feat: functions operating on all elements in the time series

[gunnarstaff]

Added statistical calculations like time weighted mean, time weighted standard deviation and min/max operators that work over all the values in the time series and not element wise

Description

Only adding new functions.

Motivation and Context

The new functionality allows you to solve problems that previously have been very hard to solve. Now we can create time series based on statistical properties from the entire time series. We can create scatter plots that are overlayed in the time series plot,+++

How Has This Been Tested?

All four functions have been tested on a real time series taken from the demo tenant.
Tested on Windows 11 with python 3.10.7

Screenshots (if appropriate):

Types of changes

• Bug fix (non-breaking change which fixes an issue)
• Refactor (non-breaking change which improves implementation)
• Performance (non-breaking change which improves performance. Please add associated performance test and results)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to change)
• Non-functional change (xml comments/documentation/etc)

Contributor Checklist:

• My code follows the code style of this project.
• I have added an example of my new feature and included it in the documentation.
• My change requires a change to the documentation.
• I have updated the documentation accordingly.
• I have read the CONTRIBUTING document.
• I have added tests to cover my changes.
• All new and existing tests passed.
• [ x My Pull Request name follows the naming convention fix: <description>, feat: <description>, etc.

Reviewer Checklist for Charts compliant functions:

• The docstrings of the new function follow the contributing guidelines.
• The new function is professionally documented
• The new function and associated scripts are covered by one or more unit tests and code coverage did not decrease.
• The new function is accompanied by an example and it is included in the Gallery of Charts.
• The new function is reviewed in Chromatic. Access the storybook build results url and comment, approve or deny.
• All function inputs, arguments, and outputs have a supported data type and have human readable names.
• No code language is included in the description of the function or parameters (e.g use "polynomial order" instead of "poly_order")

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 91.23%. Comparing base (87eb6a0) to head (14afedd).
Report is 1 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #274      +/-   ##
==========================================
+ Coverage   91.14%   91.23%   +0.08%     
==========================================
  Files         108      109       +1     
  Lines        3929     3969      +40     
  Branches      852      858       +6     
==========================================
+ Hits         3581     3621      +40     
  Misses        212      212              
  Partials      136      136              

Files	Coverage Δ
indsl/ts_utils/__init__.py	100.00% <100.00%> (ø)
indsl/ts_utils/array_operations.py	100.00% <100.00%> (ø)

[github-actions]

Unit Test Results

    15 files  ± 0      15 suites  ±0   26m 30s ⏱️ +10s
 1 130 tests + 8   1 130 ✅ + 8  0 💤 ±0  0 ❌ ±0 
11 163 runs  +84  11 155 ✅ +84  8 💤 ±0  0 ❌ ±0 

Results for commit 14afedd. ± Comparison against base commit 87eb6a0.

♻️ This comment has been updated with latest results.

blocking review