[](https://pypi.org/project/reliability/)
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[](https://github.com/MatthewReid854/reliability/)
[](https://pepy.tech/project/reliability)
[](https://www.gnu.org/licenses/lgpl-3.0.txt)
[](https://doi.org/10.5281/zenodo.3937999)
[](https://reliability.readthedocs.io/en/latest/How%20to%20donate%20to%20the%20project.html)
[](https://form.jotform.com/203156856636058)
*reliability* is a Python library for [reliability engineering](https://en.wikipedia.org/wiki/Reliability_engineering) and [survival analysis](https://en.wikipedia.org/wiki/Survival_analysis). It significantly extends the functionality of scipy.stats and also includes many specialist tools that are otherwise only available in proprietary software.
## Documentation
Detailed documentation and examples are available at [readthedocs](https://reliability.readthedocs.io/en/latest/).
## Key features
- Fitting probability distributions to data including right censored data
- Fitting Weibull mixture models and Weibull Competing risks models
- Fitting Weibull Defective Subpopulation (DS) models, Weibull Zero Inflated (ZI) models, and Weibull Defective Subpopulation Zero Inflated (DSZI) models
- Calculating the probability of failure for stress-strength interference between any combination of the supported distributions
- Support for Exponential, Weibull, Gamma, Gumbel, Normal, Lognormal, Loglogistic, and Beta probability distributions
- Mean residual life, quantiles, descriptive statistics summaries, random sampling from distributions
- Plots of probability density function (PDF), cumulative distribution function (CDF), survival function (SF), hazard function (HF), and cumulative hazard function (CHF)
- Easy creation of distribution objects. Eg. dist = Weibull_Distribution(alpha=4,beta=2)
- Non-parametric estimation of survival function using Kaplan-Meier, Nelson-Aalen, and Rank Adjustment
- Goodness of fit tests (AICc, BIC, AD, Log-likelihood)
- Probability plots on probability paper for all supported distributions
- Quantile-Quantile plots and Probability-Probability plots
- Reliability growth, optimal replacement time, sequential sampling charts, similar distributions, reliability test planners
- Interactive matplotlib functions including crosshairs and distribution explorer
- Physics of Failure (SN diagram, stress-strain, fracture mechanics, creep)
- Accelerated Life Testing Models (24) comprising of 4 distributions (Weibull, Exponential, Normal, Lognormal) and 6 life-stress models (Exponential, Eyring, Power, Dual-Exponential, Dual-Power, Power-Exponential).
- Mean cumulative function and ROCOF for repairable systems
## Installation and upgrading
To install *reliability* for the first time, open your command prompt and type:
```
pip install reliability
```
To upgrade a previous installation of *reliability* to the most recent version, open your command prompt and type:
```
pip install --upgrade reliability
```
If you would like to receive an email notification when a new release of *reliability* is uploaded to PyPI, [NewReleases.io](https://newreleases.io/) provides this service for free.
## Contact
If you find any errors, have any suggestions, or would like to request that something be added, please email alpha.reliability@gmail.com.
Raw data
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"description": "\r\n\r\n[](https://pypi.org/project/reliability/)\r\n[](http://reliability.readthedocs.io/?badge=latest)\r\n[](https://github.com/MatthewReid854/reliability/actions)\r\n[](https://github.com/MatthewReid854/reliability/actions)\r\n[](https://github.com/MatthewReid854/reliability/)\r\n[](https://pepy.tech/project/reliability)\r\n[](https://www.gnu.org/licenses/lgpl-3.0.txt)\r\n[](https://doi.org/10.5281/zenodo.3937999)\r\n[](https://reliability.readthedocs.io/en/latest/How%20to%20donate%20to%20the%20project.html)\r\n[](https://form.jotform.com/203156856636058)\r\n\r\n*reliability* is a Python library for [reliability engineering](https://en.wikipedia.org/wiki/Reliability_engineering) and [survival analysis](https://en.wikipedia.org/wiki/Survival_analysis). It significantly extends the functionality of scipy.stats and also includes many specialist tools that are otherwise only available in proprietary software.\r\n\r\n\r\n\r\n## Documentation\r\nDetailed documentation and examples are available at [readthedocs](https://reliability.readthedocs.io/en/latest/).\r\n\r\n## Key features\r\n- Fitting probability distributions to data including right censored data\r\n- Fitting Weibull mixture models and Weibull Competing risks models\r\n- Fitting Weibull Defective Subpopulation (DS) models, Weibull Zero Inflated (ZI) models, and Weibull Defective Subpopulation Zero Inflated (DSZI) models\r\n- Calculating the probability of failure for stress-strength interference between any combination of the supported distributions\r\n- Support for Exponential, Weibull, Gamma, Gumbel, Normal, Lognormal, Loglogistic, and Beta probability distributions\r\n- Mean residual life, quantiles, descriptive statistics summaries, random sampling from distributions\r\n- Plots of probability density function (PDF), cumulative distribution function (CDF), survival function (SF), hazard function (HF), and cumulative hazard function (CHF)\r\n- Easy creation of distribution objects. Eg. dist = Weibull_Distribution(alpha=4,beta=2)\r\n- Non-parametric estimation of survival function using Kaplan-Meier, Nelson-Aalen, and Rank Adjustment\r\n- Goodness of fit tests (AICc, BIC, AD, Log-likelihood)\r\n- Probability plots on probability paper for all supported distributions\r\n- Quantile-Quantile plots and Probability-Probability plots\r\n- Reliability growth, optimal replacement time, sequential sampling charts, similar distributions, reliability test planners\r\n- Interactive matplotlib functions including crosshairs and distribution explorer\r\n- Physics of Failure (SN diagram, stress-strain, fracture mechanics, creep)\r\n- Accelerated Life Testing Models (24) comprising of 4 distributions (Weibull, Exponential, Normal, Lognormal) and 6 life-stress models (Exponential, Eyring, Power, Dual-Exponential, Dual-Power, Power-Exponential).\r\n- Mean cumulative function and ROCOF for repairable systems\r\n\r\n## Installation and upgrading\r\n\r\nTo install *reliability* for the first time, open your command prompt and type:\r\n\r\n```\r\npip install reliability\r\n```\r\n\r\nTo upgrade a previous installation of *reliability* to the most recent version, open your command prompt and type:\r\n\r\n```\r\npip install --upgrade reliability\r\n```\r\n\r\nIf you would like to receive an email notification when a new release of *reliability* is uploaded to PyPI, [NewReleases.io](https://newreleases.io/) provides this service for free.\r\n\r\n## Contact\r\nIf you find any errors, have any suggestions, or would like to request that something be added, please email alpha.reliability@gmail.com.\r\n",
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