Russell Ballestrini
1ca6f67c3d
- Add matplotlib.use("Agg") backend configuration to prevent runtime errors in headless environments
- Add error handling guards for script results that might return None
- Fix AI targeting logic to exclude already-fired cells in super hunter and hunter modes
- Update CLAUDE.md with matplotlib best practices
297 lines
12 KiB
YAML
297 lines
12 KiB
YAML
default_max_attempts_per_step: 3
|
|
|
|
# Common processing script for all plotting steps
|
|
common_processing_script: &plotting_script |
|
|
import matplotlib
|
|
matplotlib.use("Agg")
|
|
import matplotlib.pyplot
|
|
import numpy
|
|
import io
|
|
import base64
|
|
import re
|
|
import sympy as sp
|
|
|
|
# Get the user's function input from metadata
|
|
user_function = metadata.get("user_function", "x")
|
|
original_function = user_function
|
|
|
|
try:
|
|
# Support multiple functions separated by semicolon or comma
|
|
function_list = re.split(r'[;,]', user_function)
|
|
function_list = [f.strip() for f in function_list if f.strip()]
|
|
|
|
# Colors for multiple functions
|
|
colors = ['blue', 'red', 'green', 'orange', 'purple', 'brown', 'pink', 'gray']
|
|
|
|
matplotlib.pyplot.figure(figsize=(10, 6))
|
|
|
|
all_y_values = []
|
|
function_info = []
|
|
|
|
for i, func_str in enumerate(function_list):
|
|
# Preprocess each function
|
|
processed_func = func_str.replace('^', '**')
|
|
processed_func = re.sub(r'(?<=\d)(?=[a-zA-Z])', '*', processed_func)
|
|
processed_func = re.sub(r'(?<=[a-zA-Z])(?=\d)', '*', processed_func)
|
|
|
|
# Enhanced function preprocessing
|
|
enhanced_replacements = {
|
|
'arctan': 'atan',
|
|
'arcsin': 'asin',
|
|
'arccos': 'acos',
|
|
'log': 'ln',
|
|
'ln': 'log', # Allow both ln and log
|
|
'abs': 'Abs'
|
|
}
|
|
|
|
parsed_function = processed_func
|
|
for old, new in enhanced_replacements.items():
|
|
parsed_function = re.sub(r'\b' + old + r'\b', new, parsed_function)
|
|
|
|
# Create sympy symbol and parse expression
|
|
x_sym = sp.Symbol('x')
|
|
expr = sp.sympify(parsed_function, locals={'x': x_sym})
|
|
|
|
# Analyze function characteristics for dynamic range (inline)
|
|
func_type = "other"
|
|
if expr.has(sp.sin) or expr.has(sp.cos) or expr.has(sp.tan):
|
|
func_type = "trigonometric"
|
|
elif expr.has(sp.exp):
|
|
func_type = "exponential"
|
|
elif expr.has(sp.log):
|
|
func_type = "logarithmic"
|
|
elif expr.is_polynomial(x_sym):
|
|
degree = sp.degree(expr, x_sym)
|
|
if degree == 1:
|
|
func_type = "linear"
|
|
elif degree == 2:
|
|
func_type = "quadratic"
|
|
elif degree == 3:
|
|
func_type = "cubic"
|
|
elif expr.has(sp.sqrt):
|
|
func_type = "radical"
|
|
elif expr.has(1/x_sym):
|
|
func_type = "rational"
|
|
|
|
# Determine optimal range inline
|
|
if func_type == "trigonometric":
|
|
x_range = (-2*numpy.pi, 2*numpy.pi)
|
|
elif func_type == "exponential":
|
|
x_range = (-3, 3)
|
|
elif func_type == "logarithmic":
|
|
x_range = (0.1, 10)
|
|
elif func_type in ["linear", "quadratic", "cubic"]:
|
|
x_range = (-10, 10)
|
|
elif func_type == "rational":
|
|
x_range = (-10, 10)
|
|
else:
|
|
x_range = (-5, 5)
|
|
|
|
# Prepare x values with dynamic range
|
|
x_vals = numpy.linspace(x_range[0], x_range[1], 400)
|
|
|
|
# Convert to numpy function and evaluate
|
|
func = sp.lambdify(x_sym, expr, 'numpy')
|
|
y = func(x_vals)
|
|
|
|
# Handle complex results
|
|
if numpy.iscomplexobj(y):
|
|
y = numpy.real(y)
|
|
|
|
# Filter out infinite/NaN values for better plotting
|
|
valid_mask = numpy.isfinite(y)
|
|
x_vals_clean = x_vals[valid_mask]
|
|
y_clean = y[valid_mask]
|
|
|
|
if len(y_clean) > 0:
|
|
all_y_values.extend(y_clean)
|
|
color = colors[i % len(colors)]
|
|
matplotlib.pyplot.plot(x_vals_clean, y_clean,
|
|
label=f'y = {func_str}',
|
|
color=color, linewidth=2)
|
|
|
|
# Store function analysis info
|
|
function_info.append({
|
|
'function': func_str,
|
|
'type': func_type,
|
|
'range': x_range
|
|
})
|
|
|
|
# Dynamic y-axis limits based on all functions
|
|
if all_y_values:
|
|
y_min, y_max = numpy.percentile(all_y_values, [5, 95])
|
|
y_range = y_max - y_min
|
|
matplotlib.pyplot.ylim(y_min - 0.1*y_range, y_max + 0.1*y_range)
|
|
|
|
# Enhanced plot styling
|
|
matplotlib.pyplot.title(f'Plot of: {original_function}', fontsize=14, fontweight='bold')
|
|
matplotlib.pyplot.xlabel('x', fontsize=12)
|
|
matplotlib.pyplot.ylabel('y', fontsize=12)
|
|
matplotlib.pyplot.grid(True, alpha=0.3)
|
|
matplotlib.pyplot.legend(fontsize=10)
|
|
|
|
# Generate function analysis inline
|
|
analysis_parts = []
|
|
for info in function_info:
|
|
func_type = info['type']
|
|
if func_type == "quadratic":
|
|
analysis_parts.append(f"'{info['function']}' is a parabola (quadratic function)")
|
|
elif func_type == "linear":
|
|
analysis_parts.append(f"'{info['function']}' is a straight line (linear function)")
|
|
elif func_type == "trigonometric":
|
|
analysis_parts.append(f"'{info['function']}' shows periodic behavior (trigonometric)")
|
|
elif func_type == "exponential":
|
|
analysis_parts.append(f"'{info['function']}' shows exponential growth/decay")
|
|
elif func_type == "logarithmic":
|
|
analysis_parts.append(f"'{info['function']}' is a logarithmic curve")
|
|
else:
|
|
analysis_parts.append(f"'{info['function']}' is a {func_type} function")
|
|
|
|
analysis_text = "; ".join(analysis_parts)
|
|
|
|
buf = io.BytesIO()
|
|
matplotlib.pyplot.tight_layout()
|
|
matplotlib.pyplot.savefig(buf, format='png', dpi=100, bbox_inches='tight')
|
|
matplotlib.pyplot.close()
|
|
buf.seek(0)
|
|
plot_image = base64.b64encode(buf.getvalue()).decode('utf-8')
|
|
|
|
script_result = {
|
|
"plot_image": plot_image,
|
|
"function_analysis": analysis_text,
|
|
"function_info": function_info
|
|
}
|
|
|
|
except Exception as e:
|
|
# Handle errors gracefully with error message plot
|
|
matplotlib.pyplot.figure()
|
|
matplotlib.pyplot.text(0.5, 0.5, f'Error: Invalid function\n"{original_function}"\n\n{str(e)[:100]}...',
|
|
horizontalalignment='center', verticalalignment='center',
|
|
transform=matplotlib.pyplot.gca().transAxes, fontsize=12,
|
|
bbox=dict(boxstyle="round,pad=0.3", facecolor="lightcoral"))
|
|
matplotlib.pyplot.title('Function Error')
|
|
matplotlib.pyplot.axis('off')
|
|
buf = io.BytesIO()
|
|
matplotlib.pyplot.savefig(buf, format='png')
|
|
matplotlib.pyplot.close()
|
|
buf.seek(0)
|
|
plot_image = base64.b64encode(buf.getvalue()).decode('utf-8')
|
|
|
|
script_result = {"plot_image": plot_image, "error": str(e)}
|
|
|
|
sections:
|
|
- section_id: "section_1"
|
|
title: "Math Plotter: Visualizing Functions"
|
|
steps:
|
|
- step_id: "step_1"
|
|
title: "Introduction to Plotting"
|
|
content_blocks:
|
|
- "Welcome to the Math Plotter activity! 📈"
|
|
- "In this activity, you'll learn how to plot mathematical functions and visualize them."
|
|
question: "Are you ready to start plotting? Type 'yes' to begin."
|
|
tokens_for_ai: |
|
|
Determine if the user's response is 'yes' to proceed.
|
|
If the user wants to change the language, categorize as 'set_language'.
|
|
buckets:
|
|
- proceed
|
|
- set_language
|
|
transitions:
|
|
proceed:
|
|
next_section_and_step: "section_1:step_2"
|
|
set_language:
|
|
content_blocks:
|
|
- "Language preference updated. Please continue in your preferred language."
|
|
metadata_add:
|
|
language: "the-users-response"
|
|
counts_as_attempt: false
|
|
next_section_and_step: "section_1:step_1"
|
|
|
|
- step_id: "step_2"
|
|
title: "First Plot - Linear Function"
|
|
content_blocks:
|
|
- "Let's start by plotting a specific linear function! 📏"
|
|
- "We'll plot: y = 2*x + 1"
|
|
question: "Ready to plot y = 2*x + 1? Type 'yes' to see the graph."
|
|
tokens_for_ai: |
|
|
Check if the user entered a valid linear function. Accept any linear function like 'mx + b' format.
|
|
Don't require analysis at this step - just check if it's a valid function.
|
|
If the user wants to change the language, categorize as 'set_language'.
|
|
processing_script: *plotting_script
|
|
|
|
buckets:
|
|
- proceed
|
|
- set_language
|
|
transitions:
|
|
proceed:
|
|
run_processing_script: True
|
|
ai_feedback:
|
|
tokens_for_ai: "Perfect! Here's the linear function y = 2*x + 1 plotted for you. Now you can explore plotting any functions you want!"
|
|
metadata_add:
|
|
user_function: "2*x + 1"
|
|
next_section_and_step: "section_1:step_3"
|
|
set_language:
|
|
content_blocks:
|
|
- "Language preference updated. Please continue in your preferred language."
|
|
metadata_add:
|
|
language: "the-users-response"
|
|
counts_as_attempt: false
|
|
next_section_and_step: "section_1:step_2"
|
|
|
|
- step_id: "step_3"
|
|
title: "Free Exploration - Plot Anything!"
|
|
content_blocks:
|
|
- "🎨 Time to explore! You can plot any function(s) you want."
|
|
- "Try single functions: x**2, sin(x), exp(x), log(x), sqrt(x)"
|
|
- "Try multiple functions: sin(x), cos(x) or x**2, 2*x + 1"
|
|
- "Mix different types: sin(x), x**2, exp(-x)"
|
|
- "Type 'done' when you're ready to finish."
|
|
question: "Enter any function(s) to plot (or 'done' to complete):"
|
|
tokens_for_ai: |
|
|
This is a free exploration step. Accept any valid mathematical function(s).
|
|
If user says 'done', 'finished', 'complete', etc., categorize as 'done'.
|
|
If the user wants to change the language, categorize as 'set_language'.
|
|
Otherwise, if it looks like a valid function, categorize as 'valid_function'.
|
|
processing_script: *plotting_script
|
|
|
|
buckets:
|
|
- valid_function
|
|
- done
|
|
- invalid_function
|
|
- set_language
|
|
transitions:
|
|
valid_function:
|
|
run_processing_script: True
|
|
ai_feedback:
|
|
tokens_for_ai: "Great exploration! Here's your plot. Try another function or type 'done' to finish."
|
|
metadata_add:
|
|
user_function: "the-users-response"
|
|
exploration_count: "n+1"
|
|
counts_as_attempt: false
|
|
next_section_and_step: "section_1:step_3"
|
|
done:
|
|
ai_feedback:
|
|
tokens_for_ai: "Excellent exploration! You've completed the math plotting activity."
|
|
metadata_add:
|
|
score: "n+1"
|
|
next_section_and_step: "section_2:step_1"
|
|
invalid_function:
|
|
ai_feedback:
|
|
tokens_for_ai: "That doesn't look like a valid function. Try mathematical expressions like 'x**2' or 'sin(x)'."
|
|
counts_as_attempt: false
|
|
next_section_and_step: "section_1:step_3"
|
|
set_language:
|
|
content_blocks:
|
|
- "Language preference updated. Please continue in your preferred language."
|
|
metadata_add:
|
|
language: "the-users-response"
|
|
counts_as_attempt: false
|
|
next_section_and_step: "section_1:step_3"
|
|
|
|
- section_id: "section_2"
|
|
title: "Plotting Complete"
|
|
steps:
|
|
- step_id: "step_1"
|
|
title: "Completion"
|
|
content_blocks:
|
|
- "Congratulations! You've completed the math plotter activity."
|
|
- "You've learned how to plot and visualize different types of functions."
|