feets | feATURE eXTRACTOR FOR tIME sERIES | Machine Learning library
kandi X-RAY | feets Summary
kandi X-RAY | feets Summary
In time-domain astronomy, data gathered from the telescopes is usually represented in the form of light-curves. These are time series that show the brightness variation of an object through a period of time (for a visual representation see video below). Based on the variability characteristics of the light-curves, celestial objects can be classified into different groups (quasars, long period variables, eclipsing binaries, etc.) and consequently be studied in depth independentely. In order to characterize this variability, some of the existing methods use machine learning algorithms that build their decision on the light-curves features. Features, the topic of the following work, are numerical descriptors that aim to characterize and distinguish the different variability classes. They can go from basic statistical measures such as the mean or the standard deviation, to complex time-series characteristics such as the autocorrelation function. In this package we present a library with a compilation of some of the existing light-curve features. The main goal is to create a collaborative and open tool where every user can characterize or analyze an astronomical photometric database while also contributing to the library by adding new features. However, it is important to highlight that this library is not restricted to the astronomical field and could also be applied to any kind of time series. Our vision is to be capable of analyzing and comparing light-curves from all the available astronomical catalogs in a standard and universal way. This would facilitate and make more efficient tasks as modelling, classification, data cleaning, outlier detection and data analysis in general. Consequently, when studying light-curves, astronomers and data analysts would be on the same wavelength and would not have the necessity to find a way of comparing or matching different features. In order to achieve this goal, the library should be run in every existent survey (MACHO, EROS, OGLE, Catalina, Pan-STARRS, etc) and future surveys (LSST) and the results should be ideally shared in the same open way as this library.
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Top functions reviewed by kandi - BETA
- Fetch a lightcurve3 object
- Retrieve the data home directory
- Ensure lc is 1d
- Fetch a file from url
- Compute the log - likelihood
- Flattens the value of the given feature
- Flattens a single feature
- Create a periodic distribution
- Create a data object
- Run setup
- Fit the autocorrelation function
- Run the extractor
- Generate a list of features
- Fit the SlottedA model
- Parse command line options
- Sort a list of extractors
- Render the features table
- Download a file from a given URL
- Load MACHO example
- Register an Extractor
- Calculate the phonon harmonic coefficients
- Create a normal distribution
- Create a random distribution
- Plot a feature
- Fit the function to the model
- Try to load setuptools
feets Key Features
feets Examples and Code Snippets
Community Discussions
Trending Discussions on feets
QUESTION
I am trying to validate 3 values, one that is entered manually and the other two are selected with the picker, in the end it is not validated and an error appears, I need that when the user has not entered any value, an alert pops up saying that all fields must be completed, but I can't see how to implement it.
...ANSWER
Answered 2020-Nov-23 at 19:47bool error = false;
if (string.IsNullOrEmpty(peso.Text) ||
Pies.SelectedItem == null ||
Pulgadas.SelectedItem == null)
{
error = true;
// display error message
}
QUESTION
I'm new to SwiftUI and manual camera functionality, and I really need help.
So I trying to build a SwiftUI camera view that has a UIKit camera as a wrapper to control the focus lens position via SwiftUI picker view, display below a fucus value, and want to try have a correlation between AVcaptureDevice.lensPosition from 0 to 1.0 and feats that are displayed in the focus picker view. But for now, I only want to display that fucus number on screen.
And the problem is when I try to update focus via coordinator focus observation and set it to the camera view model then nothing happened. Please help 🙌
Here's the code:
...ANSWER
Answered 2020-Nov-13 at 15:56The problem with your provided code is that the type of selectedFocus within the FocusPicker view should be Integer rather than Float. So one option is to change this type to Integer and find a way to express the AVCaptureDevice.lensPosition as an Integer with the given range.
The second option is to replace the feets array with an enumeration. By making the enumeration conform to the CustomStringConvertible protocol, you can even provide a proper description. Please see my example below.
I've stripped your code a bit as you just wanted to display the number in the first step and thus the code is more comprehensible.
My working example:
QUESTION
How can we pass floating point values to another page? I have sent a floating point value in an AJAX request, but the page only received an integer value.
...ANSWER
Answered 2020-Mar-14 at 07:19just add this
QUESTION
I am working on two NLP projects in Python, and both have a similar task to extract numerical values and comparison operators from sentences, like the following:
...ANSWER
Answered 2017-Jul-16 at 15:20I would probably approach this as a chunking task and use nltk's part of speech tagger combined with its regular expression chunker. This will allow you to define a regular expression based on the part of speech of the words in your sentences instead of on the words themselves. For a given sentence, you can do the following:
QUESTION
I need to be able to convert from a standard double into another double (or float) that is rationalized into feet.inches. The tool that reads this output reads the first number before the . as "feet" and anything after as "inches".
The tool reads 1.12 as 2 feet, because it's 1 foot and 12 inches, this is why we are rounding to one decimal place unless it is exactly x feet and 11 inches.
The goal of this function is to pass in a standard decimal and return its conversion into feet and inches, via this specific format.
...ANSWER
Answered 2020-Mar-03 at 23:56One simple way to do it would be to take the input number, get the "whole" part (which won't change) and then get the "decimal" part separately and multiply it by 12. We can then return these combined as a string:
QUESTION
I'm looking for a way to get an A4 responsive page like in this example : https://codepen.io/chriscoyier/pen/VvRoWy. But instead of resizing through a component, it would be using the navigator. Is that actually possible ?
I've been trying to get an answer with the help of the community in thoses posts :
However, the responsive is different. Because I really need to keep the A4 format from cellphone screens to 4K televisors. Like in any screen, we would see an entire page (not smaller, nor bigger than the screen itself).
In the very last case, I would use media queries but getting a solution with JS would be better. I guess in some way, I need to get the height and adjust the scale even after the page feets the screen. But I can't find a solution alone.
Any help is very welcomed :)
My actual code :
...ANSWER
Answered 2020-Feb-16 at 18:59Well, in fact, I made it. I let my code here, if anyone needs it someday : A4 pages scaled to always fit the screen
QUESTION
I am using Django rest auth to authenticate my users, that works well. how my model is set up is that I have the custom user model for authentication and I also have a profile model that gets created with a signal.
I want that when the users are fetched in its URL, the profile for that user is also called an object in user.
my models.py (I didnt include some models like the user managers, skill, e.t.c as i felt they werent relevant)
...ANSWER
Answered 2019-Nov-23 at 16:15Use source (DRF doc) argument
QUESTION
I am making a game where I can spawn soldiers with a button click. All of these soldiers will be added in an ArrayList named entity_walking_right_array. I also have another ArrayList for the entities which are walking left.
I have another class where the x, y position, the animation etc. of the soldier is determined or drawn. All soldiers have a random Y value between the screen height and 450 pixels.
When I spawn the soldiers some of them will logically have a higher y value or y position than others but when those are created later, than soldiers with a lower y value, they will be rendered above them. That leads to soldiers being rendered above soldiers when they logically would be behind them. (For example the feets are in the face of the lower y value soldier)
I then render the soldiers like that:
...ANSWER
Answered 2019-Jun-17 at 11:43it simply says "Cannot resolve method 'compareTo(float)'. You need to use method compare instead of compareTo and pass as parameters the two objects you want compare. https://docs.oracle.com/javase/7/docs/api/java/util/Comparator.html
Collections.sort(entity_walking_right_array, (o1, o2) -> compare(o1.getY(), o2.getY()));
QUESTION
When the friendly function add is used to print the value of sum variable of two classes, the correct output is printing. But, when then display function of their respective class are used, garbage value is printing.
What's wrong with the code?
ANSWER
Answered 2019-Jun-17 at 12:05The problem is that you print sum but you never initialize the sum of obj1 and obj2.
You initialize sum only inside add() but you pass values to add() by copy, so you initialize sum only in temporary objects.
When you print obj1.sum and obj2.sum (through display()), the sum member are still not-initialized.
So the garbage.
Try passing objects by reference
QUESTION
I am trying to implement a Machine-Learning algorithm to predict house prices in New-York-City.
Now, when I try to plot (using Seaborn) the relationship between two columns of my house-prices dataset: 'gross_sqft_thousands' (the gross area of the property in thousands of square feets) and the target-column which is the 'sale_price_millions', I get a weird plot like this one:
Code used to plot:
...ANSWER
Answered 2019-Jun-02 at 16:01Your housing price dataset is much larger than the tips dataset shown in that Seaborn example plot, so scatter plots made with default settings will be massively overcrowded.
The second plot looks "weird" because it plots a (practically) continuous variable, sales price, against an integer-valued variable, total_units.
The following solutions come to mind:
Downsample the dataset with something like
sns.regplot(x="sale_price_millions", y="gross_sqft_thousands", data=clean_df[::10]). The[::10]part selects every 10th line fromclean_df. You could also tryclean_df.sample(frac=0.1, random_state=12345), which randomly samples 10% of all rows without replacement (using a random seed for reproducibility).Reduce the alpha (opacity) and/or size of the scatterplot points with
sns.regplot(x="sale_price_millions", y="gross_sqft_thousands", data=clean_df, scatter_kws={"alpha": 0.1, "s": 1}).For plot 2, add a bit of "jitter" (random noise) to the y-axis variable with
sns.regplot(..., y_jitter=0.05).
For more, check out the Seaborn documentation on regplot: https://seaborn.pydata.org/generated/seaborn.regplot.html
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Install feets
Clone this repo and then inside the local
Execute ``` {.sourceCode .bash} $ pip install -e . ```
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