Not an open-source alternative. Burne Ars Praefectus Tribus: Mount Olympus, level 42. Registered: Jun 18, 2014. Mac OS actually has a built in tool for wireless. Mac OS's from the original 1.0 until OS X. I started & ran a business on Turbo Pascal starting in 1987, on an XT clone. It all started with the LAMP stack where LAMP stands for Linux Apache MySQL and PHP. The term refers to the tech stack where a website is running on a Linux server with the MySQL database and PHP programming language. You might hear about WAMP or MAMP which is the same but refers to Windows and Mac OS. This movement started in the late '90s. Multi-platform infrastructure management - (Windows, Mac OS X, Red Hat/CentOS Linux) - 24/7 Security Management (SIEM, Vulnerability Scan, Security Assessments and Audit). Ananke IT Solutions.
This quick start uses macOS in the examples. For instructions about how to install Hugo on other operating systems, see install.
It is recommended to have Git installed to run this tutorial.
Cosmic ritual mac os. For other approaches learning Hugo like book or a video tutorial refer to the external learning resources page.
Step 1: Install Hugo
Homebrew and MacPorts, package managers for macOS, can be installed from brew.sh or macports.org respectively. See install if you are running Windows etc.
To verify your new install:
Step 2: Create a New Site
The above will create a new Hugo site in a folder named quickstart.
Step 3: Add a Theme
See themes.gohugo.io for a list of themes to consider. This quickstart uses the beautiful Ananke theme.
First, download the theme from GitHub and add it to your site's themes directory:
Note for non-git users:
Ananke Mac Os 11
- If you do not have git installed, you can download the archive of the latestversion of this theme from:https://github.com/theNewDynamic/gohugo-theme-ananke/archive/master.zip
- Extract that .zip file to get a 'gohugo-theme-ananke-master' directory.
- Rename that directory to 'ananke', and move it into the 'themes/' directory.
Then, add the theme to the site configuration:
Step 4: Add Some Content
You can manually create content files (for example as content//.) and provide metadata in them, however you can use the new command to do a few things for you (like add title and date):
You can manually create content files (for example as content//.) and provide metadata in them, however you can use the new command to do a few things for you (like add title and date):
Edit the newly created content file if you want, it will start with something like this:
Drafts do not get deployed; once you finish a post, update the header of the post to say draft: false. More info here.
Step 5: Start the Hugo server
Now, start the Hugo server with drafts enabled:
Navigate to your new site at http://localhost:1313/.
Feel free to edit or add new content and simply refresh in browser to see changes quickly (You might need to force refresh in webbrowser, something like Ctrl-R usually works).
Mac Os Download
Step 6: Customize the Theme
The white knight (patrickpasq) mac os. Your new site already looks great, but you will want to tweak it a little before you release it to the public.
Site Configuration
Open up config.toml in a text editor:
Replace the title above with something more personal. Also, if you already have a domain ready, set the baseURL. Note that this value is not needed when running the local development server.
Tip: Make the changes to the site configuration or any other file in your site while the Hugo server is running, and you will see the changes in the browser right away, though you may need to clear your cache.
For theme specific configuration options, see the theme site.
For further theme customization, see Customize a Theme.
Step 7: Build static pages
It is simple. Just call:
Output will be in ./public/ directory by default (-d/--destination flag to change it, or set publishdir in the config file).
See Also
This is a short tutorial for users that want to get into the thick of things right away. However, we highly recommend that users read the other docs provided in order to get a feel for all of the functionality provided in Ananke. The estimators here are based on theory in our paper Semiparametric Inference For Causal Effects In Graphical Models With Hidden Variables (Bhattacharya, Nabi, & Shpitser, 2020).
Following are the necessary packages that need to be imported for this tutorial.
Creating a Causal Graph¶
In Ananke, the most frequently used causal graph is an acyclic directed mixed graph (ADMG). Roughly, directed edges (X rightarrow Y) indicate (X) is a direct cause of (Y) and bidirected edges (X leftrightarrow Y) indicate the presence of one or more unmeasured confounders between (X) and (Y.) Let's say we are studying the efficacy of a new antiretroviral therapy vs. an old one. Call this the treatment (T) where (T=1) represents receiving thenew drug and (T=0) represents receiving the old. Our outcome of interest is the patients CD4 counts post treatment. Thus, our target of interest (in potential outcomes notation) is the counterfactual contrast (psi equiv E[Y(1)] - E[Y(0)].) This is how one may create a causal graph, with additional variables relevant to the given problem.
Identification of the Causal Effect¶
Using Ananke, we can ask whether the effect of a given treatment (T) on a given outcome (Y) is identified or not. We have implemented the one line ID algorithm provided in Nested Markov Properties for Acyclic Directed Mixed Graphs which is sound and complete in identifying (p(Y(t))) or equivalently (p(Y | do(t))). We show how to use this in Ananke through the following example.
Estimation of the Causal Effect¶
Ananke provides an easy interface in order to compute causal effects. First, we instantiate a CausalEffect object.
In this case, it recommends Efficient Generalized AIPW which is to say, that the estimator used to compute the effect in this case looks a lot like Augmented IPW (which is doubly robust). Further, Ananke uses semiparametric theory in order to provide an estimator that achieves the lowest asymptotic variance.
Given the list of estimators, it is up to the user to specify what estimators they want to work with. For instance, if the user decides to use the efficient generalized AIPW, they only need to use the keyword given in front of it, i.e., eff-aipw, when computing the effect. All the nuisance models are fit using generalized linear models provided in the statsmodels. Users interested in using different modeling approaches can refer to the documentation on accessing the functional form ofthe influence functions at the end of this notebook.
Let's load up some toy data and use all of the available estimators in order to compute the causal effect.
In addition, the user can run bootstraps and obtain ((1-alpha)*100%) confidence level for the causal effect point estimate. The user needs to specify two arguments: number of bootstraps n_bootstraps and the significance level (alpha)alpha. The confidence interval can then be obtained via bootstrap percentile intervals, as described in All of Nonparametric Statistics. In this case, the call to thecompute_effect returns three values: the first corresponds to the effect computed on the original data, the second and third are the pre-specified lower and upper quantiles, i.e., ((frac{alpha}{2}, 1 - frac{alpha}{2}).) The default value for (alpha) is set to be (0.05). We illustrate this through the following toy example.
While Ananke has its own built-in esimation strategy for every identifiable causal effect concerning a single treatment and outcome, users may be interested in building their own estimators based on the identifying functionals/nonparametric influence functions. This allows users to use their own preferred estimation strategies such as sample splitting, using their preferred machine learning model etc. Below, we provide an example for a new causal graph reflecting some background knowledge and weare interested in the causal effect of the treatment (T) on the outcome (Y.)
