stochastic | Generate realizations of stochastic processes in python | Analytics library

by crflynn Python Version: 0.7.0 License: MIT

X-Ray Key Features Code Snippets(3)Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | stochastic Summary

stochastic is a Python library typically used in Analytics applications. stochastic has no bugs, it has no vulnerabilities, it has a Permissive License and it has high support. However stochastic build file is not available. You can install using 'pip install stochastic' or download it from GitHub, PyPI.

Generate realizations of stochastic processes in python.

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Support

stochastic has a highly active ecosystem.

It has 235 star(s) with 48 fork(s). There are 13 watchers for this library.

It had no major release in the last 12 months.

There are 8 open issues and 7 have been closed. On average issues are closed in 102 days. There are 6 open pull requests and 0 closed requests.

It has a positive sentiment in the developer community.

The latest version of stochastic is 0.7.0

Quality

stochastic has 0 bugs and 0 code smells.

Security

stochastic has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

stochastic code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

stochastic is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

stochastic releases are available to install and integrate.

Deployable package is available in PyPI.

stochastic has no build file. You will be need to create the build yourself to build the component from source.

stochastic saves you 1112 person hours of effort in developing the same functionality from scratch.

It has 2515 lines of code, 481 functions and 85 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed stochastic and discovered the below as its top functions. This is intended to give you an instant insight into stochastic implemented functionality, and help decide if they suit your requirements.

Sample n colored noise
Sample colored noise
Validate an integer
Set the strength of the discount
Check that value is a number
The rate
Check that the value is nonnegative
Set the drift speed
Ensures that value is a single argument
Make a matplotlib plot
Returns a list of samples from the instanciate instants
Sets the discount

Get all kandi verified functions for this library.

stochastic Key Features

No Key Features are available at this moment for stochastic.

stochastic Examples and Code Snippets

Noisy linear cosine decay .

python

Lines of Code : 92

License : Non-SPDX (Apache License 2.0)

Copy

def noisy_linear_cosine_decay(learning_rate,
                              global_step,
                              decay_steps,
                              initial_variance=1.0,
                              variance_decay=0.55,

Creates a Zero bias for a given strategy .

python

Lines of Code : 87

License : Non-SPDX (Apache License 2.0)

Copy

def _zero_debias(strategy, unbiased_var, value, decay):
  """Compute the delta required for a debiased Variable.

  All exponential moving averages initialized with Tensors are initialized to 0,
  and therefore are biased to 0. Variables initialized

Linear cosine decay .

python

Lines of Code : 82

License : Non-SPDX (Apache License 2.0)

Copy

def linear_cosine_decay(learning_rate,
                        global_step,
                        decay_steps,
                        num_periods=0.5,
                        alpha=0.0,
                        beta=0.001,
                        n

Community Discussions

Trending Discussions on stochastic

How to add new columns to pandas data frame using .loc

is it efficient to define random number generator inside function integrator?

Expectation Maximization using a Poisson likelihood function

how to apply a function on several simulated graphs in R

Encountering a TypeError: can't multiply sequence by non-int of type 'float' when creating an SGD algorithm

How can use multiple indicators() in version5

Cannot print bibliography despite changing backend to biber, print bibliography says empty bibliography

Translating Stata commands into R (Stochastic Frontier Analysis)

Combining NULL and numeric value in Shiny

PyTorch training loop within a sklearn pipeline

QUESTION

How to add new columns to pandas data frame using .loc

Asked 2022-Feb-28 at 21:40

I am calculating very simple daily stock calculations in data frame ( for e.g. SMA, VWAP, RSI etc). After I upgraded to anaconda 3.0, my code stopped working and gives followed error. I don't have much experience in coding and need some help.

KeyError: "Passing list-likes to .loc or [] with any missing labels is no longer supported. The following labels were missing: Index(['RSI', 'ZONE'], dtype='object'). See https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#deprecate-loc-reindex-listlike"

Followed is the code.

...

ANSWER

Answered 2022-Feb-28 at 21:40

A few lines need to be tweaked

Instead of

Source https://stackoverflow.com/questions/71300628

QUESTION

is it efficient to define random number generator inside function integrator?

Asked 2022-Feb-22 at 10:14

Consider an Euler integrator that solves a stochastic differential equation:

...

ANSWER

Answered 2022-Feb-22 at 10:14

Seeding a PRNG if often costly and should usually only be done once during the whole program run so, no, this is not efficient.

I suggest that you break the creation of the PRNG out into a separate function that has a static PRNG (only initialized once).

Source https://stackoverflow.com/questions/71218664

QUESTION

Expectation Maximization using a Poisson likelihood function

Asked 2022-Feb-11 at 15:57

I am trying to apply the expectation-maximization algorithm to estimate missing count data but all the packages in R, such as missMethods, assume a multivariate Gaussian distribution. How would I apply the expectation-maximization algorithm to estimate missing count data assuming a Poisson distribution?

Say we have data that look like this:

...

ANSWER

Answered 2022-Feb-11 at 15:57

Defining x0:

Source https://stackoverflow.com/questions/71053286

QUESTION

how to apply a function on several simulated graphs in R

Asked 2022-Feb-04 at 09:40

I need a vector (or list) of several results of a function on several simulated graphs (eg assortativity). This is to emulate a Monte Carlo procedure, to perform a segregation analysis with stochastic block models instead of Erdos-Renyi models. This allows to differentiate the probability of links between two types of actors due to the design of the data collection, with a method similar to conditional uniform graphs. I have tried unsuccessfully with the following loop:

...

ANSWER

Answered 2022-Feb-04 at 09:40

I think replicate is the thing you may need

Source https://stackoverflow.com/questions/70979920

QUESTION

Encountering a TypeError: can't multiply sequence by non-int of type 'float' when creating an SGD algorithm

Asked 2022-Jan-27 at 08:04

# We first define the observations as a list and then also as a table for the experienced worker's performance.

Observation1 = [2.0, 6.0, 2.0]
Observation2 = [1.0, 5.0, 7.0]
Observation3 = [5.0, 2.0, 1.0]
Observation4 = [2.0, 3.0, 8.0]
Observation5 = [4.0, 4.0, 0.0]
ObservationTable = [
                    Observation1,
                    Observation2,
                    Observation3,
                    Observation4,
                    Observation5
                    ]

# Then we define our learning rate, number of observations, and the epoch counters we will be utilizing (10, 100, and 1000).

LearningRate = 0.01
ObservationCounter = 5
EpochVersion1 = 10
EpochVersion2 = 100
EpochVersion3 = 1000

# Thus, we are now ready to define the Stochastic Gradient Descent Algorithm:

def StochasticGradientDescent(EpochCounter):
    Theta0 = 10.0
    Theta1 = 0.0
    Theta2 = -1.0

    while (EpochCounter != 0):

        ObservationCounter = 5

        while (ObservationCounter >= 0):

            Theta0_Old = float(Theta0)
            Theta1_Old = float(Theta1)
            Theta2_Old = float(Theta2)

            n = 5 - ObservationCounter
            x = ObservationTable [n]
            x0 = float(x[0])
            x1 = float(x[1])
            x2 = float(x[2])

            Theta0_New = Theta0_Old - LearningRate*[(Theta0_Old+Theta1_Old*float(x0)+Theta2_Old*float(x1))-float(x2)]
            Theta1_New = Theta1_Old - LearningRate*[(Theta0_Old+Theta1_Old*float(x0)+Theta2_Old*float(x1))-float(x2)]*float(x0)
            Theta2_New = Theta2_Old - LearningRate*[(Theta0_Old+Theta1_Old*float(x0)+Theta2_Old*float(x1))-float(x2)]*float(x1)

            print(Theta0_New, Theta1_New, Theta2_New)
            ObservationCounter -= 1

        else:
            EpochCounter -= 1
            if (EpochCounter == 0):
               print(Theta0_New, Theta1_New, Theta2_New)


StochasticGradientDescent(int(EpochVersion1))

...

ANSWER

Answered 2022-Jan-27 at 08:04

I do not know very much about stochastic gradient descent but there are two improvements that I spot in your code.

Firstly, the error is caused because you try to multiply a float with a list and add that to a float. This is fixed by using round brackets instead of square:

Source https://stackoverflow.com/questions/70874703

QUESTION

How can use multiple indicators() in version5

Asked 2022-Jan-25 at 14:46

I'm trying to use custom Stochastic and RSI in version5 but it only allows me to use 1 indicator in the script.

I've tried using study but that doesn't work.

How can I fix this?

I've tried removing version version5 and using only study but that breaks the RSI code.

PS - not a programmer. Know very little about coding, trying to learn though!

...

ANSWER

Answered 2022-Jan-25 at 13:23

You can only have 1 indicator() or study() tag in a script.
You have to merge the code of both, like this for example:

Source https://stackoverflow.com/questions/70849218

QUESTION

Cannot print bibliography despite changing backend to biber, print bibliography says empty bibliography

Asked 2022-Jan-12 at 15:03

Hi I have tried a lot of things and gone through several questions posted earlier but I can't seem to get my bibliography to print. I get the following errors:

Empty Bibliography (when I write \printbibliography)
Undefined Control Sequence (when I overwrite file contents for reference.bib in my main.tex)

Things I have tried:

Changing the backend to biber and biblatex both. None worked.
Adding overwrite file contents and reinputting the bib file content in main.tex and then cite them one by one using \citep{}
Changing styles

I have posted all of my code here (main.tex) in case there are some other code lines that might be messing with the use package of bibliography.

...

ANSWER

Answered 2022-Jan-12 at 15:03

Several problems:

\citep is a natbib macro. If you want to use it in biblatex, you must use the natbib option when you load biblatex.
you shouldn't load package more then once. You MUSTN'T load them more than once with different options. An error message will explicitly tell you about the option clash for the geometry package
the syntax \begin{filecontents*}[overwrite]{\references.bib} is wrong, references.bib should just be the filename, not a (non-existent) macro
the note field in the wikipedia entry caused come probelems, so I moved it to another field.

Source https://stackoverflow.com/questions/70683370

QUESTION

Translating Stata commands into R (Stochastic Frontier Analysis)

Asked 2022-Jan-10 at 03:09

I have very little familiarity with Stata, and I am working on interpreting the code below (which concerns stochastic frontier analysis) in order to translate into R:

...

ANSWER

Answered 2022-Jan-10 at 03:08

u_e is just the name supplied for a new variable. What's important is that it contains estimates of minus the natural log of the technical efficiency via E(u|e)

Hence exp(-u_e) is just the estimated technical efficiency.

See https://www.stata.com/manuals/rfrontierpostestimation.pdf

Source https://stackoverflow.com/questions/70647300

QUESTION

Combining NULL and numeric value in Shiny

Asked 2022-Jan-07 at 23:49

I would like to replicate the following R code in Shiny

...

ANSWER

Answered 2022-Jan-07 at 23:49

numericInput default to NA when it's empty. Maybe a workaround can be:

Source https://stackoverflow.com/questions/70627604

QUESTION

PyTorch training loop within a sklearn pipeline

Asked 2021-Dec-29 at 18:42

What I am playing around with right now is to work with PyTorch within a pipeline, where all of the preprocessing will be handled.

I am able to make it work. However, the results I am getting are a bit off. The loss function seems to be not decreasing and gets stuck (presumably in local optima?) as the training loop progresses.

I follow the standard PyTorch training loop and wrap it inside the fit method as this is what sklearn wants:

...

ANSWER

Answered 2021-Dec-29 at 14:32

The problem in this implementation is in the fit method.

We are comparing prediction and design matrix

Source https://stackoverflow.com/questions/70518288

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install stochastic

You can install using 'pip install stochastic' or download it from GitHub, PyPI.
You can use stochastic like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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