Kevin/numeric questions (#110)

* adjusted numeric question_type to work with significant figures

* i dont understand anything anymore

* finalized numeric_quesiton type

* update version number

* hope test does not fail anymore

stylistic stuff

* hook

* rm output

---------

Co-authored-by: Kevin <[email protected]>
Co-authored-by: floriscalkoen <[email protected]>

Author: 3 people

.gitignore

@@ -146,3 +146,6 @@ dist*
 
 # don't add ruff cache
 *.ruff_cache*
+
+# don't add questions to public github
+questions/*.json

notebooks/6_cross_shore_transport.ipynb

@@ -482,7 +482,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "727482ed-a483-426c-b08a-2ed418650823",
+   "id": "843e7e78-4c57-4741-8db3-6dddc232670f",
    "metadata": {},
    "outputs": [],
    "source": [

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "coastal-dynamics"
-version = "0.0.6"
+version = "0.0.7"
 description = "Jupyterbook for Delft Technical University Coastal Systems"
 authors = ["Floris Calkoen"]
 license = "MIT"

scripts/python/hash_questions.py

@@ -12,7 +12,11 @@
 def process_questions(questions):
     """Process and hash answers within the questions dictionary based on question type."""
     for _, q_data in questions.items():
-        q_data["answer"] = cd.hash_answer(q_data.get("answer"), q_data.get("type"))
+        print(1)
+        q_data["answer"] = cd.hash_answer(
+            q_data.get("answer"), q_data.get("type"), sig_figs=q_data.get("sig_figs")
+        )
+        print(2)
     return questions
 
 

src/coastal_dynamics/__init__.py

@@ -2,7 +2,7 @@
 
 __author__ = """Floris Calkoen"""
 __email__ = "[email protected]"
-__version__ = "0.0.6"
+__version__ = "0.0.7"
 
 from .factory import QuestionFactory
 from .io import read_questions, write_questions

src/coastal_dynamics/factory.py

@@ -73,8 +73,8 @@ def _create_numeric_question(self):
             question_text=self.question_data["question"],
             question_answer=self.question_data["answer"],
             question_feedback=self.question_data["feedback"],
-            precision=self.question_data.get(
-                "precision", 0
+            sig_figs=self.question_data.get(
+                "sig_figs", 0
             ),  # Handle precision as optional
         )
 

src/coastal_dynamics/numeric.py

@@ -1,5 +1,6 @@
 from typing import Literal
 
+import numpy as np
 import panel as pn
 
 import coastal_dynamics as cd
@@ -11,24 +12,24 @@ class NumericQuestion(Question):
     A class to create and manage a numeric answer question widget.
 
     This class creates a numeric question using Panel widgets.
-    It supports a question text, numeric answer, and precision for the answer.
+    It supports a question text, numeric answer, and sig_figs for the answer.
 
     Attributes:
         correct_answer (float): The correct numeric answer.
-        precision (int): The precision of the numeric answer.
+        sig_figs (int): The number of significant figures of the numeric answer.
         answer_input (pn.widgets.FloatInput): The widget for inputting the answer.
     """
 
     def __init__(
         self,
         question_name: str,
         question_text: str,
-        question_answer: float,
+        question_answer: str,
         question_feedback: dict[Literal["correct", "incorrect"], str],
-        precision: int | None = None,
+        sig_figs: int | None = None,
     ):
         self.correct_answer = question_answer
-        self.precision = precision
+        self.sig_figs = sig_figs
         self.answer_input: pn.widgets.FloatInput
 
         super().__init__(question_name, question_text, question_feedback)
@@ -43,12 +44,26 @@ def check_answer(self, event) -> None:
         """Check the submitted answer against the correct answer."""
         try:
             user_answer = float(self.answer_input.value)
-            if self.precision:
-                user_answer = round(user_answer, self.precision)
-            if self.hash_answer(user_answer, "numeric") == self.correct_answer:
+
+            if self.sig_figs:
+                user_answer = np.format_float_positional(
+                    user_answer,
+                    precision=self.sig_figs,
+                    unique=False,
+                    fractional=False,
+                    trim="k",
+                )
+
+            hashed_user_answer = self.hash_answer(
+                user_answer, "numeric", sig_figs=self.sig_figs
+            )
+
+            if hashed_user_answer == self.correct_answer:
                 self.feedback_widget.value = self.feedback["correct"]
+
             else:
                 self.feedback_widget.value = self.feedback["incorrect"]
+
         except ValueError:
             self.feedback_widget.value = "Please enter a valid number."
 
@@ -65,21 +80,28 @@ def serve(self) -> pn.Column:
 if __name__ == "__main__":
     question_data = {
         "question": "What is the relative importance of S2 vs M2?",
-        "answer": 0.33,
-        "precision": 2,
+        "answer": 35,
+        "sig_figs": 2,
     }
 
     nq = NumericQuestion(
         question_name="Q3: Simple numeric question",
         question_text=question_data["question"],
         question_answer=cd.hash_answer(
-            round(float(question_data["answer"]), question_data["precision"]), "numeric"
+            np.format_float_positional(
+                float(question_data["answer"]),
+                precision=question_data["sig_figs"],
+                unique=False,
+                fractional=False,
+                trim="k",
+            ),
+            "numeric",
         ),
         question_feedback={
             "correct": "Correct!...",
             "incorrect": "Incorrect, try again. Please consider that...",
         },
-        precision=question_data["precision"],
+        sig_figs=question_data["sig_figs"],
     )
     nq.serve().show()
     print("done")

src/coastal_dynamics/question.py

@@ -46,6 +46,6 @@ def check_answer(self, event) -> None:
         msg = "This method should be implemented by subclasses"
         raise NotImplementedError(msg)
 
-    def hash_answer(self, answer, question_type):
+    def hash_answer(self, answer, question_type, sig_figs=None):
         """Delegate the hashing of an answer to the coastal_dynamics module."""
-        return cd.hash_answer(answer, question_type)
+        return cd.hash_answer(answer, question_type, sig_figs=sig_figs)

src/coastal_dynamics/utils.py

@@ -1,7 +1,8 @@
 import hashlib
+import numpy as np
 
 
-def hash_answer(answer, question_type, precision=None):
+def hash_answer(answer, question_type, sig_figs=None):
     """Hash a single answer or a list of answers based on the question type."""
     if question_type == "multiple_selection":
         # For multiple_selection, directly hash each answer in the list
@@ -13,8 +14,14 @@ def hash_answer(answer, question_type, precision=None):
         # For multiple_choice and numeric, directly hash the answer
         return hashlib.sha256(str(answer).encode()).hexdigest()
     elif question_type == "numeric":
-        if precision:
-            answer = round(float(answer), precision)
+        if sig_figs:
+            answer = np.format_float_positional(
+                float(answer),
+                precision=sig_figs,
+                unique=False,
+                fractional=False,
+                trim="k",
+            )
         return hashlib.sha256(str(answer).encode()).hexdigest()
     else:
         msg = f"Unsupported question type: {question_type}"