ImitationChain

class psynet.trial.imitation_chain.ImitationChainNetwork(*args, **kwargs)[source]

Bases: ChainNetwork

A Network class for imitation chains.

creation_time

the time at which the Network was created.

details

a generic column for storing structured JSON data

failed

boolean indicating whether the Network has failed which prompts Dallinger to ignore it unless specified otherwise. Objects are usually failed to indicate something has gone wrong.

failed_reason

an optional reason the object was failed. If the object is failed as part of a cascading failure triggered from another object, the chain of objects will be captured in this field.

full

Whether the network is currently full

id

a unique number for every entry. 1, 2, 3 and so on…

make_definition()[source]

Derives the definition for the network. This definition represents some collection of attributes that is shared by all nodes/trials in a network, but that may differ between networks.

Suppose one wishes to have multiple networks in the experiment, each characterised by a different value of an attribute (e.g. a different color). One approach would be to sample randomly; however, this would not guarantee an even distribution of attribute values. In this case, a better approach is to use the psynet.trial.chain.ChainNetwork.balance_across_networks() method, as follows:

colors = ["red", "green", "blue"]
return {
    "color": self.balance_across_networks(colors)
}

See psynet.trial.chain.ChainNetwork.balance_across_networks() for details on how this balancing works.

Returns:

  • object – By default this returns an empty dictionary, but this can be customised by subclasses. The object should be suitable for serialisation to JSON.

max_size

How big the network can get, this number is used by the full() method to decide whether the network is full

property1

a generic column that can be used to store experiment-specific details in String form.

property2

a generic column that can be used to store experiment-specific details in String form.

property3

a generic column that can be used to store experiment-specific details in String form.

property4

a generic column that can be used to store experiment-specific details in String form.

property5

a generic column that can be used to store experiment-specific details in String form.

role

The role of the network. By default dallinger initializes all networks as either “practice” or “experiment”

time_of_death

the time at which failing occurred

type

A String giving the name of the class. Defaults to “network”. This allows subclassing.

vars
class psynet.trial.imitation_chain.ImitationChainNode(*args, **kwargs)[source]

Bases: ChainNode

A Node class for imitation chains.

create_definition_from_seed(seed, experiment, participant)[source]

(Built-in) In an imitation chain, the next node in the chain is a faithful reproduction of the previous iteration.

Parameters:
  • seed – The seed being passed to the node.

  • experiment – An instantiation of psynet.experiment.Experiment, corresponding to the current experiment.

  • participant – Current participant, if relevant.

Returns:

  • object – The node’s new definition, which is a faithful reproduction of the seed that it was passed.

creation_time

the time at which the Network was created.

details

a generic column for storing structured JSON data

failed

boolean indicating whether the Network has failed which prompts Dallinger to ignore it unless specified otherwise. Objects are usually failed to indicate something has gone wrong.

failed_reason

an optional reason the object was failed. If the object is failed as part of a cascading failure triggered from another object, the chain of objects will be captured in this field.

id

a unique number for every entry. 1, 2, 3 and so on…

network

the network the node is in

network_id

the id of the network that this node is a part of

participant

the participant the node is associated with

participant_id

the id of the participant whose node this is

property1

a generic column that can be used to store experiment-specific details in String form.

property2

a generic column that can be used to store experiment-specific details in String form.

property3

a generic column that can be used to store experiment-specific details in String form.

property4

a generic column that can be used to store experiment-specific details in String form.

property5

a generic column that can be used to store experiment-specific details in String form.

summarize_trials(trials, experiment, participant)[source]

(Abstract method, to be overridden) This method should summarize the answers to the provided trials. A default method is implemented for cases when there is just one trial per node; in this case, the method extracts and returns the trial’s answer, available in trial.answer. The method must be extended if it is to cope with multiple trials per node, however.

Parameters:
  • trials (list) – Trials to be summarized. By default only trials that are completed (i.e. have received a response) and processed (i.e. aren’t waiting for an asynchronous process) are provided here.

  • experiment – An instantiation of psynet.experiment.Experiment, corresponding to the current experiment.

  • participant – The participant who initiated the creation of the node.

Returns:

  • object – The derived seed. Should be suitable for serialisation to JSON.

time_of_death

the time at which failing occurred

type

A String giving the name of the class. Defaults to node. This allows subclassing.

vars
class psynet.trial.imitation_chain.ImitationChainTrial(*args, **kwargs)[source]

Bases: ChainTrial

A Trial class for imitation chains.

complete

whether the info is ‘complete’, i.e. has received its contents

creation_time

the time at which the Network was created.

details

a generic column for storing structured JSON data

failed

boolean indicating whether the Network has failed which prompts Dallinger to ignore it unless specified otherwise. Objects are usually failed to indicate something has gone wrong.

failed_reason

an optional reason the object was failed. If the object is failed as part of a cascading failure triggered from another object, the chain of objects will be captured in this field.

id

a unique number for every entry. 1, 2, 3 and so on…

make_definition(experiment, participant)[source]

(Built-in) In an imitation chain, the trial’s definition equals the definition of the node that created it.

Parameters:
  • experiment – An instantiation of psynet.experiment.Experiment, corresponding to the current experiment.

  • participant – Optional participant with which to associate the trial.

Returns:

  • object – The trial’s definition, equal to the node’s definition.

network

the network the info is in

network_id

the id of the network the info is in

origin

the Node that created the info.

origin_id

the id of the Node that created the info

property1

a generic column that can be used to store experiment-specific details in String form.

property2

a generic column that can be used to store experiment-specific details in String form.

property3

a generic column that can be used to store experiment-specific details in String form.

property4

a generic column that can be used to store experiment-specific details in String form.

property5

a generic column that can be used to store experiment-specific details in String form.

time_of_death

the time at which failing occurred

type

a String giving the name of the class. Defaults to “info”. This allows subclassing.

vars
class psynet.trial.imitation_chain.ImitationChainTrialMaker(*, id_, trial_class, node_class, network_class=None, chain_type, expected_trials_per_participant, max_trials_per_participant=<class 'psynet.utils.NoArgumentProvided'>, max_trials_per_block=None, max_nodes_per_chain=None, chains_per_participant=None, chains_per_experiment=None, trials_per_node=1, n_repeat_trials=0, target_n_participants=None, balance_across_chains=False, start_nodes=None, check_performance_at_end=False, check_performance_every_trial=False, recruit_mode='n_participants', fail_trials_on_premature_exit=False, fail_trials_on_participant_performance_check=False, propagate_failure=True, wait_for_networks=False, allow_revisiting_networks_in_across_chains=False, assets=None, choose_participant_group=None, sync_group_type=None)[source]

Bases: ChainTrialMaker

A TrialMaker class for imitation chains; see the documentation for ChainTrialMaker for usage instructions.