first experiment ready

1 files changed, 87 insertions, 20 deletions

diff --git a/master_thesis/frensch_task.py b/master_thesis/frensch_task.py
index ad67ee5..e74117d 100644
--- a/master_thesis/frensch_task.py
+++ b/master_thesis/frensch_task.py
@@ -5,11 +5,24 @@ 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()
@@ -18,8 +31,10 @@ def experiment_shutdown():
 
 WIN = visual.Window((2560, 1440), fullscr=True, units="pix")
 MONITOR_FPS = 60
-TRAIN_TRIALS = 1  # 75
-TEST_TRIALS = 1  # 50
+# 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"]
 
@@ -76,8 +91,14 @@ def generate_procedure_display(procedure: DisplayProcedure, position):
     return stim_procedure
 
 
-def run_trial(procedure_keys: list, condition):
-    water_sample = frensch_procedures.constrained_WaterSample()
+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":
@@ -128,23 +149,29 @@ def run_trial(procedure_keys: list, condition):
                 stim.draw()
             WIN.flip()
             answer = stim_answer_box.text
-            # TODO: prevent nondigits
-            # answer.replace("\n", "")
-            # if not answer.isdigit():
-            #     stim_answer_box.text = ""
-            #     answer = ""
-            if "\n" in stim_answer_box.text:
-                not_finished = False
+            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
-        print(f"time to answer: {answer_time}")
-        answers.append(answer.replace("\n", ""))
+        answers.append((answer.replace("\n", ""), answer_time))
 
     event.waitKeys(keyList=["space"])
 
-    return answers
+    return answers, procedure_keys
 
 
-intro = visual.TextBox2(WIN, "Introduction")
+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"])
@@ -154,13 +181,53 @@ 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)
 
 
-for _ in range(TRAIN_TRIALS):
-    print(f"Answer: {run_trial(train_procedures, ORDER_CONDITIONS[0])}")
+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
-print(train_procedures)
-for _ in range(TEST_TRIALS):
-    print(f"Answer: {run_trial(train_procedures, ORDER_CONDITIONS[0])}")
+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)