boltzmann | an ergodic framework for entropic
kandi X-RAY | boltzmann Summary
kandi X-RAY | boltzmann Summary
Boltzmann is a JavaScript framework for writing web servers. It is implemented in a single file that lives alongside your code. Boltzmann is focused on delivering a great developer experience and makes its tradeoffs with that goal in mind. Boltzmann is implemented in vanilla JavaScript and scaffolds a JavaScript project by default, with TypeScript definitions for your development convenience. It can scaffold a TypeScript project if you choose, but does not otherwise require you to opt into transpilation. We'd like you to be able to run Boltzmann apps under deno or in a web worker some day, so we make API choices that move us toward that goal. For full Boltzmann docs, visit the documentation site.
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QUESTION
I'm currently working on a lab report for Brownian Motion using this PDF equation with the intent of evaluating D: Brownian PDF equation
And I am trying to curve_fit it to a histogram. However, whenever I plot my curve_fits, it's a line and does not appear correctly on the histogram. Example Histogram with bad curve_fit
And here is my code:
...ANSWER
Answered 2020-Dec-05 at 16:38There are a few things here. I don't think x and y were ever flipped, or at least when I assumed they weren't, everything seemed to work fine. I also cleaned up a few parts of the code, for example, I'm not sure why you call two different histograms; and I think there may have been problems handling the single element tuple of parameters. Also, for curve fitting, the initial parameter guess often needs to be in the ballpark, so I changed that too.
Here's a version that works for me:
QUESTION
I have come across a very strange problem where i do a lot of math and the result is inf or nan when my input is of type , but i get the correct (checked analytically) results when my input is of type . The only library functions i use are np.math.factorial(), np.sum() and np.array(). I also use a generator object to sum over series and the Boltzmann constant from scipy.constants.
My question is essentially this: Are their any known cases where np.int64 objects will behave very differently from int objects?
When i run with np.int64 input, i get the RuntimeWarnings: overflow encountered in long_scalars, divide by zero encountered in double_scalars and invalid value encountered in double_scalars. However, the largest number i plug into the factorial function is 36, and i don't get these warnings when i use int input.
Below is a code that reproduces the behaviour. I was unable to find out more exactly where it comes from.
...ANSWER
Answered 2020-Dec-02 at 11:16- Numpy's
int64is a 64-bit integer, meaning it consists of 64 places that are either 0 or 1. Thus the smallest representable value is-2**63and the biggest one is2**63 - 1 - Python's
intis essentially unlimited in length, so it can represent any value. It is equivalent to aBigIntegerin Java. It's stored as a list ofint64s essentially that are considered a single large number.
What you have here is a classic integer overflow. You mentioned that you "only" plug 36 into the factorial function, but the factorial function grows very fast, and 36! = 3.7e41 > 9.2e18 = 2**63 - 1, so you get a number bigger than you can represent in an int64!
Since int64s are also called longs this is exactly what the warning overflow encountered in long_scalars is trying to tell you!
QUESTION
I need to import some functions from several files into a Jupyter Notebook, when I try to do this I get the module not found error despite all necessary files being present.
The original import code looks like this:
...ANSWER
Answered 2020-Nov-04 at 16:35the reason why your sys.path.append statements have no effect is that you start the paths with a trailing "/", which indicates that they are absolute paths, even though they should not be.
You could either add the full paths to the modules you would like to import or, if you want to use relative paths, do something like this:
QUESTION
I have an admittedly very basic problem: I need to compare two numbers of type double for >=. For some reason, however, my code evaluates to true for values I know to be less than the threshold.
EDIT: My code (the error occurs in the countTrig() method of the Antenna class):
ANSWER
Answered 2020-Sep-19 at 17:34You have a typo.
QUESTION
In the article that I am interested in, it states that the data is well represented with a Maxwellian distribution and it also provides a Mean speed (307 km/s) and 1 sigma uncertainty (47 km/s) for the distribution.
Using the provided values, I have attempted to re-generate the data and then fit it with the Maxwellian distribution using the python scipy.stats.
As it described in here, maxwell function in scipy takes two input, 1) "loc" which shifts the x variable and 2) "a" parameter which corresponds to the parameter "a" in the maxwell-Boltzmann equation.
In my case, I have neither of these parameters, so using the Mean and variance (sigma^2) description in wiki page, I have attempted to calculate the "a" and "loc" parameter. Both mean and sigma parameters are only dependent on "a" parameter.
The first problem I have encountered was the "a" parameter that I get from Mean (a = 192.4) and sigma (a = 69.8) are different from each other. The second problem is that I don't know how can I obtain the exact loc (shift) value from Mean and sigma.
Based on the shape of the distribution (where mean speed values fall in the graph, check figure 2), I tried to guess the "loc" value and together with the "a" value obtained from sigma (a = 69.8), I have generated and fitted the data. Approximately it seems correct, but I don't know the answer to the questions I mentioned above and I need some expert's guidance on this. I appreciate any help.
...ANSWER
Answered 2020-Aug-08 at 01:57Well, mean value is affected by location, and sigma won't.
So compute a from sigma, compute mean as if loc=0, find the difference and assign it to location, sample 100K RVs to check if
sampled mean/stddev are close enough.
Code, Python 3.8, Windows 10 x64
QUESTION
I'm currently doing an DeepLearning course in Udemy. I am currently designing an Restricted Boltzmann machine in which my training runs perfectly, but I ended up with this error while testing
IndexError: The shape of the mask [1, 1682] at index 0 does not match the shape of the indexed tensor [100, 1682] at index 0
...ANSWER
Answered 2020-May-28 at 17:25In the test loop, you're re-using a variable of the training phase, which I think (you didn't provide the full stacktrace) is just a typo:
QUESTION
Can anyone explain how can one explain ensemble average concept as i have the working code in Scilab below which demonstrates particles experiencing attraction and repulsion when they comes e=to each other (like the LJ potential) and one sees that the speed distribution obtained in my code matches with Maxwell Boltzmann curve.
Take N=25 tf=25 dt=0.02 and V0=1
ANSWER
Answered 2020-May-13 at 16:45i is not incremented in the while i < n .... end instruction this explains why you got an infinite loop. I do not know what your algorithm is intended to do. May be you have to add something like i=i+1 just before the end of the while loop (see in the code below: "may be here")
QUESTION
enter image description herefor my exercise sheet, I need to write a function which find the x value for given y value of a function (called Maxwell_Boltzmann) without any library function. So I tried to define the function ( called most_probable_speed) which at first, find the maximum value of the y value of Maxwell_Boltzmann, and then find for which x (which is defined as v in my code), the maximum is reached. I did this with a for and if loop trying to print v, but it doesnt print me the parameter v for which the maximun is reached but gives me the entire vector v. Has anyone any idea how I could print the parameter v, for which y is reached ?
my code is:
...ANSWER
Answered 2020-May-06 at 12:05Since each element of y corresponds to the element of v in the same index (which is the x value you want), you can use enumerate to give you the index of each value and print out the corresponding x rather than the entire vector:
QUESTION
import math
import random
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
ANSWER
Answered 2020-Apr-28 at 21:47There are several issues with
QUESTION
I would like to generate random numbers using a truncated Maxwell-Boltzmann distribution. I know that scipy has built-in Maxwell random variables, but there is no truncated version of it (I am also aware of a truncated normal distribution, which is irrelevant here). I have tried to write my own random variables using rvs_continuous:
...ANSWER
Answered 2020-Apr-24 at 21:28There are several things you can do here.
- For fixed parameters
v_escandv_0,n_0is a constant, so it doesn't need to be calculated in thepdfmethod - You can precalculate values of the PDF at various points 0 through 550 (which is the support of the distribution). Then you can take those points and their values as input to a piecewise linear distribution (which is similar to the one found in C++, but I don't think SciPy has), which you then sample from.
- If you know the distribution's CDF, then there are some additional tricks. One of them is the relatively new k-vector sampling method for sampling a continuous distribution. There are two phases: a setup phase and a sampling phase. The setup phase involves approximating the CDF's inverse via root finding, and the sampling phase uses this approximation to generate random numbers that follow the distribution in a very fast way without having to further evaluate the CDF. For a fixed distribution like this one, if you show me the CDF, I can precalculate the necessary data and the code needed to sample the distribution using that data. Essentially, the only non-trivial part of k-vector sampling is the root-finding step.
- More information on sampling from an arbitrary distribution is found on my sampling methods page.
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