massive community support
Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions.
Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking.
Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.
The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.
Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential.
The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.
#python development services #python development company #python app development #python development #python in web development #python software development
Magic Methods are the special methods which gives us the ability to access built in syntactical features such as ‘<’, ‘>’, ‘==’, ‘+’ etc…
You must have worked with such methods without knowing them to be as magic methods. Magic methods can be identified with their names which start with __ and ends with __ like init, call, str etc. These methods are also called Dunder Methods, because of their name starting and ending with Double Underscore (Dunder).
Now there are a number of such special methods, which you might have come across too, in Python. We will just be taking an example of a few of them to understand how they work and how we can use them.
class AnyClass: def __init__(): print("Init called on its own") obj = AnyClass()
The first example is _init, _and as the name suggests, it is used for initializing objects. Init method is called on its own, ie. whenever an object is created for the class, the init method is called on its own.
The output of the above code will be given below. Note how we did not call the init method and it got invoked as we created an object for class AnyClass.
Init called on its own
Let’s move to some other example, add gives us the ability to access the built in syntax feature of the character +. Let’s see how,
class AnyClass: def __init__(self, var): self.some_var = var def __add__(self, other_obj): print("Calling the add method") return self.some_var + other_obj.some_var obj1 = AnyClass(5) obj2 = AnyClass(6) obj1 + obj2
#python3 #python #python-programming #python-web-development #python-tutorials #python-top-story #python-tips #learn-python
Python is awesome, it’s one of the easiest languages with simple and intuitive syntax but wait, have you ever thought that there might ways to write your python code simpler?
In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.
Swapping value in Python
Instead of creating a temporary variable to hold the value of the one while swapping, you can do this instead
>>> FirstName = "kalebu" >>> LastName = "Jordan" >>> FirstName, LastName = LastName, FirstName >>> print(FirstName, LastName) ('Jordan', 'kalebu')
#python #python-programming #python3 #python-tutorials #learn-python #python-tips #python-skills #python-development
Today you’re going to learn how to use Python programming in a way that can ultimately save a lot of space on your drive by removing all the duplicates.
In many situations you may find yourself having duplicates files on your disk and but when it comes to tracking and checking them manually it can tedious.
Heres a solution
Instead of tracking throughout your disk to see if there is a duplicate, you can automate the process using coding, by writing a program to recursively track through the disk and remove all the found duplicates and that’s what this article is about.
But How do we do it?
If we were to read the whole file and then compare it to the rest of the files recursively through the given directory it will take a very long time, then how do we do it?
The answer is hashing, with hashing can generate a given string of letters and numbers which act as the identity of a given file and if we find any other file with the same identity we gonna delete it.
There’s a variety of hashing algorithms out there such as
#python-programming #python-tutorials #learn-python #python-project #python3 #python #python-skills #python-tips