Investment and risk technologies maintained by Fortitudo Technologies.

Related tags

Data Visualizationfortitudo.tech
Overview

Fortitudo Technologies Open Source

This package allows you to freely explore open-source implementations of some of our fundamental technologies under the GNU General Public License, Version 3.

Fortitudo Technologies is a fintech company offering novel software solutions as well as quantitative and digitalization consultancy to the investment management industry. For more information, please visit our website.

Installation Instructions

Installation can be done via pip:

pip install fortitudo.tech

For best performance, we recommend that you install the package into a conda environment and let conda handle the installation of dependencies before installing the package using pip. You can do this by following these steps:

conda create -n fortitudo.tech python=3.9 scipy -y
conda activate fortitudo.tech
conda install -c conda-forge cvxopt=1.2.6 -y
pip install fortitudo.tech

Contributing

You are very welcome to contribute to this package by forking the github repository and creating pull requests. Pull requests should always be sent to the dev branch. We especially appreciate contributions in relation to packaging, e.g., making the package available on conda-forge or improving pip dependencies.

Using the conda environment specified in the requirements.yml file and located in the root directory is the easiest way to start contributing to the code.

The style guide mostly follows PEP 8, but it uses some important modifications that can be found in .vscode/settings.json. If you use Visual Studio Code, you can use these settings to make sure that your code follows the basic rules of the style guide. The most important modifications/additions are:

  1. We allow line length to be 99 characters for both code and docstrings,
  2. We allow the use of capital I as a variable,
  3. We use type hints introduced in PEP 484.

We generally follow naming conventions with descriptive variable and function names, but we often use short variable names for the very mathematical parts of the code to replicate the variables used in the references. We believe this makes it easier to link the code to the theory.

We encourage you to keep individual contributions small in addition to avoid imposing object-oriented design patterns. We are unlikely to accept contributions that use inheritance without exceptionally good reasons and encourage you to use composition instead.

Code of Conduct

We welcome feedback and bug reports, but we have very limited resources for support and feature requests.

If you experience bugs with some of the upstream packages, please report these directly to the maintainers of these packages.

Disclaimer

This package is completely separate from our proprietary solutions and therefore not representative of the functionality offered therein.

Comments
  • Bump certifi from 2022.9.24 to 2022.12.7

    Bump certifi from 2022.9.24 to 2022.12.7

    Bumps certifi from 2022.9.24 to 2022.12.7.

    Commits

    Dependabot compatibility score

    Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

    Dependabot commands and options

    You can trigger Dependabot actions by commenting on this PR:

    • @dependabot rebase will rebase this PR
    • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
    • @dependabot merge will merge this PR after your CI passes on it
    • @dependabot squash and merge will squash and merge this PR after your CI passes on it
    • @dependabot cancel merge will cancel a previously requested merge and block automerging
    • @dependabot reopen will reopen this PR if it is closed
    • @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
    • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)
    • @dependabot use these labels will set the current labels as the default for future PRs for this repo and language
    • @dependabot use these reviewers will set the current reviewers as the default for future PRs for this repo and language
    • @dependabot use these assignees will set the current assignees as the default for future PRs for this repo and language
    • @dependabot use this milestone will set the current milestone as the default for future PRs for this repo and language

    You can disable automated security fix PRs for this repo from the Security Alerts page.

    dependencies 
    opened by dependabot[bot] 4
  • CodeQL implementation

    CodeQL implementation

    A cron'ed , simple code analysis implementation by CodeQL to verify the integrity of the python project. A detailed summary is provided in the details for further analysis or rectification.

    opened by GNRain 4
  • v0.5

    v0.5

    • functions initial commit

    • cov and corr bug fixes

    • Examples updated to use the new functions

    • Removed esbonio from vscode settings

    • docs update

    • import refactor

    • docstring update

    • Added functions unit tests

    • Minor improvements

    • Requirements update

    • poetry update

    opened by antonvorobets 1
  • v0.4.2

    v0.4.2

    • Minor refactor of _dual_equality

    • Minor refactor of _hessian_equality

    • _dual_equality and entropy_pooling refactor

    • Test tol increase

    • Minor TNC improvements

    • Poetry update

    • Docs version update

    opened by antonvorobets 1
  • v0.4.1

    v0.4.1

    • requirements update

    • Minor tests refactor

    • Updated time series data with credit spreads

    • Updated time series example to include credit spreads

    • Poetry update

    • Docs update

    opened by antonvorobets 1
  • v0.4

    v0.4

    • Time series data and load_time_series function

    • European option pricing functionality

    • Renamed derivatives.py to option_pricing.py

    • docs update

    • Updated test_data to include time_series

    • Option pricing tests

    • Updated example names

    • Added time series example

    • Docs and README update

    • Minor examples updates

    • pyproject.toml update

    • poetry.lock update

    opened by antonvorobets 1
  • v0.3

    v0.3

    • Initial MeanVariance commit

    • Added mean-variance efficient frontier

    • Removed mean_scalar

    • Optimization refactor

    • Initial docs update

    • Removed CVaR init ValueError raises

    • Various docs updates

    • Added load_parameters function

    • Added tests for load_pnl and load_parameters

    • Data docs updates

    • poetry updates

    • Examples update

    • Docs and typo update

    opened by antonvorobets 1
Releases(v0.8.1)
Owner
Fortitudo Technologies
Fortitudo Technologies' open-source code will be made available through this organization profile.
Fortitudo Technologies
GitHub Repository
Python script to generate a visualization of various sorting algorithms, image or video.

sorting_algo_visualizer Python script to generate a visualization of various sorting algorithms, image or video.

146 Nov 12, 2022
Python library that makes it easy for data scientists to create charts.

Chartify Chartify is a Python library that makes it easy for data scientists to create charts. Why use Chartify? Consistent input data format: Spend l

Spotify 3.2k Jan 01, 2023
Calendar heatmaps from Pandas time series data

Note: See MarvinT/calmap for the maintained version of the project. That is also the version that gets published to PyPI and it has received several f

Martijn Vermaat 195 Dec 22, 2022
These data visualizations were created for my introductory computer science course using Python

Homework 2: Matplotlib and Data Visualization Overview These data visualizations were created for my introductory computer science course using Python

Sophia Huang 12 Oct 20, 2022
patchwork for matplotlib

patchworklib patchwork for matplotlib test code Preparation of example plots import seaborn as sns import numpy as np import pandas as pd #Bri

Mori Hideto 185 Jan 06, 2023
阴阳师后台全平台（使用网易 MuMu 模拟器）辅助。支持御魂，觉醒，御灵，结界突破，秘闻副本，地域鬼王。

阴阳师后台全平台辅助 Python 版本：Python 3.8.3 模拟器：网易 MuMu ｜ 雷电模拟器 模拟器分辨率：1024*576 显卡渲染模式：兼容（OpenGL） 兼容 Windows 系统和 MacOS 系统 思路： 利用 adb 截图后，使用 opencv 找图找色，模拟点击。使用

简讯 27 Jul 09, 2022
Shaded 😎 quantile plots

shadyquant 😎 This python package allows you to quantile and plot lines where you have multiple samples, typically for visualizing uncertainty. Your d

Mehrad Ansari 13 Sep 29, 2022
Movies-chart - A CLI app gets the top 250 movies of all time from imdb.com and the top 100 movies from rottentomatoes.com

movies-chart This CLI app gets the top 250 movies of all time from imdb.com and

3 Feb 17, 2022
Joyplots in Python with matplotlib & pandas :chart_with_upwards_trend:

JoyPy JoyPy is a one-function Python package based on matplotlib + pandas with a single purpose: drawing joyplots (a.k.a. ridgeline plots). The code f

Leonardo Taccari 462 Jan 02, 2023
a plottling library for python, based on D3

Hello August 2013 Hello! Maybe you're looking for a nice Python interface to build interactive, javascript based plots that look as nice as all those

Mike Dewar 1.4k Dec 28, 2022
Collection of scripts for making high quality beautiful math-related posters.

Poster Collection of scripts for making high quality beautiful math-related posters. The poster can have as large printing size as 3x2 square feet wit

Nattawut Phetmak 3 Jun 09, 2022
Complex heatmaps are efficient to visualize associations between different sources of data sets and reveal potential patterns.

Make Complex Heatmaps Complex heatmaps are efficient to visualize associations between different sources of data sets and reveal potential patterns. H

Zuguang Gu 973 Jan 09, 2023
Visualize your pandas data with one-line code

PandasEcharts 简介 基于pandas和pyecharts的可视化工具 安装 pip 安装 $ pip install pandasecharts 源码安装 $ git clone https://github.com/gamersover/pandasecharts $ cd pand

陈华杰 2 Apr 13, 2022
Python library that makes it easy for data scientists to create charts.

Chartify Chartify is a Python library that makes it easy for data scientists to create charts. Why use Chartify? Consistent input data format: Spend l

Spotify 3.2k Jan 04, 2023
Visualizing weather changes across the world using third party APIs and Python.

WEATHER FORECASTING ACROSS THE WORLD Overview Python scripts were created to visualize the weather for over 500 cities across the world at varying di

G Johnson 0 Jun 12, 2021
Chem: collection of mostly python code for molecular visualization, QM/MM, FEP, etc

chem: collection of mostly python code for molecular visualization, QM/MM, FEP,

5 Sep 02, 2022
又一个云探针

ServerStatus-Murasame 感谢ServerStatus-Hotaru，又一个云探针诞生了（大雾 本项目在ServerStatus-Hotaru的基础上使用fastapi重构了服务端，部分修改了客户端与前端 项目还在非常原始的阶段，可能存在严重的问题 演示站：https://stat

6 Oct 19, 2021
Practical-statistics-for-data-scientists - Code repository for O'Reilly book

Code repository Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python by Peter Bruce, Andrew Bruce, and Peter Gedeck Pub

1.7k Jan 04, 2023
Create SVG drawings from vector geodata files (SHP, geojson, etc).

SVGIS Create SVG drawings from vector geodata files (SHP, geojson, etc). SVGIS is great for: creating small multiples, combining lots of datasets in a

Neil Freeman 78 Dec 09, 2022
simple tool to paint axis x and y

simple tool to paint axis x and y

G705 1 Oct 21, 2021