_gpt.md

Experiment profiles are a way to automate your Pioreactor's actions from a flat YAML file. Think of it as creating a "script", that a colleagues precisely follows, to control your Pioreactors.

Users can create profiles to control all of their pioreactors (using the common block), or specific unique actions per pioreactor (using the pioreactor block). In the pioreactor block, we have subsections based on the worker names (like worker01, worker02, or pr01, etc.).

The if directive can be included in any action to conditionally execute it or not. The if statement is evaluated when the action is to be executed (i.e., when elapsed_hours has passed).

The if directive is a general boolean expression, and to common operators can be used:

• and,or,not, True, False,( and )

Also included are numbers, and strings. The comparison operators are are the usual operators.

The operators addition +, -, *, and / are allowed on floats, as well. The power of if comes when you combine it with expressions, see below:

Expressions are the method used to get is dynamic data, provided from jobs, during execution of profiles. For example, the following:

pio1:stirring:target_rpm

will fetch the target_rpm from pio1's stirring job at the time the action is to be executed. To use this in an example:

`` stirring: ... - type: update hours_elapsed: 6.0 if: pio1:stirring:target_rpm >= 500 options: target_rpm: 400

``

will check, after 6 hours, if the target_rpm is above 500, and if true, will update the target RPM to 400.

You can also compare against strings. For example, to stop a job if the temperature automation running is equal to thermostat, use:

temperature_automation: ... - type: stop hours_elapsed: 6.0 if: pio1:temperature_automation:automation_name == thermostat

Where do these dynamic values come from? Each job has published_settings that can be referenced (refer to the job's source code to all published_settings for a job, or they are published in MQTT).

Some published settings have are actually nested json blobs, but we need either numbers or strings to compare in our boolean expression. You can index these json blobs in the boolean expression using ., for example:

temperature_automation: ... - type: update hours_elapsed: 6.0 if: pio1:temperature_automation:temperature.temperature <= 30 options: target_temperature: 32

We use temperature.temperature because the temperature published setting is a json blob that looks like the following, and we wish to reference the "temperature" field in the blob: { "temperature": <float>, "timestamp": <8601 timestamp> }

Similar to an if directive using dynamic data, options can also have dynamic data (see notes above for syntax, too). However, to distinguish between a string and an expression, an expression must be wrapped in ${{ ... }}. For example, consider the following update action:

`` pioreactors: worker1: jobs: stirring: actions: - type: start hours_elapsed: 0 options: target_rpm: 500 - type: update hours_elapsed: 12 options: target_rpm: ${{ worker1:stirring:target_rpm + 50 }}

``

This will update the value of target_rpm to whatever its current value is (after 1 hour), and add 50 to it.

You can use the any pioreactor and any job in an expression - you aren't limited to the job your editing. For example, the update below will dynamically set the target_rpm to a function of optical density.

pioreactors: worker1: jobs: stirring: actions: - type: start hours_elapsed: 0 options: target_rpm: 500 - type: update hours_elapsed: 12 options: target_rpm: ${{ worker1:stirring:target_rpm + worker1:od_reading:od1.od * 10 }}

Expressions can reference individual Pioreactors, for example worker1:stirring:target_rpm, but what if you want to specify all Pioreactors in an expression? This is useful for using expressions in the common block. The syntax for this is to use the following

::<job_name>:setting

For example, to conditionally change the stirring RPM in all Pioreactors, and to update it:

common: jobs: stirring: actions: - type: update hours_elapsed: 6 if: ${{ ::stirring:target_rpm <= 500 }} options: target_rpm: 500

You can also use this syntax in options:

common: jobs: stirring: actions: - type: update hours_elapsed: 6 if: ${{ ::stirring:target_rpm <= 500 }} options: target_rpm: ${{ ::stirring:target_rpm + 10 * ::od_reading:od1.od }}

The repeat directive is the most powerful action, as it allows you loop actions over and over again to check for a condition change, update based on state, etc.

The repeat action requires two necessary fields:

• actions: a list of actions (start, stop, update, etc.) that you want to repeat. The field hours_elapsed refers to the start of the loop, not when the profile starts.
• repeat_every_hours: this is a float describing how long, in hours, the loop should last for. For example, repeat an action every 2 hours, or generally: repeat a sequence of actions every X hours.

There is more control using the other optional fields:

• max_hours: this controls how long the loop should run for. For example, if repeat_every_hours is 0.5 (or 30 minutes), and max_hours is 6, then the loop will repeat 12 times before exiting.
• while: this is an expression, like if, that runs at the start of each loop, including the first. For example, the following profile will run media until the OD is less than 3.0. We also remove waste so we don't overflow the vial. This is a really coarse turbidostat, and is just for demonstration - don't use this:
• You can also use the if directive to skip running the entire repeat action, too.

There is also a when action that will check for a condition (defined as an expression in the field condition), and when the condition is true, executes actions in the list actions. For example: `` dosing_automation: actions: - type: when hours_elapsed: 0.08 # start after 5m condition: pr1:growth_rate_calculating:od_filtered.od_filtered > 30 actions: - type: start hours_elapsed: 0.0 options: automation_name: chemostat volume: 0.63 duration: 9 # In minutes, which translates to 0.1 mL every 2.1 minutes

``

Newly introduced into expressions are the functions:

• random() produces a random number between 0 and 1.
• unit() returns the unit the expression is running for
• experiment() returns the experiment the profile is running in
• job_name() returns the job name the expression is a part of
• hours_elapsed() returns the hours since the profile began