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#!/usr/bin/env python3
from __future__ import annotations
from psychopy import constants, core, event, gui, visual
from collections import namedtuple
import frensch_procedures
import random
from pprint import pprint
import pandas as pd
import pickle
DisplayVariable = namedtuple("DisplayVariable", ["name", "values"])
DisplayProcedure = namedtuple("DisplayProcedure", ["procedure", "solution"])
intro_text = """Vielen Dank dass Sie bei unserem Experiment zum menschlichen Lernen teilnehmen!
Im folgenden müssen sie verschiedene Rechenaufgaben lösen.
Verwenden Sie die gewohnten Rechenregeln und geben sie Ihre Lösung bitte immer als zweistellige Zahl ein, und bestätigen mit Enter.
Die Werte der Variablen werden oben am Bildschirm angezeigt. Manche Variablen haben mehrere mögliche Werte; "_2" besagt z.B. das der zweite Wert zu verwenden ist.
Nach jeder Aufgabe können Sie kurz pausieren.
Drücken Sie die Leertaste um zu beginnen"""
def experiment_shutdown():
WIN.close()
core.quit()
WIN = visual.Window((2560, 1440), fullscr=True, units="pix")
MONITOR_FPS = 60
# TRAIN_TRIALS = 1
# TEST_TRIALS = 1
TRAIN_TRIALS = 75
TEST_TRIALS = 50
ORDER_CONDITIONS = ["fixed", "random", "blocked"]
PROCEDURE_KEYS = ["1", "2", "3", "4", "5", "6", "overall"]
# Cancel experiment anytime with Esc
event.globalKeys.add(key="escape", func=experiment_shutdown, name="shutdown")
def generate_variable_display(varx: list[DisplayVariable], x_positions: list[int]):
assert len(varx) == len(x_positions)
stims = []
def gen_value_stims(values, x, y, offset):
for value in values:
y -= offset
value_stim = visual.TextBox2(
WIN,
pos=(x, y),
text=value,
# size=200,
letterHeight=100,
alignment="center",
)
stims.append(value_stim)
y = 650
offset = 120
for var, x_pos in zip(varx, x_positions):
stim_var = visual.TextBox2(
WIN,
pos=[x_pos, y],
text=var.name,
# size=[1000, 1000],
letterHeight=50,
alignment="center",
)
stims.append(stim_var)
gen_value_stims(var.values, x_pos, y, offset)
return stims
def generate_procedure_display(procedure: DisplayProcedure, position):
stim_procedure = visual.TextBox2(
WIN,
pos=position,
text=procedure.procedure,
# size=[1000, 1000],
letterHeight=50,
alignment="center",
)
return stim_procedure
def generate_all_watersamples(n):
samples = []
for _ in range(n):
samples.append(frensch_procedures.constrained_WaterSample())
return samples
def run_trial(water_sample, procedure_keys: list, condition):
water_sample.print_all()
if condition == "random":
random.shuffle(procedure_keys)
solid = DisplayVariable("SOLID", [water_sample.solid])
algae = DisplayVariable("ALGAE", [water_sample.algae])
lime = DisplayVariable("LIME", water_sample.lime)
toxin = DisplayVariable("TOXIN", water_sample.toxin)
x_positions = [-800, -400, 400, 800]
stims = generate_variable_display([solid, algae, lime, toxin], x_positions)
procedures = water_sample.procedure_dict()
answers = []
proc_x = -800
proc_y = -100
answ_x = 0
answ_y = -100
y_offset = 80
for proc in procedure_keys:
p = DisplayProcedure(procedures[proc][1](), procedures[proc][0]())
p = generate_procedure_display(p, (proc_x, proc_y))
stims.append(p)
proc_y -= y_offset
stim_answer_box = visual.TextBox2(
WIN,
"",
letterHeight=50,
pos=(answ_x, answ_y),
size=[150, 70],
editable=True,
fillColor="white",
color="black",
alignment="center",
)
stims.append(stim_answer_box)
answ_y -= y_offset
not_finished = True
answer = "not answered"
start_time = core.monotonicClock.getTime()
while not_finished:
stim_answer_box.hasFocus = True
for stim in stims:
stim.draw()
WIN.flip()
answer = stim_answer_box.text
if "\n" in answer:
if answer[0].isdigit() and answer[1].isdigit():
not_finished = False
else:
stim_answer_box.text = answer[:-1]
if len(answer) > 2:
stim_answer_box.text = stim_answer_box.text[:2]
answer_time = core.monotonicClock.getTime() - start_time
answers.append((answer.replace("\n", ""), answer_time))
event.waitKeys(keyList=["space"])
return answers, procedure_keys
pause = visual.TextBox2(
WIN,
"""Drücken Sie die Leertaste um mit der nächsten Aufgabe fortzufahren""",
letterHeight=50,
alignment="center",
)
intro = visual.TextBox2(WIN, intro_text, letterHeight=30, alignment="center")
intro.draw()
WIN.flip()
event.waitKeys(keyList=["space"])
train_procedures = PROCEDURE_KEYS[:-1]
random.shuffle(train_procedures)
transfer_procedure = train_procedures[-1]
train_procedures = train_procedures[:-1]
train_procedures.append(PROCEDURE_KEYS[-1])
print("test/train")
print(train_procedures)
test_procedures = train_procedures
test_procedures[2] = transfer_procedure
print(test_procedures)
all_samples = generate_all_watersamples(TRAIN_TRIALS + TEST_TRIALS)
pprint(all_samples)
results = {}
for i in range(TRAIN_TRIALS):
answer, procedure_keys = run_trial(
all_samples[i], train_procedures, ORDER_CONDITIONS[0]
)
answer_dict = {}
answer_dict["procedure_order"] = procedure_keys
for proc, key in zip(answer, procedure_keys):
answer_dict[key] = {"answer": proc[0], "time": proc[1]}
results[f"train_{i}"] = answer_dict
pause.draw()
WIN.flip()
event.waitKeys(keyList=["space"])
train_procedures[2] = transfer_procedure
for i in range(TEST_TRIALS):
answer, procedure_keys = run_trial(
all_samples[TRAIN_TRIALS + i], train_procedures, ORDER_CONDITIONS[0]
)
answer_dict = {}
answer_dict["procedure_order"] = procedure_keys
for proc, key in zip(answer, procedure_keys):
answer_dict[key] = {"answer": proc[0], "time": proc[1]}
results[f"test_{i}"] = answer_dict
pause.draw()
WIN.flip()
event.waitKeys(keyList=["space"])
pprint(results)
df = pd.DataFrame.from_dict(results, orient="index")
df.to_csv("vp_results.csv")
with open("vp.pkl", "wb") as file:
pickle.dump(results, file)
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