Update docs to say just boa -c path in most cases

boa/__main__.py

@@ -3,7 +3,7 @@ def main():
 
     # Main entry point
     # Can be invoked with `python -m boa`
-    # or just `boa` (see pypoject.toml`
+    # or just `boa` (see pypoject.toml`)
     _main()
 
 

boa/plot.py

@@ -3,9 +3,11 @@
 Plotting & EDA CLI
 ###################################
 
-You can launch a basic EDA plot view
+You can launch a basic EDA plot dashboard view
 of your optimization with::
 
+    boa.plot path/to/scheduler.json
+    or
     python -m boa.plot path/to/scheduler.json
 
 

docs/examples/1run_r_streamlined.ipynb

@@ -1507,13 +1507,13 @@
     "To run our script we just need to path the config file to BOA's CLI\n",
     "\n",
     "```python\n",
-    "python -m boa --config-file path/to/config.yaml\n",
+    "boa --config-file path/to/config.yaml\n",
     "```\n",
     "\n",
     "or\n",
     "\n",
     "```python\n",
-    "python -m boa -c path/to/config.yaml\n",
+    "boa -c path/to/config.yaml\n",
     "```"
    ]
   },
@@ -1891,7 +1891,7 @@
     }
    ],
    "source": [
-    "output = !python -m boa -c {config_path}  # we capture ipython terminal output to python variable\n",
+    "output = !boa -c {config_path}  # we capture ipython terminal output to python variable\n",
     "o = \"\\n\".join(ln for ln in output)  # it comes in as a list, we convert to string\n",
     "o = o.replace(str(r_dir),  \"[/path/to/your/dir/]\")  # replace the actual dir with a stand in for privacy reasons\n",
     "Code(o)"

docs/examples/2EDA_from_r_run.ipynb

@@ -24,11 +24,11 @@
     "From the command line, we can issue\n",
     "\n",
     "```python\n",
-    "python -m boa.plot --scheduler-path path/to/scheduler.json\n",
+    "boa.plot --scheduler-path path/to/scheduler.json\n",
     "\n",
     "or\n",
     "\n",
-    "python -m boa.plot -sp path/to/scheduler.json\n",
+    "boa.plot -sp path/to/scheduler.json\n",
     "```\n",
     "\n",
     "```{attention} \n",

docs/examples/example_py_run.rst

@@ -30,7 +30,7 @@ You can start and run your optimization like this:
 
 ..  code-block:: console
 
-    $ python -m boa -c config.json
+    $ boa -c config.json
     Start time: 20221026T210522
     [INFO 10-26 21:05:22] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x0. If that is not the expected value type, you can explicity specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.
     [INFO 10-26 21:05:22] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x1. If that is not the expected value type, you can explicity specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.

docs/index.rst

@@ -24,10 +24,6 @@ Key features
   - Customizable objective functions, multi-objective optimization, acquisition functions, etc
   - Choice of built-in evaluation metrics, but it’s also easy to implement custom metrics
 
-.. important::
-
-    This site is still under construction. More content will be added soon!
-
 Contents
 --------
 .. toctree::

docs/user_guide/getting_started.rst

@@ -30,7 +30,7 @@ Here are instructions on how to install python through Anaconda or miniconda:
 Install boa
 ===========
 
-If using conda and you don't already have a dedicated conda environment for your model::
+If using conda and you don't already have a dedicated conda environment for your model (if using mamba, replace all conda calls with mamba)::
 
      conda create -n boa
      conda activate boa
@@ -42,11 +42,11 @@ or if not using Python, make sure you have a virtual environment create::
 and activate the virtual environment,
 on windows::
 
-    venv\Scripts\activate.bat
+    . venv\Scripts\activate.bat
 
 on linux and mac::
 
-    source tutorial-env/bin/activate
+    . venv/bin/activate
 
 Once your environment is activated, if using conda, run::
 
@@ -78,6 +78,10 @@ so if on either of those, it should install pytorch>2 by default
 but if not and something doesn't work, upgrade pytorch, torchvision,
 and torchaudio
 
+and then activate this environment::
+
+    conda activate boa-dev
+
 :doc:`/contributing`
 
 ********
@@ -86,10 +90,16 @@ Test run
 
 Once everything is installed, run the test script to ensure everything is install properly::
 
-    python -m boa.scripts.run_branin
+    boa.scripts.run_branin
 
 If this test case runs successfully, you can move on to the next steps.
 
+If you encounter a problem, make sure you environment that you install boa into is activated (`conda activate boa`, `. venv/bin/activate`, or `. venv\Scripts\activate.bat` for conda or pip (unix or windows), see above)), and then try again. If it still doesn't work, you can try::
+
+    python -m boa.scripts.run_branin
+
+If this works, it may mean it installed an older version of BOA or that the boa command is not found on your path. If this works, you should be able to run boa commands by using the `python -m boa` instead of just `boa` and the plot command with `python -m boa.plot`.
+
 **********
 Update BOA
 **********

docs/user_guide/package_overview.rst

@@ -45,7 +45,7 @@ Creating a Python launch script (Usually Not Needed)
 ****************************************************
 
 Most of the time you won't need to write a launch script because BOA has an built-in launch script in
-its :mod:`.controller` that is called when calling `python -m boa`. But if you do need more control over your launch script than the default
+its :mod:`.controller` that is called when calling `boa`. But if you do need more control over your launch script than the default
 provides, you can either subclass :class:`.Controller` or write your own launch script. Subclassing
 :class:`.Controller` might be easier if you just need to modify :meth:`.Controller.run` or :meth:`.Controller.initialize_wrapper` or :meth:`.Controller.initialize_scheduler`
 but can utilize the rest of the functions. If you need a lot of customization, writing your own script might be
@@ -63,24 +63,24 @@ you can start your run easily from the command line.
 
 With your conda environment for boa activated, run::
 
-    python -m boa --config-path path/to/your/config/file
+    boa --config-path path/to/your/config/file
 
 or::
 
-    python -m boa -c path/to/your/config/file
+    boa -c path/to/your/config/file
 
 :doc:`BOA's </index>` will save the its current state automatically to a `scheduler.json` file in your output experiment directory every 1-few trials (depending on parallelism settings). It will also save a optimization.csv at the end of your run with the trial information as well in the same directory as scheduler.json. The console will output the Output directory at the start and end of your runs to the console, it will also throughout the run, whenever it saves the `scheduler.json` file, output to the console the location where the file is being saved. You can resume a stopped run from a scheduler file::
 
-    python -m boa --scheduler-path path/to/your/scheduler.json
+    boa --scheduler-path path/to/your/scheduler.json
 
 or::
 
-    python -m boa -sp path/to/your/scheduler.json
+    boa -sp path/to/your/scheduler.json
 
 
 For a list of options and descriptions, type::
 
-    python -m boa --help
+    boa --help
 
 A fuller example using the command line interface can be found  :doc:`here </examples/example_py_run>`