Equivalent Sensitivity Calculator for Different Mouse Weights
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Mouse Sensitivity Equivalence Calculator
Calculation Results
—
Formula Used: Perceived sensitivity is influenced by mouse weight due to inertia and physical effort. Lighter mice feel faster, requiring lower eDPI for the same perceived speed. The formula approximates this by adjusting eDPI based on the ratio of target weight to current weight.
Adjustment Factor = (Target Weight / Current Weight)
Equivalent eDPI = Current eDPI * Adjustment Factor
Sensitivity vs. Mouse Weight
Sensitivity Comparison Table
| Metric |
Value |
| Current Mouse Weight |
|
| Current eDPI |
|
| Target Mouse Weight |
|
| Equivalent eDPI |
|
| Required DPI Change (at same in-game sens) |
|
| Required In-Game Sens Change (at same DPI) |
|
What is Equivalent Sensitivity on Different Weight Mice?
The concept of equivalent sensitivity on different weight mice refers to adjusting your gaming mouse's sensitivity settings (DPI and in-game sensitivity) so that the perceived speed and control remain consistent when switching between mice of varying weights. While the numerical eDPI (effective Dots Per Inch) might be the same, a lighter mouse often feels faster and more responsive, potentially leading to overshooting targets or feeling less stable. Conversely, a heavier mouse might feel sluggish, requiring more effort for quick flicks. This calculator helps bridge that gap, ensuring a smoother transition and consistent performance regardless of your mouse's physical mass.
Gamers, particularly those in competitive titles like First-Person Shooters (FPS), rely heavily on muscle memory and precise aiming. Inconsistencies in perceived sensitivity due to mouse weight can disrupt this muscle memory, leading to frustration and decreased performance. Understanding and calculating equivalent sensitivity allows players to maintain their established aiming style and accuracy.
Common Misconceptions:
- Myth: eDPI is the only factor. Reality: Mouse weight introduces physical dynamics (inertia, ease of movement) that affect perceived sensitivity.
- Myth: Heavier mice are always better for control. Reality: While heavier mice can offer stability, lighter mice allow for faster, less fatiguing movements, which can be crucial for flick shots and rapid target acquisition.
- Myth: Sensitivity adjustment is purely mathematical. Reality: Personal preference and acclimatization play a significant role. The calculator provides a starting point, not a definitive final setting.
Equivalent Sensitivity Formula and Mathematical Explanation
The core idea behind calculating equivalent sensitivity is to account for the physical difference in how mice of varying weights feel. Lighter mice require less force to initiate and stop movement, making them feel more "twitchy" or sensitive. Heavier mice require more force, feeling more planted but potentially slower to react.
A common approach is to use the ratio of the mouse weights to determine an adjustment factor. The assumption is that a lighter mouse will feel proportionally faster, and thus require a proportionally lower eDPI to achieve the same perceived speed and control as a heavier mouse.
The Formula:
Adjustment Factor = (Target Mouse Weight / Current Mouse Weight)
Equivalent eDPI = Current eDPI * Adjustment Factor
This formula suggests that if you move to a lighter mouse (Target Weight Current Weight) results in an Adjustment Factor greater than 1, increasing the required eDPI.
We can also break down the eDPI into its components: DPI (Dots Per Inch) and In-Game Sensitivity.
Current eDPI = Current DPI * Current In-Game Sensitivity
Equivalent eDPI = Target DPI * Target In-Game Sensitivity
Therefore, if you want to keep either your DPI or your In-Game Sensitivity constant, you can calculate the required change for the other:
To keep In-Game Sensitivity constant:
Target DPI = Equivalent eDPI / Current In-Game Sensitivity
Target DPI = (Current eDPI * (Target Weight / Current Weight)) / Current In-Game Sensitivity
To keep DPI constant:
Target In-Game Sensitivity = Equivalent eDPI / Current DPI
Target In-Game Sensitivity = (Current eDPI * (Target Weight / Current Weight)) / Current DPI
Variables Table
| Variable |
Meaning |
Unit |
Typical Range |
| Current Mouse Weight |
Weight of the mouse currently being used. |
grams (g) |
40g – 150g |
| Current Sensitivity (eDPI) |
Effective Dots Per Inch; a combined measure of mouse sensitivity. |
eDPI |
200 – 6400+ |
| Target Mouse Weight |
Weight of the new mouse being considered. |
grams (g) |
40g – 150g |
| Adjustment Factor |
Ratio determining how much to scale sensitivity based on weight difference. |
Unitless |
0.5 – 2.0 (approx.) |
| Equivalent eDPI |
The calculated eDPI needed on the target mouse for similar perceived sensitivity. |
eDPI |
Varies |
| Current DPI |
Dots Per Inch setting on the current mouse. |
DPI |
400 – 32000+ |
| Current In-Game Sensitivity |
Sensitivity setting within the game itself. |
Unitless |
0.1 – 5.0+ (game dependent) |
Practical Examples (Real-World Use Cases)
Let's explore how this calculator can be used in practical scenarios for gamers aiming to maintain consistent performance.
Example 1: Switching to a Lighter FPS Mouse
Scenario: A competitive FPS player currently uses a heavier mouse weighing 100g with an eDPI of 1200 (e.g., 800 DPI * 1.5 in-game sensitivity). They are considering switching to a new, much lighter mouse that weighs only 60g. They want to know what eDPI setting on the new mouse will feel most similar.
Inputs:
- Current Mouse Weight: 100g
- Current eDPI: 1200
- Target Mouse Weight: 60g
Calculation:
- Adjustment Factor = 60g / 100g = 0.6
- Equivalent eDPI = 1200 * 0.6 = 720
Interpretation: The player should aim for an eDPI of approximately 720 on their new 60g mouse to achieve a similar perceived sensitivity. This means they might need to lower their DPI significantly (e.g., to 400 DPI and keep 1.8 in-game sensitivity) or drastically reduce their in-game sensitivity if they keep the DPI the same. This lower eDPI helps compensate for the reduced inertia and increased responsiveness of the lighter mouse.
Example 2: Moving to a Heavier Productivity Mouse
Scenario: A content creator primarily uses a lightweight mouse (55g) for gaming, with an eDPI of 2400 (e.g., 1200 DPI * 2.0 in-game sensitivity). They are now looking for a more robust, heavier mouse for general productivity and occasional gaming, weighing around 110g. They want to find a comparable sensitivity setting.
Inputs:
- Current Mouse Weight: 55g
- Current eDPI: 2400
- Target Mouse Weight: 110g
Calculation:
- Adjustment Factor = 110g / 55g = 2.0
- Equivalent eDPI = 2400 * 2.0 = 4800
Interpretation: To maintain a similar feel when moving to the heavier 110g mouse, the user should aim for an eDPI of approximately 4800. This significantly higher eDPI is needed to counteract the increased inertia and perceived sluggishness of the heavier mouse, allowing for quicker cursor movements and aiming adjustments. They might achieve this by increasing their DPI or in-game sensitivity settings.
How to Use This Equivalent Sensitivity Calculator
Using the Equivalent Sensitivity Calculator is straightforward. Follow these steps to find your optimal settings when switching mouse weights:
-
Enter Current Mouse Details: Input the exact weight of your current mouse in grams into the "Current Mouse Weight" field. Then, enter your current overall sensitivity, known as eDPI (effective Dots Per Inch), into the "Current Sensitivity (eDPI)" field. Remember, eDPI is calculated by multiplying your mouse's DPI setting by your in-game sensitivity multiplier.
-
Enter Target Mouse Weight: Input the weight of the new mouse you are considering or have purchased into the "Target Mouse Weight" field.
-
Calculate: Click the "Calculate" button. The calculator will process the inputs and display the results.
-
Review Results:
- Primary Result (Equivalent eDPI): This is the main output, showing the target eDPI you should aim for on the new mouse to feel similar to your old setup.
- Intermediate Values: These provide breakdowns, such as the calculated adjustment factor, and potential changes needed for DPI or in-game sensitivity if you wish to keep one constant.
- Table: A detailed table summarizes all input and output values, including suggested changes for DPI and in-game sensitivity.
- Chart: Visualizes how sensitivity changes across a range of mouse weights based on your inputs.
-
Apply and Adjust: Use the "Equivalent eDPI" as a starting point. You may need to adjust your DPI or in-game sensitivity settings in your mouse software or game settings to match this target eDPI. It's recommended to test the new settings in-game and make minor fine-tuning adjustments based on your personal feel and performance.
-
Reset or Copy: Use the "Reset" button to clear the fields and start over. Use the "Copy Results" button to copy the key findings to your clipboard for easy reference.
Decision-Making Guidance: This calculator is invaluable when choosing a new mouse. If you prefer a lighter feel for faster reactions, use the calculator to see how much you'll need to lower your sensitivity. If you're moving to a heavier mouse and want more stability, it shows how much you might need to increase your sensitivity. Always remember that these are starting points; personal comfort and practice are key.
Key Factors That Affect Equivalent Sensitivity Results
While the weight-to-sensitivity ratio provides a solid baseline, several other factors can influence the perceived equivalence and your overall aiming experience. Understanding these nuances helps in fine-tuning your settings beyond the calculator's output.
-
Mouse Grip Style: How you hold the mouse (palm, claw, fingertip) significantly impacts control and the perceived effort required for movement. A lighter mouse might feel more natural for a fingertip grip, while a heavier one could suit a palm grip better, affecting how sensitive you need it to feel.
-
Mouse Skates/Feet: The material and condition of a mouse's feet (skates) affect its glide. Low-friction skates on a lighter mouse can make it feel even faster, potentially requiring a lower eDPI than the calculator suggests. Conversely, worn or high-friction skates can slow down any mouse.
-
Mousepad Surface: Different mousepad surfaces (cloth, hard, hybrid) offer varying levels of friction and stopping power. A faster pad combined with a lighter mouse might necessitate a lower sensitivity adjustment than calculated.
-
Sensor Performance: While modern sensors are highly accurate, subtle differences in tracking performance, jitter, or acceleration between mice can affect the consistency of sensitivity, regardless of weight.
-
Personal Arm/Wrist Strength and Fatigue: Individual physical capabilities play a role. Someone with stronger arms might handle heavier mice more easily, while fatigue over long sessions can make lighter mice feel more comfortable and controllable, influencing preferred sensitivity.
-
In-Game Movement Mechanics: The specific game's movement speed, acceleration curves, and aiming mechanics can interact with mouse weight and sensitivity. A game with fast character movement might benefit from a slightly lower sensitivity, irrespective of mouse weight adjustments.
-
Polling Rate: A higher polling rate (e.g., 1000Hz vs 500Hz) results in smoother cursor movement and potentially a more responsive feel, which can indirectly influence perceived sensitivity and the need for fine-tuning.
-
Build Quality and Balance: The distribution of weight within a mouse matters. An unevenly weighted mouse, regardless of its total weight, can feel awkward and affect aiming consistency.
Frequently Asked Questions (FAQ)
Q1: Does mouse weight *really* affect sensitivity?
A: Yes, it affects *perceived* sensitivity. Lighter mice require less inertia to move and stop, making them feel faster and more responsive. Heavier mice require more force, feeling slower and more stable. The calculator helps adjust numerical sensitivity to match this perceived difference.
Q2: Is there a "perfect" weight for gaming mice?
A: No, there's no universal "perfect" weight. It's highly subjective and depends on the game genre, player preference, grip style, and physical comfort. Lightweight mice (under 70g) are popular for FPS games requiring fast flicks, while heavier mice might be preferred for slower-paced strategy games or by users who value a substantial feel.
Q3: My calculator result is very different from my current eDPI. Is something wrong?
A: Not necessarily. If you're switching between mice with drastically different weights (e.g., 50g to 120g), the required eDPI adjustment can be significant. The calculator provides a mathematical starting point based on weight ratios. You'll still need to fine-tune based on feel.
Q4: How do I calculate my current eDPI?
A: Multiply your mouse's DPI setting (found in its software) by your in-game sensitivity multiplier (found in the game's settings). For example, 800 DPI * 2.5 in-game sensitivity = 2000 eDPI.
Q5: Should I adjust DPI or in-game sensitivity?
A: It often depends on the range available and personal preference. Many prefer to keep DPI consistent (e.g., 400, 800, 1600) and adjust in-game sensitivity. However, if the required change is drastic, adjusting DPI might yield a smoother result. Some games have better sensitivity scaling at certain ranges.
Q6: What if my new mouse has different sensor properties?
A: While the calculator focuses on weight, different sensors can have subtle differences in tracking, acceleration, or jitter. If you notice inconsistencies beyond what weight adjustment explains, consider if the sensor itself is a factor.
Q7: How long does it take to get used to a new sensitivity?
A: This varies greatly. Some players adapt within hours, while others might take days or even weeks to fully adjust their muscle memory. Be patient and focus on consistent practice.
Q8: Can I use this calculator for non-gaming mice?
A: While designed with gaming in mind, the principle applies. If you find a heavier office mouse feels slower and requires more effort for precise tasks, you can use the calculator to find a setting that feels more responsive, though the required sensitivity adjustments might be less extreme than in competitive gaming.
Related Tools and Internal Resources
var currentWeightInput = document.getElementById('currentWeight');
var currentSensitivityInput = document.getElementById('currentSensitivity');
var targetWeightInput = document.getElementById('targetWeight');
var currentWeightError = document.getElementById('currentWeightError');
var currentSensitivityError = document.getElementById('currentSensitivityError');
var targetWeightError = document.getElementById('targetWeightError');
var primaryResultDiv = document.getElementById('primary-result');
var intermediateDpiDiv = document.getElementById('intermediate-dpi');
var intermediateIngameDiv = document.getElementById('intermediate-ingame');
var intermediatePhysicalEffectDiv = document.getElementById('intermediate-physical-effect');
var tableCurrentWeight = document.getElementById('tableCurrentWeight');
var tableCurrentEDPI = document.getElementById('tableCurrentEDPI');
var tableTargetWeight = document.getElementById('tableTargetWeight');
var tableEquivalentEDPI = document.getElementById('tableEquivalentEDPI');
var tableDPIChange = document.getElementById('tableDPIChange');
var tableInGameSensChange = document.getElementById('tableInGameSensChange');
var sensitivityChart;
var chartContext;
function validateInput(value, min, max, errorElement, inputElement, fieldName) {
var error = ";
if (value === null || value === ") {
error = fieldName + ' is required.';
inputElement.classList.add('error-border');
} else {
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if (isNaN(numValue)) {
error = fieldName + ' must be a number.';
inputElement.classList.add('error-border');
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error = fieldName + ' cannot be greater than ' + max + '.';
inputElement.classList.add('error-border');
} else {
inputElement.classList.remove('error-border');
}
}
if (errorElement) {
errorElement.textContent = error;
}
return !error;
}
function calculateEquivalentSensitivity() {
var currentWeight = parseFloat(currentWeightInput.value);
var currentSensitivity = parseFloat(currentSensitivityInput.value);
var targetWeight = parseFloat(targetWeightInput.value);
var isValid = true;
isValid &= validateInput(currentWeightInput.value, 10, null, currentWeightError, currentWeightInput, 'Current Mouse Weight');
isValid &= validateInput(currentSensitivityInput.value, 100, null, currentSensitivityError, currentSensitivityInput, 'Current Sensitivity');
isValid &= validateInput(targetWeightInput.value, 10, null, targetWeightError, targetWeightInput, 'Target Mouse Weight');
if (!isValid) {
primaryResultDiv.textContent = '–';
intermediateDpiDiv.textContent = ";
intermediateIngameDiv.textContent = ";
intermediatePhysicalEffectDiv.textContent = ";
updateTable(", ", ", ", ", ");
updateChart([], []);
return;
}
var adjustmentFactor = targetWeight / currentWeight;
var equivalentEDPI = currentSensitivity * adjustmentFactor;
// Calculate intermediate values assuming standard DPI/In-game split
var currentDPI = 800; // Assume a common DPI for calculation basis
var currentInGameSensitivity = currentSensitivity / currentDPI;
var targetDPI_keepInGame = currentInGameSensitivity !== 0 ? equivalentEDPI / currentInGameSensitivity : 0;
var targetInGameSensitivity_keepDPI = currentDPI !== 0 ? equivalentEDPI / currentDPI : 0;
var physicalEffect = (targetWeight currentWeight ? "Feels Slower" : "Neutral");
primaryResultDiv.textContent = equivalentEDPI.toFixed(0) + ' eDPI';
intermediateDpiDiv.textContent = 'Equivalent DPI (if In-Game Sens constant): ' + targetDPI_keepInGame.toFixed(0);
intermediateIngameDiv.textContent = 'Equivalent In-Game Sens (if DPI constant): ' + targetInGameSensitivity_keepDPI.toFixed(2);
intermediatePhysicalEffectDiv.textContent = 'Perceived Effect: ' + physicalEffect;
updateTable(currentWeight, currentSensitivity, targetWeight, equivalentEDPI.toFixed(0), targetDPI_keepInGame.toFixed(0), targetInGameSensitivity_keepDPI.toFixed(2));
updateChartData(currentWeight, currentSensitivity, targetWeight, equivalentEDPI);
}
function updateTable(cWeight, cEDPI, tWeight, eqEDPI, dpiChange, sensChange) {
tableCurrentWeight.textContent = cWeight + ' g';
tableCurrentEDPI.textContent = cEDPI + ' eDPI';
tableTargetWeight.textContent = tWeight + ' g';
tableEquivalentEDPI.textContent = eqEDPI + ' eDPI';
tableDPIChange.textContent = dpiChange + ' DPI (approx, keeping in-game sens constant)';
tableInGameSensChange.textContent = sensChange + ' (approx, keeping DPI constant)';
}
function updateChartData(currentWeight, currentSensitivity, targetWeight, equivalentEDPI) {
var chartDataPoints = [];
var weights = [];
var sensitivities = [];
// Generate data points around the current and target weights
var minWeight = Math.min(currentWeight, targetWeight) * 0.8;
var maxWeight = Math.max(currentWeight, targetWeight) * 1.2;
var step = (maxWeight – minWeight) / 10;
for (var w = minWeight; w <= maxWeight; w += step) {
weights.push(w.toFixed(0));
var adjFactor = w / currentWeight;
var sens = currentSensitivity * adjFactor;
sensitivities.push(sens.toFixed(0));
chartDataPoints.push({ weight: w.toFixed(0), sensitivity: sens.toFixed(0) });
}
// Ensure current and target points are included
var currentPointExists = chartDataPoints.some(function(p) { return p.weight == currentWeight.toFixed(0); });
if (!currentPointExists) {
chartDataPoints.push({ weight: currentWeight.toFixed(0), sensitivity: currentSensitivity.toFixed(0) });
}
var targetPointExists = chartDataPoints.some(function(p) { return p.weight == targetWeight.toFixed(0); });
if (!targetPointExists) {
chartDataPoints.push({ weight: targetWeight.toFixed(0), sensitivity: equivalentEDPI.toFixed(0) });
}
// Sort points by weight for chart rendering
chartDataPoints.sort(function(a, b) { return parseFloat(a.weight) – parseFloat(b.weight); });
weights = chartDataPoints.map(function(p) { return p.weight; });
sensitivities = chartDataPoints.map(function(p) { return p.sensitivity; });
updateChart(weights, sensitivities);
}
function updateChart(weights, sensitivities) {
if (!chartContext) {
var canvas = document.getElementById('sensitivityChart');
chartContext = canvas.getContext('2d');
}
if (sensitivityChart) {
sensitivityChart.destroy();
}
sensitivityChart = new Chart(chartContext, {
type: 'line',
data: {
labels: weights,
datasets: [{
label: 'Equivalent eDPI',
data: sensitivities,
borderColor: 'var(–primary-color)',
backgroundColor: 'rgba(0, 74, 153, 0.2)',
fill: true,
tension: 0.1
}]
},
options: {
responsive: true,
maintainAspectRatio: false,
scales: {
x: {
title: {
display: true,
text: 'Mouse Weight (grams)'
}
},
y: {
title: {
display: true,
text: 'eDPI'
},
beginAtZero: true
}
}
}
});
}
function resetCalculator() {
currentWeightInput.value = 80;
currentSensitivityInput.value = 1600;
targetWeightInput.value = 60;
currentWeightError.textContent = '';
currentSensitivityError.textContent = '';
targetWeightError.textContent = '';
currentWeightInput.classList.remove('error-border');
currentSensitivityInput.classList.remove('error-border');
targetWeightInput.classList.remove('error-border');
calculateEquivalentSensitivity(); // Recalculate with defaults
}
function copyResults() {
var resultsText = "Equivalent Sensitivity Results:\n\n";
resultsText += "Primary Result (Equivalent eDPI): " + primaryResultDiv.textContent + "\n";
resultsText += intermediateDpiDiv.textContent + "\n";
resultsText += intermediateIngameDiv.textContent + "\n";
resultsText += intermediatePhysicalEffectDiv.textContent + "\n\n";
resultsText += "Key Assumptions & Details:\n";
resultsText += "- Current Mouse Weight: " + tableCurrentWeight.textContent + "\n";
resultsText += "- Current eDPI: " + tableCurrentEDPI.textContent + "\n";
resultsText += "- Target Mouse Weight: " + tableTargetWeight.textContent + "\n";
resultsText += "- Equivalent eDPI: " + tableEquivalentEDPI.textContent + "\n";
resultsText += "- " + tableDPIChange.textContent + "\n";
resultsText += "- " + tableInGameSensChange.textContent + "\n";
// Use a temporary textarea for copying
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!' : 'Copying failed!';
console.log(msg);
// Optionally show a temporary message to the user
var copyButton = document.querySelector('.btn-copy');
var originalText = copyButton.textContent;
copyButton.textContent = msg;
setTimeout(function() {
copyButton.textContent = originalText;
}, 2000);
} catch (err) {
console.log('Oops, unable to copy');
}
document.body.removeChild(textArea);
}
// Initial calculation on page load
document.addEventListener('DOMContentLoaded', function() {
// Ensure Chart.js is loaded before initializing chart
if (typeof Chart !== 'undefined') {
updateChartData(
parseFloat(currentWeightInput.value),
parseFloat(currentSensitivityInput.value),
parseFloat(targetWeightInput.value),
parseFloat(currentSensitivityInput.value) * (parseFloat(targetWeightInput.value) / parseFloat(currentWeightInput.value))
);
calculateEquivalentSensitivity();
} else {
console.error("Chart.js not loaded. Chart will not display.");
// Add a placeholder message or disable chart section if Chart.js is critical
}
});
// Add event listeners for real-time updates
currentWeightInput.addEventListener('input', calculateEquivalentSensitivity);
currentSensitivityInput.addEventListener('input', calculateEquivalentSensitivity);
targetWeightInput.addEventListener('input', calculateEquivalentSensitivity);
// Add Chart.js library dynamically if not present (for standalone HTML)
// In a real WordPress setup, you'd enqueue this script properly.
if (typeof Chart === 'undefined') {
var script = document.createElement('script');
script.src = 'https://cdn.jsdelivr.net/npm/chart.js';
script.onload = function() {
console.log('Chart.js loaded.');
// Re-initialize chart after library load
updateChartData(
parseFloat(currentWeightInput.value),
parseFloat(currentSensitivityInput.value),
parseFloat(targetWeightInput.value),
parseFloat(currentSensitivityInput.value) * (parseFloat(targetWeightInput.value) / parseFloat(currentWeightInput.value))
);
calculateEquivalentSensitivity();
};
document.head.appendChild(script);
} else {
// If Chart.js is already available, initialize immediately
updateChartData(
parseFloat(currentWeightInput.value),
parseFloat(currentSensitivityInput.value),
parseFloat(targetWeightInput.value),
parseFloat(currentSensitivityInput.value) * (parseFloat(targetWeightInput.value) / parseFloat(currentWeightInput.value))
);
calculateEquivalentSensitivity();
}