Using Pre-installed Python Libraries
The libraries below are pre-installed in CalcTree’s Python environment. To use them, simply import them in your script as you would normally.
CalcTree provides a set of pre-installed Python libraries ready for use in your scripts. These include numerical, plotting, structural, geotechnical, and simulation packages commonly used in engineering workflows.
To use any library, you must import it at the top of your Python script as you would in a standard Python environment:
import numpy as np
import matplotlib.pyplot as pltAvailable Libraries
The following libraries are currently supported in CalcTree:
2D structural analysis in Python
(Resilient Design for the Next Generation of Buildings) seismic engine documentation developed at ARUP
A teaching aid for 1-D shear-force and bending-moment diagrams
Optimize energy assets using mixed-integer linear programming
A Python package for calculating structures according to Eurocodes
A Python package to create new DXF documents and read/modify/write existing DXF
An open-source, Python-based 3-D structural geological modeling software
A general-purpose geotechnical package
handcalcs Python library for converting Python calculations into rendered latex
Joyplots in Python with matplotlib & pandas
Plotting with Python
The fundamental package for scientific computing with Python
Finite element applications for simulating the response of structural and geotechnical systems subjected to earthquakes
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Python 3 library to automate and build finite element analysis (FEA) models in Calculix
Python Continuous Beam Analysis
Python bindings to Frame3DD
A 3D structural engineering finite element library for Python
Python Spatial Analysis Library
Machine learning in Python
Software for mathematics, science, and engineering. It includes modules for statistics, optimization, integration, linear algebra, Fourier transforms, signal and image processing, ODE solvers, and more.
Statistical data visualization in Python
Analysis of an arbitrary cross-section in Python using the finite element method
A process-based discrete-event simulation framework
Structural Analysis Library for Python based on the direct stiffness method
Symbolic mathematics
An extension of GeoJSON that encodes topology
Roadmap and Feedback
We’re actively expanding this list based on user demand. You can view the current roadmap and request support for additional libraries here.
Let us know which packages are essential to your workflow.
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