Db a Weighting Calculator

DBA Weighting Calculator: Understand Your Acoustic Significance :root { –primary-color: #004a99; –success-color: #28a745; –background-color: #f8f9fa; –text-color: #333; –border-color: #ddd; –shadow-color: rgba(0, 0, 0, 0.1); –card-background: #fff; –input-border: #ccc; –error-color: #dc3545; } body { font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; background-color: var(–background-color); color: var(–text-color); line-height: 1.6; margin: 0; padding: 20px; } .container { max-width: 960px; margin: 20px auto; background-color: var(–card-background); padding: 30px; border-radius: 8px; box-shadow: 0 4px 15px var(–shadow-color); } h1, h2, h3 { color: var(–primary-color); text-align: center; margin-bottom: 20px; } h1 { font-size: 2.5em; } h2 { font-size: 1.8em; border-bottom: 2px solid var(–primary-color); padding-bottom: 10px; margin-top: 30px; } h3 { font-size: 1.4em; margin-top: 25px; } .loan-calc-container { background-color: var(–card-background); padding: 25px; border-radius: 8px; 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DBA Weighting Calculator

Calculate and visualize the weighting of your acoustic measurements to understand their significance and inform treatment decisions.

Acoustic Measurement Input

Enter the measured sound pressure level in decibels (dB).
Enter the frequency of the measurement in Hertz (Hz).
A-weighting B-weighting C-weighting D-weighting Z-weighting (Flat) Select the frequency weighting curve applied (e.g., A, C).
Enter the reference sound pressure level for comparison (typically 94 dB for A and C weighting).
Enter the minimum audible threshold or baseline for weighting calculation (often 0 dB).

Calculation Results

Weighted Value: dB
Weighting Difference: dB
Acoustic Significance:

Frequency Weighting Comparison

Comparison of applied weighting factors across different frequencies.

Weighting Table

Input Parameter Value Unit
Measurement Value dB
Frequency Hz
Selected Weighting N/A
Reference Level dB
Threshold Level dB
Weighted Value dB
Weighting Difference dB

What is DBA Weighting?

DBA weighting, often referred to in contexts like the DBA weighting formula, is a signal processing technique used to adjust the measured amplitude of sound signals based on frequency. It's not a direct measurement of decibels alone, but rather a method to represent how humans perceive loudness at different frequencies. Our DBA weighting calculator helps you visualize and quantify this effect.

The primary goal of applying a weighting curve, such as A-weighting (dBA), C-weighting (dBC), or Z-weighting (flat), is to make sound level meter readings more representative of human hearing sensitivity. Our hearing is not equally sensitive to all frequencies. We are most sensitive to mid-range frequencies (around 1kHz to 4kHz) and less sensitive to very low and very high frequencies. DBA weighting, in particular, mimics this sensitivity curve.

Who Should Use It? Anyone involved in acoustic measurements, sound engineering, environmental noise monitoring, workplace safety, or audio system calibration can benefit from understanding DBA weighting. This includes:

  • Audio engineers and acousticians analyzing room acoustics.
  • Environmental consultants monitoring noise pollution.
  • Occupational health and safety professionals assessing noise exposure risks.
  • Musicians and producers optimizing their studio environments.
  • Home theater enthusiasts seeking accurate sound reproduction.

Common Misconceptions A frequent misconception is that dBA readings directly represent the absolute loudness of a sound. While dBA is more aligned with perceived loudness than raw dB, it's still a relative measure. Another is that all weighting curves are the same; however, A, C, and Z weighting serve different purposes and have distinct frequency responses. Our DBA weighting calculator provides clarity on these distinctions.

DBA Weighting Formula and Mathematical Explanation

The core of DBA weighting involves applying a frequency-dependent filter to the raw sound pressure level (SPL) measurement. The calculation essentially modifies the measured decibel value based on the frequency of the sound and the specific weighting curve selected.

For A-weighting, the formula is derived from standardized filter characteristics. A simplified representation of how the weighting factor (W) is applied is:

Weighted dB = Measured dB + W(f)

Where W(f) is the weighting factor in decibels at a given frequency (f). This factor is negative for low and high frequencies (where human hearing is less sensitive) and close to zero for mid-range frequencies.

The actual calculation of W(f) for A-weighting involves complex transfer functions, but it's typically pre-programmed into sound level meters and calculators like ours. Our calculator uses lookup tables or simplified approximations to derive the appropriate W(f) based on the input frequency and selected weighting curve.

A general form of the calculation performed by this DBA weighting calculator is:

  1. Determine the weighting factor (W(f)) for the selected curve (A, C, B, D, Z) at the input Frequency.
  2. Calculate the Weighted Value: Weighted Value = Measurement Value (dB) + W(f)
  3. Calculate the Weighting Difference: Weighting Difference = Measurement Value (dB) - Weighted Value = -W(f)
  4. Determine Acoustic Significance based on the Weighting Difference and potentially the Reference Level and Threshold Level. For simplicity, we can categorize:
    • Large negative difference (high attenuation): Very low perceived loudness.
    • Small negative difference: Loudness close to raw dB.
    • Zero or positive difference (rare for A/C): High perceived loudness relative to raw dB.

Variables Table

Variable Meaning Unit Typical Range / Notes
Measured dB Raw sound pressure level dB 0 to 150+
Frequency The frequency of the sound Hz 20 Hz to 20,000 Hz (audible range)
Weighting Curve Type of frequency filter applied N/A A, B, C, D, Z
Reference Level A standard SPL for comparison dB Often 94 dB (for IEC 61672 standards)
Threshold Level Minimum perceived sound level dB 0 dB (or lower, depending on context)
W(f) Weighting factor at frequency f dB Ranges from approx. -60 dB to +3 dB
Weighted Value Measured dB adjusted by W(f) dB Effectively dBA, dBC, etc.
Weighting Difference Difference between raw and weighted dB dB Equal to -W(f)

Practical Examples (Real-World Use Cases)

Example 1: Home Studio Monitoring

An audio engineer is setting up monitors in their home studio. They measure a pink noise signal at the listening position.

  • Inputs:
  • Measurement Value (dB): 85.0 dB
  • Frequency (Hz): 100 Hz
  • Weighting Curve: A-weighting
  • Reference Level (dB): 94.0 dB
  • Threshold Level (dB): 0.0 dB

Calculation: At 100 Hz, the A-weighting factor W(f) is approximately -9.6 dB.

Results:

  • Primary Result (A-weighted): 75.4 dBA
  • Weighted Value: 75.4 dB
  • Weighting Difference: 9.6 dB
  • Acoustic Significance: Moderate reduction in perceived loudness due to low-frequency emphasis.

Interpretation: The raw measurement shows 85 dB, but the A-weighted value is 75.4 dBA. This indicates that while the physical sound pressure is high, our ears perceive it as significantly quieter due to the lower sensitivity at 100 Hz compared to mid-range frequencies. This is crucial for setting appropriate monitoring levels that are safe and representative of perceived loudness. Use our DBA weighting calculator to see how other frequencies change this perception.

Example 2: Industrial Noise Assessment

A safety officer is measuring noise levels near a large machine in a factory. They want to assess potential hearing damage risk using C-weighting, which is less aggressive with low frequencies than A-weighting.

  • Inputs:
  • Measurement Value (dB): 105.0 dB
  • Frequency (Hz): 50 Hz
  • Weighting Curve: C-weighting
  • Reference Level (dB): 110.0 dB (typical for C-weighting reference)
  • Threshold Level (dB): 0.0 dB

Calculation: At 50 Hz, the C-weighting factor W(f) is approximately -3.0 dB.

Results:

  • Primary Result (C-weighted): 102.0 dBC
  • Weighted Value: 102.0 dB
  • Weighting Difference: 3.0 dB
  • Acoustic Significance: Slight reduction in perceived loudness.

Interpretation: The raw noise level is 105 dB. Using C-weighting, the perceived level drops slightly to 102.0 dBC. This machine produces significant low-frequency noise. The difference highlights that while C-weighting is closer to the raw SPL than A-weighting, it still accounts for the reduced sensitivity at 50 Hz. For occupational exposure limits, comparing these values against standards helps determine the required hearing protection. This DBA weighting calculator is a valuable tool for such assessments.

How to Use This DBA Weighting Calculator

Using the DBA weighting calculator is straightforward. Follow these steps to get accurate weighted sound measurements:

  1. Enter Measurement Value (dB): Input the raw decibel reading from your sound level meter or measurement device. This is the unadjusted sound pressure level.
  2. Enter Frequency (Hz): Provide the specific frequency (in Hertz) that corresponds to your measurement. If you are measuring broadband noise (like pink or white noise), you might use a central frequency or analyze different frequency bands separately.
  3. Select Weighting Curve: Choose the desired frequency weighting curve from the dropdown menu. The most common are:
    • A-weighting (dBA): Most closely approximates human hearing at moderate levels.
    • C-weighting (dBC): Flatter response, better for high sound levels and capturing low-frequency content.
    • Z-weighting (dBZ): Flat response, no frequency adjustment. Measures the true SPL across a defined bandwidth.
  4. Enter Reference Level (dB): Input the standard reference sound pressure level associated with the chosen weighting curve (often 94 dB for A and C). This is used in some specific standards but primarily impacts certain calculation standards. For general use, the default is usually appropriate.
  5. Enter Threshold Level (dB): Input the baseline sound level or the threshold of hearing you are considering. For most practical acoustic applications, this is 0 dB.
  6. Click "Calculate": The calculator will instantly process your inputs.

How to Read Results:

  • Primary Highlighted Result: This is your main weighted dB value (e.g., dBA, dBC) – the measurement adjusted for perceived loudness at the specified frequency.
  • Weighted Value: This confirms the calculated dB value after applying the selected weighting.
  • Weighting Difference: This shows how many decibels were added or subtracted by the weighting filter. A negative number means the perceived loudness is less than the raw measurement; a positive number means it's greater (less common with A/C weighting).
  • Acoustic Significance: A qualitative interpretation of the weighting difference, indicating how much the perceived loudness is modified.
  • Table: Provides a clear breakdown of all input parameters and calculated results for easy reference.
  • Chart: Visualizes how the selected weighting curve affects sound levels across different frequencies, comparing it to a flat response.

Decision-Making Guidance: The weighted values are generally more useful for understanding the impact of noise on humans or the perceived loudness in a mix. For instance, if you're concerned about noise pollution, dBA is often the standard. If you need to assess the peak energy of a sound system, especially with significant low-frequency content (like subwoofers), dBC might be more relevant. Z-weighting provides the raw physics. Use the results to inform acoustic treatment choices, set safe listening levels, or comply with noise regulations.

Key Factors That Affect DBA Weighting Results

Several factors influence the outcome of DBA weighting calculations and their interpretation:

  1. Frequency Content of the Sound: This is the most direct factor. Sounds rich in low or high frequencies will be attenuated more by A-weighting than sounds with energy primarily in the mid-range. Our DBA weighting calculator demonstrates this sensitivity.
  2. Type of Weighting Curve Selected: A-weighting, C-weighting, and Z-weighting have fundamentally different frequency responses. A-weighting significantly reduces low-frequency content, C-weighting less so, and Z-weighting not at all. Choosing the correct curve based on the application (e.g., perceived loudness vs. peak SPL) is critical.
  3. Measurement Accuracy and Calibration: The accuracy of the initial sound pressure level (SPL) measurement is paramount. An incorrectly calibrated or inaccurate sound level meter will produce flawed raw data, leading to incorrect weighted results.
  4. Sound Pressure Level (SPL): While weighting curves are standardized, human hearing sensitivity can subtly vary with loudness. However, the primary impact of SPL on weighting is that C-weighting is often preferred over A-weighting for very high SPLs (above 100 dB) where human hearing response becomes flatter.
  5. Environmental Conditions: Temperature and humidity can slightly affect the accuracy of acoustic measurements and the behavior of sound waves. While typically a minor factor for weighting calculations themselves, they impact the raw dB reading.
  6. Room Acoustics (Reverberation and Absorption): In a real environment, reflections and absorption alter the sound field. The location of the measurement (near-field vs. far-field, direct vs. reverberant sound) affects the raw dB reading. The weighting calculation is applied *after* these environmental effects influence the sound reaching the microphone. Understanding room acoustics is key.
  7. Dynamic Range of the Measurement Device: If the sound source produces very loud peaks and very quiet passages, the dynamic range of the measurement tool is important. This relates more to capturing the full spectrum accurately before weighting is applied.
  8. Purpose of Measurement: Are you measuring environmental noise, studio acoustics, or workplace safety? The intended use dictates which weighting curve is most appropriate and therefore how the results should be interpreted. Use our studio setup guide for context.

Frequently Asked Questions (FAQ)

What is the difference between dB, dBA, and dBC?
dB (decibel) is a unit of logarithmic measurement of sound pressure level (SPL). It represents the raw physical intensity.
dBA (A-weighted decibel) adjusts the dB reading to approximate human hearing sensitivity, which is less sensitive to low and high frequencies.
dBC (C-weighted decibel) is also a weighted measurement but has a flatter frequency response than dBA, making it suitable for higher sound levels and capturing more low-frequency content.
Which weighting curve should I use?
Use A-weighting (dBA) for general noise level measurements, environmental noise assessment, and when approximating perceived loudness at moderate levels.
Use C-weighting (dBC) for measuring peak sound levels, assessing systems with significant low-frequency content (like PA systems or industrial machinery), or when dealing with very high sound pressure levels where human hearing is flatter.
Use Z-weighting (dBZ) when you need the absolute raw sound pressure level without any frequency adjustment, often for scientific or calibration purposes.
Why does my dBA reading differ from my raw dB reading?
This difference occurs because the A-weighting filter adjusts the measured sound pressure level based on frequency. If your sound has significant energy in low or high frequencies where human hearing is less sensitive, the dBA reading will be lower than the raw dB reading. Conversely, if the energy is concentrated in the mid-range frequencies (around 1-4 kHz), the dBA reading will be closer to the raw dB reading.
Can the DBA weighting calculator handle ultrasonic or infrasonic frequencies?
Standard weighting curves like A and C are designed primarily for the human audible range (approx. 20 Hz to 20,000 Hz). While the calculator can technically process inputs outside this range, the resulting weighted values may not be physically meaningful or relevant to human perception for ultrasonic (>20 kHz) or infrasonic (<20 Hz) frequencies. Z-weighting (flat) would be more appropriate for characterizing these ranges directly.
What is the 'Reference Level' input for?
The reference level is part of the standardized definitions for weighting curves, often set at 94 dB SPL for A and C weighting, and 110 dB SPL for D-weighting, referenced to 20 micropascals. In most practical applications using modern sound level meters or calculators like this, the exact reference level value doesn't change the *shape* of the weighting curve but might be relevant for certain specific calibration or historical standards. For general use, the default values are usually sufficient.
How does DBA weighting relate to studio acoustics?
In studio acoustics, dBA measurements help engineers understand how the overall perceived loudness of their room and monitoring system compares to physical measurements. It's useful for setting safe listening levels and ensuring mixes translate well across different playback systems. Understanding the frequency balance (e.g., low-frequency buildup) is also crucial, where C-weighting or even flat (Z) might provide more insight into the raw energy.
Is A-weighting always the best for perceived loudness?
A-weighting is the best standard approximation for perceived loudness at *moderate* sound levels. At very high sound pressure levels (e.g., > 100 dB), human hearing becomes more linear across frequencies, meaning C-weighting or even Z-weighting might better represent the *relative* perception. However, for most common applications like environmental noise or typical studio monitoring, A-weighting remains the standard for perceived loudness.
What does a large positive Weighting Difference mean?
A positive Weighting Difference (meaning the raw dB is *lower* than the weighted dB) is rare for A and C weighting curves in the audible spectrum. It would imply that the specific frequency being measured falls into a range where the weighting curve *amplifies* the signal relative to the reference. This typically doesn't happen significantly within the standard operational ranges for A/C weighting related to human hearing perception. Z-weighting will always yield a Weighting Difference of 0 dB.
Can this calculator be used for musical instrument testing?
Yes, it can be useful. Measuring an instrument's output with dBA can give an idea of its perceived loudness to a listener. Analyzing measurements at different frequencies with various weighting curves (or flat Z-weighting) can help understand the instrument's tonal balance and how its perceived loudness changes with frequency content.
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Real implementations use complex functions. if (frequency < 31.5) return -55.2; if (frequency < 63) return -30.2; if (frequency < 125) return -15.0; if (frequency < 250) return -7.0; if (frequency < 500) return -1.1; if (frequency < 1000) return 0.0; if (frequency < 2000) return 1.1; if (frequency < 5000) return 2.1; if (frequency < 10000) return 1.1; if (frequency < 20000) return -1.5; } if (curve === 'C') { if (frequency < 31.5) return -11.4; if (frequency < 63) return -5.7; if (frequency < 125) return -3.0; if (frequency < 250) return -1.5; if (frequency < 500) return -0.4; if (frequency < 1000) return 0.0; if (frequency < 2000) return -0.4; if (frequency < 5000) return -1.1; if (frequency < 10000) return -2.7; if (frequency series.data); var minY = Math.min(…allYValues, -60); // Ensure reasonable lower bound var maxY = Math.max(…allYValues, 5); // Ensure reasonable upper bound var yRange = maxY – minY; // Draw axes ctx.strokeStyle = '#ccc'; ctx.lineWidth = 1; ctx.beginPath(); ctx.moveTo(padding, padding); ctx.lineTo(padding, chartHeight – padding); // Y-axis ctx.lineTo(chartWidth – padding, chartHeight – padding); // X-axis ctx.stroke(); // Draw Y-axis labels and ticks var numYTicks = 5; for (var i = 0; i <= numYTicks; i++) { var yValue = minY + (yRange * (numYTicks – i)) / numYTicks; var yPos = padding + (plotAreaHeight * i) / numYTicks; ctx.fillStyle = '#666'; ctx.textAlign = 'right'; ctx.fillText(yValue.toFixed(1) + ' dB', padding – 5, yPos + 4); ctx.beginPath(); ctx.moveTo(padding – 5, yPos); ctx.lineTo(padding, yPos); ctx.stroke(); } // Draw X-axis labels and ticks var numXTicks = frequencies.length; for (var i = 0; i < numXTicks; i++) { var xPos = padding + (plotAreaWidth * i) / (numXTicks – 1); ctx.fillStyle = '#666'; ctx.textAlign = 'center'; ctx.fillText(frequencies[i] + ' Hz', xPos, chartHeight – padding + 15); ctx.beginPath(); ctx.moveTo(xPos, chartHeight – padding); ctx.lineTo(xPos, chartHeight – padding + 5); ctx.stroke(); } // Draw data series lines dataSeries.forEach(function(series) { ctx.strokeStyle = series.borderColor; ctx.lineWidth = 2; ctx.beginPath(); series.data.forEach(function(yValue, index) { var xPos = padding + (plotAreaWidth * index) / (numXTicks – 1); var yPos = padding + plotAreaHeight – (plotAreaHeight * (yValue – minY)) / yRange; if (index === 0) { ctx.moveTo(xPos, yPos); } else { ctx.lineTo(xPos, yPos); } }); ctx.stroke(); // Draw points series.data.forEach(function(yValue, index) { var xPos = padding + (plotAreaWidth * index) / (numXTicks – 1); var yPos = padding + plotAreaHeight – (plotAreaHeight * (yValue – minY)) / yRange; ctx.fillStyle = series.borderColor; ctx.beginPath(); ctx.arc(xPos, yPos, 4, 0, Math.PI * 2); ctx.fill(); }); }); // Draw legend ctx.fillStyle = '#333'; ctx.textAlign = 'left'; var legendY = padding / 2; dataSeries.forEach(function(series, index) { ctx.fillStyle = series.borderColor; ctx.fillRect(padding + index * 150, legendY – 10, 15, 10); ctx.fillStyle = '#333'; ctx.fillText(series.label, padding + index * 150 + 20, legendY); }); } function calculateWeighting() { var measurementValue = parseFloat(document.getElementById("measurementValue").value); var frequency = parseFloat(document.getElementById("frequency").value); var weightingCurve = document.getElementById("weightingCurve").value; var referenceLevel = parseFloat(document.getElementById("referenceLevel").value); var thresholdLevel = parseFloat(document.getElementById("thresholdLevel").value); var error = false; // Input validation if (isNaN(measurementValue) || measurementValue < 0) { showError("measurementValue", "Please enter a valid non-negative number for measurement."); error = true; } else { clearError("measurementValue"); } if (isNaN(frequency) || frequency 10) { acousticSignificance = "Significant reduction in perceived loudness"; } else if (weightingDifference > 5) { acousticSignificance = "Moderate reduction in perceived loudness"; } else if (weightingDifference > 1) { acousticSignificance = "Slight reduction in perceived loudness"; } else if (weightingDifference < -1) { acousticSignificance = "Slight increase in perceived loudness (uncommon for A/C)"; } else { acousticSignificance = "Perceived loudness close to raw measurement"; } // Update primary result var primaryResultDisplay = weightedValue.toFixed(1) + (weightingCurve === 'Z' ? ' dB' : ' d' + weightingCurve); document.getElementById("primary-result").innerText = primaryResultDisplay; // Update intermediate results document.getElementById("weighted-value").querySelector("span").innerText = weightedValue.toFixed(1); document.getElementById("weighting-difference").querySelector("span").innerText = weightingDifference.toFixed(1); document.getElementById("acoustic-significance").innerText = "Acoustic Significance: " + acousticSignificance; // Update formula explanation var formulaText = "Formula: Weighted dB = Measured dB + W(f) [" + weightingCurve + "-weighting factor]."; formulaText += " Weighting Difference = Measured dB – Weighted dB = -W(f)."; formulaText += " W(f) for " + weightingCurve + " at " + frequency + " Hz is approx. " + w_f.toFixed(1) + " dB."; document.getElementById("formula-explanation").innerText = formulaText; // Update table document.getElementById("table-measurement-value").innerText = measurementValue.toFixed(1); document.getElementById("table-frequency").innerText = frequency.toFixed(0); document.getElementById("table-weighting-curve").innerText = weightingCurve; document.getElementById("table-reference-level").innerText = referenceLevel.toFixed(1); document.getElementById("table-threshold-level").innerText = thresholdLevel.toFixed(1); document.getElementById("table-weighted-value").innerText = weightedValue.toFixed(1); document.getElementById("table-weighting-difference").innerText = weightingDifference.toFixed(1); drawChart(); } function showError(inputId, message) { var inputGroup = document.getElementById(inputId).closest('.input-group'); var errorElement = inputGroup.querySelector('.error-message'); if (!errorElement) { errorElement = document.createElement('div'); errorElement.className = 'error-message'; inputGroup.appendChild(errorElement); } errorElement.innerText = message; errorElement.style.display = 'block'; document.getElementById(inputId).style.borderColor = 'var(–error-color)'; } function clearError(inputId) { var inputGroup = document.getElementById(inputId).closest('.input-group'); var errorElement = inputGroup.querySelector('.error-message'); if (errorElement) { errorElement.style.display = 'none'; } document.getElementById(inputId).style.borderColor = 'var(–input-border)'; } function resetCalculator() { document.getElementById("measurementValue").value = "85"; document.getElementById("frequency").value = "100"; document.getElementById("weightingCurve").value = "A"; document.getElementById("referenceLevel").value = "94"; document.getElementById("thresholdLevel").value = "0"; // Clear errors var inputs = document.querySelectorAll('.loan-calc-container input, .loan-calc-container select'); inputs.forEach(function(input) { clearError(input.id); }); calculateWeighting(); // Recalculate with defaults } function copyResults() { var primaryResult = document.getElementById("primary-result").innerText; var weightedValue = document.getElementById("weighted-value").innerText; var weightingDifference = document.getElementById("weighting-difference").innerText; var significance = document.getElementById("acoustic-significance").innerText; var formula = document.getElementById("formula-explanation").innerText; var assumptions = "Key Assumptions:\n"; assumptions += "- Measurement Value: " + document.getElementById("measurementValue").value + " dB\n"; assumptions += "- Frequency: " + document.getElementById("frequency").value + " Hz\n"; assumptions += "- Weighting Curve: " + document.getElementById("weightingCurve").value + "\n"; assumptions += "- Reference Level: " + document.getElementById("referenceLevel").value + " dB\n"; assumptions += "- Threshold Level: " + document.getElementById("thresholdLevel").value + " dB\n"; var resultsText = "— DBA Weighting Calculator Results —\n\n"; resultsText += "Primary Result: " + primaryResult + "\n"; resultsText += weightedValue + "\n"; resultsText += weightingDifference + "\n"; resultsText += significance + "\n\n"; resultsText += "Formula Used:\n" + formula + "\n\n"; resultsText += assumptions; // Use a temporary textarea to copy text var textArea = document.createElement("textarea"); textArea.value = resultsText; textArea.style.position = "fixed"; textArea.style.left = "-9999px"; document.body.appendChild(textArea); textArea.focus(); textArea.select(); try { var successful = document.execCommand('copy'); var msg = successful ? 'Results copied to clipboard!' : 'Copying failed!'; console.log(msg); // Optionally show a temporary success message var notification = document.createElement('div'); notification.innerText = msg; notification.style.cssText = 'position: fixed; bottom: 20px; left: 50%; transform: translateX(-50%); background-color: var(–primary-color); color: white; padding: 10px 20px; border-radius: 5px; z-index: 1000;'; document.body.appendChild(notification); setTimeout(function() { document.body.removeChild(notification); }, 2000); } catch (err) { console.error('Fallback: Oops, unable to copy', err); var notification = document.createElement('div'); notification.innerText = 'Copying failed!'; notification.style.cssText = 'position: fixed; bottom: 20px; left: 50%; transform: translateX(-50%); background-color: var(–error-color); color: white; padding: 10px 20px; border-radius: 5px; z-index: 1000;'; document.body.appendChild(notification); setTimeout(function() { document.body.removeChild(notification); }, 2000); } document.body.removeChild(textArea); } // Initial calculation and chart draw on page load window.onload = function() { // Adjust canvas size on resize window.addEventListener('resize', function() { canvas.width = canvas.offsetWidth; canvas.height = 300; // Keep height consistent or adjust as needed drawChart(); }); calculateWeighting(); drawChart(); };

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