Calculate a Reddish Weight

Calculate Reddish Weight: Your Definitive Guide & Calculator body { font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; line-height: 1.6; color: #333; background-color: #f8f9fa; margin: 0; padding: 0; display: flex; justify-content: center; padding-top: 20px; padding-bottom: 40px; } .container { width: 100%; max-width: 1000px; margin: 0 auto; padding: 20px; background-color: #ffffff; border-radius: 8px; box-shadow: 0 4px 15px rgba(0, 0, 0, 0.05); display: flex; flex-direction: column; gap: 30px; } header { background-color: #004a99; color: white; padding: 20px; border-radius: 8px 8px 0 0; text-align: center; margin: -20px -20px 0 -20px; } header h1 { margin: 0; font-size: 2.2em; font-weight: 600; } .loan-calc-container { background-color: #e9ecef; padding: 25px; border-radius: 8px; box-shadow: inset 0 2px 5px rgba(0, 0, 0, 0.05); } .loan-calc-container h2 { text-align: center; color: #004a99; margin-top: 0; margin-bottom: 20px; font-size: 1.8em; } .input-group { margin-bottom: 20px; text-align: left; } .input-group label { display: block; margin-bottom: 8px; font-weight: 500; color: #555; } .input-group input[type="number"], .input-group select { width: calc(100% – 22px); padding: 12px; border: 1px solid #ccc; border-radius: 4px; font-size: 1em; box-sizing: border-box; } .input-group .helper-text { font-size: 0.85em; color: #6c757d; margin-top: 5px; display: block; } .error-message { color: #dc3545; font-size: 0.85em; margin-top: 5px; height: 1.2em; } .results-container { background-color: #d4edda; padding: 25px; border-radius: 8px; color: #155724; text-align: center; box-shadow: inset 0 2px 5px rgba(0, 0, 0, 0.05); } .results-container h3 { margin-top: 0; font-size: 1.6em; color: #004a99; } .primary-result { font-size: 2.5em; font-weight: bold; color: #28a745; margin: 15px 0; display: block; background-color: #e9f7ec; padding: 15px; border-radius: 5px; } .intermediate-results div, .key-assumptions div { margin-bottom: 10px; font-size: 1.1em; } .intermediate-results span, .key-assumptions span { font-weight: bold; } .formula-explanation { font-size: 0.95em; color: #555; margin-top: 15px; padding-top: 15px; border-top: 1px dashed #ccc; } .button-group { display: flex; justify-content: center; gap: 10px; margin-top: 25px; flex-wrap: wrap; } .btn { padding: 12px 25px; border: none; border-radius: 5px; cursor: pointer; font-size: 1em; font-weight: 500; transition: background-color 0.3s ease; } .btn-primary { background-color: #004a99; color: white; } .btn-primary:hover { background-color: #003a7a; } .btn-secondary { background-color: #6c757d; color: white; } .btn-secondary:hover { background-color: #5a6268; } .btn-success { background-color: #28a745; color: white; } .btn-success:hover { background-color: #218838; } table { width: 100%; border-collapse: collapse; margin-top: 20px; margin-bottom: 20px; } th, td { padding: 12px; text-align: left; border: 1px solid #dee2e6; } th { background-color: #004a99; color: white; font-weight: bold; } tbody tr:nth-child(even) { background-color: #f2f2f2; } caption { caption-side: bottom; font-style: italic; color: #6c757d; margin-top: 10px; font-size: 0.9em; } canvas { display: block; margin: 20px auto; background-color: #fff; border-radius: 5px; box-shadow: 0 2px 5px rgba(0,0,0,0.1); } .section { margin-bottom: 40px; } .section h2 { color: #004a99; border-bottom: 2px solid #004a99; padding-bottom: 8px; margin-bottom: 20px; font-size: 2em; } .section h3 { color: #0056b3; margin-top: 25px; margin-bottom: 15px; font-size: 1.6em; } .section p, .section ul, .section ol { margin-bottom: 15px; color: #333; } .section li { margin-bottom: 10px; } .faq-item { margin-bottom: 20px; border-left: 3px solid #004a99; padding-left: 15px; background-color: #fefefe; padding-top: 10px; padding-bottom: 10px; border-radius: 3px; } .faq-item strong { color: #004a99; display: block; margin-bottom: 5px; font-size: 1.1em; } .internal-links { background-color: #e9ecef; padding: 20px; border-radius: 8px; } .internal-links h3 { color: #004a99; margin-top: 0; font-size: 1.6em; } .internal-links ul { list-style: none; padding: 0; } .internal-links li { margin-bottom: 15px; } .internal-links a { color: #004a99; text-decoration: none; font-weight: bold; } .internal-links a:hover { text-decoration: underline; } .internal-links p { font-size: 0.9em; color: #555; margin-top: 5px; } .footer { text-align: center; margin-top: 40px; font-size: 0.85em; color: #6c757d; } /* Canvas styling */ #chartContainer { position: relative; display: block; margin: 20px auto; background-color: #fff; border-radius: 5px; box-shadow: 0 2px 5px rgba(0,0,0,0.1); padding: 15px; }

Calculate Reddish Weight: Expert Guide & Calculator

Interactive Reddish Weight Calculator

The total mass of the object.
A numerical value representing the 'reddishness' (e.g., 0 for no red, 1 for very red).
The brightness of the surrounding light.
How much light the surface reflects (0-100).

Your Reddish Weight Calculation

Perceived Redness Value:
Effective Light Factor:
Adjusted Redness Score:

Key Assumptions:

Object Mass: kg
Surface Color Index:
Ambient Light Intensity: lux
Surface Reflectivity: %
The Reddish Weight is calculated by multiplying the Object Mass by a derived Perceived Redness Value. The Perceived Redness Value is influenced by the Surface Color Index, Ambient Light Intensity, and Surface Reflectivity, creating a normalized score. Formula: Reddish Weight = Mass * (SCI * (AmbientLight / MaxLightPossible) * (Reflectivity / 100)).

Reddish Weight Components

Chart illustrating the impact of Surface Color Index and Ambient Light Intensity on the Reddish Weight components.

What is Reddish Weight?

Reddish weight is a conceptual metric used to quantify the perceived intensity of a "reddish" hue associated with an object, taking into account its physical properties and the surrounding environmental conditions. Unlike traditional weight, which measures mass, reddish weight attempts to assign a numerical value to a visual characteristic. It's a fictional construct for demonstration purposes, blending objective physical parameters with subjective visual perception factors.

This metric is particularly useful in fields where color intensity and its interaction with light are critical. For instance, in material science, it could hypothetically relate to how a material appears under various lighting conditions. In digital imaging or graphic design, understanding how color values are perceived under different ambient light can be crucial for accurate representation. While "reddish weight" isn't a standard scientific term, the principles it models—how objective properties and environmental factors influence perceived color—are very real and have practical applications.

Who Should Use It: Individuals or professionals interested in exploring how physical properties and light interact to create visual perception. This could include artists, designers, material scientists, or hobbyists experimenting with color theory and physics. It's also a fantastic tool for understanding how calculators can model complex interactions, even for abstract concepts.

Common Misconceptions: The most common misconception is that "reddish weight" is a physical property like mass. It is not. It's a calculated value derived from several objective inputs to represent a subjective quality (reddishness intensity). Another misconception might be that it directly correlates to the actual amount of red pigment; while the Surface Color Index is related, the interaction with light and reflectivity significantly modifies the final perceived value.

Reddish Weight Formula and Mathematical Explanation

The calculation of Reddish Weight is designed to simulate how various factors contribute to the perception of an object's "reddishness." It aims to provide a comprehensive score that goes beyond simple color values by incorporating physical mass and environmental lighting.

The core formula integrates the object's mass with a derived "Perceived Redness Value." This value is influenced by the Surface Color Index (SCI), Ambient Light Intensity, and the Surface Reflectivity.

Step-by-Step Derivation:

  1. Effective Light Factor: First, we determine how the ambient light intensity compares to a theoretical maximum or baseline light level. For simplicity, we can normalize the ambient light intensity by a reference maximum (e.g., 50000 lux). This factor adjusts the perceived color based on how bright or dim the environment is. Effective Light Factor = Ambient Light Intensity / 50000
  2. Reflectivity Modifier: The surface reflectivity dictates how much light is actually bouncing off the object towards the observer. A higher reflectivity means more of the incident light (and thus the color) is perceived. We normalize this to a 0-1 scale. Reflectivity Modifier = Surface Reflectivity (%) / 100
  3. Base Redness Value: The Surface Color Index directly represents the inherent "reddishness." We then scale this by the reflectivity modifier. Base Redness Value = Surface Color Index * Reflectivity Modifier
  4. Perceived Redness Value: This combines the base redness with the effective light factor. Brighter conditions might slightly diminish the perceived intensity of a specific hue if the SCI is moderate, or enhance it if the SCI is high. Perceived Redness Value = Base Redness Value * Effective Light Factor
  5. Final Reddish Weight: The ultimate Reddish Weight is the product of the object's mass and this Perceived Redness Value. This gives a sense of the "total perceived reddish intensity" of the object in its environment. Reddish Weight = Object Mass (kg) * Perceived Redness Value

Variable Explanations:

Understanding the variables is key to interpreting the Reddish Weight calculation:

Variable Meaning Unit Typical Range
Object Mass The physical mass of the item being assessed. kilograms (kg) 1 – 100,000+
Surface Color Index (SCI) A numerical value quantifying the inherent 'reddishness' of the object's surface. Higher values mean more red. Unitless index 0.0 – 1.0 (or higher, depending on definition)
Ambient Light Intensity The brightness of the light source illuminating the object. lux (lx) 100 – 100,000+
Surface Reflectivity The percentage of incident light that the surface reflects. Percent (%) 0 – 100
Reddish Weight The final calculated metric representing perceived reddish intensity. kg * (Unitless Index) Varies significantly based on inputs
Perceived Redness Value An intermediate score indicating how red the object appears under specific light conditions. Unitless index Varies
Effective Light Factor Normalization of ambient light to assess its impact. Unitless Varies
Variables used in the Reddish Weight calculation.

Practical Examples (Real-World Use Cases)

Let's explore how the Reddish Weight calculator can be used with realistic scenarios:

Example 1: A Red Sports Car in Bright Sunlight

Consider a sleek, newly painted red sports car. The goal is to understand its "reddish weight" under ideal viewing conditions.

  • Object Mass: 1500 kg
  • Surface Color Index (SCI): 0.85 (A vibrant, deep red paint)
  • Ambient Light Intensity: 80,000 lux (Bright midday sun)
  • Surface Reflectivity: 80% (Glossy finish, highly reflective)

Calculation Steps:

  • Effective Light Factor = 80000 / 50000 = 1.6
  • Reflectivity Modifier = 80 / 100 = 0.8
  • Base Redness Value = 0.85 * 0.8 = 0.68
  • Perceived Redness Value = 0.68 * 1.6 = 1.088
  • Reddish Weight = 1500 kg * 1.088 = 1632 kg

Interpretation: The car has a high Reddish Weight. This indicates that its significant mass combined with a strong inherent red color, high reflectivity, and intense bright sunlight results in a powerfully perceived "reddishness." This value could be used comparatively to assess the visual impact of different car colors or lighting conditions.

Example 2: A Faded Red Brick Wall in Dim Evening Light

Now, let's look at an older brick wall with a predominantly red hue, but showing signs of weathering, under less ideal lighting.

  • Object Mass: 50,000 kg (Assuming a section of a large wall)
  • Surface Color Index (SCI): 0.4 (Muted, faded red brick)
  • Ambient Light Intensity: 500 lux (Dim evening light)
  • Surface Reflectivity: 30% (Matte, rough texture, low reflectivity)

Calculation Steps:

  • Effective Light Factor = 500 / 50000 = 0.01
  • Reflectivity Modifier = 30 / 100 = 0.3
  • Base Redness Value = 0.4 * 0.3 = 0.12
  • Perceived Redness Value = 0.12 * 0.01 = 0.0012
  • Reddish Weight = 50000 kg * 0.0012 = 60 kg

Interpretation: The brick wall has a considerably lower Reddish Weight, despite its large mass. This is due to the low inherent red color (low SCI), poor reflectivity, and significantly dim lighting conditions, all of which reduce the perceived intensity of its reddish hue. This contrasts sharply with the sports car example, highlighting the calculator's ability to model diverse scenarios.

How to Use This Reddish Weight Calculator

Using the Reddish Weight calculator is straightforward. Follow these steps to get your results:

  1. Input Object Mass: Enter the total physical mass of the object you are analyzing in kilograms.
  2. Define Surface Color Index (SCI): Input a numerical value that represents how inherently "reddish" the object's surface is. A value of 0 means no perceived redness, while higher values indicate stronger redness. You might estimate this based on color charts or specific material data.
  3. Set Ambient Light Intensity: Provide the brightness of the light surrounding the object in lux. Use a light meter or estimate based on common conditions (e.g., bright sunlight is around 100,000 lux, office lighting around 500 lux).
  4. Specify Surface Reflectivity: Enter the percentage (0-100) of light that the surface reflects. Glossy surfaces have high reflectivity, while matte or rough surfaces have low reflectivity.
  5. Click Calculate: Press the "Calculate" button.

How to Read Results:

  • Primary Result (Reddish Weight): This is the main output, displayed prominently. It gives you the final calculated value in units of kg * (Unitless Index). Higher values mean a greater perceived reddish intensity relative to the object's mass and its environment.
  • Intermediate Values: These show the calculated "Perceived Redness Value," "Effective Light Factor," and "Adjusted Redness Score." They provide insight into how each input contributes to the final result.
  • Key Assumptions: This section confirms the values you entered, acting as a quick reference for the parameters used in the calculation.

Decision-Making Guidance: Use the Reddish Weight as a comparative tool. Compare the results for different objects, materials, or lighting conditions to understand which factors contribute most to perceived reddishness. For example, if you're designing a product, a higher Reddish Weight might be desirable for certain branding goals, or undesirable if aiming for a neutral appearance. Remember, this is a conceptual metric designed to explore the interplay of physical properties and perception.

Key Factors That Affect Reddish Weight Results

Several factors critically influence the calculated Reddish Weight. Understanding these helps in interpreting the results and making informed estimations:

  • Object Mass: This is a fundamental multiplier. A heavier object, even with moderate redness, can yield a higher Reddish Weight than a lighter object with intense redness. It represents the "scale" of the perceived color.
  • Surface Color Index (SCI): This is the most direct determinant of inherent redness. A material's pigment, dye, or structural color properties directly dictate its SCI. Higher SCI values mean the material is intrinsically more red.
  • Ambient Light Intensity: Light is crucial for perception. Bright light generally enhances perceived color saturation and intensity, leading to higher Reddish Weight scores, especially for objects with high SCI and reflectivity. Dim light significantly reduces perceived color, lowering the score.
  • Surface Reflectivity: How light bounces off a surface dramatically affects perceived color. Glossy, highly reflective surfaces present a more intense and vibrant color because more light reaches the observer. Matte, absorptive surfaces appear duller, reducing perceived redness.
  • Color Temperature of Light: While not explicitly in this simplified calculator, the color temperature (warm vs. cool) of the ambient light can significantly alter perceived colors. Warmer light sources tend to enhance reds, while cooler sources might diminish them.
  • Observer's Perception and Color Vision: Human perception is subjective. Factors like individual color vision deficiencies, lighting adaptation, and surrounding colors (color constancy effects) can influence how redness is perceived, which this calculator models simplistically.
  • Surface Texture and Condition: Beyond simple reflectivity, the microscopic texture of a surface (smooth vs. rough) can scatter light differently, affecting perceived color intensity and hue. Dirt, dust, or wear can also alter the effective SCI and reflectivity.

Frequently Asked Questions (FAQ)

Q1: Is Reddish Weight a real scientific measurement?

No, "Reddish Weight" is a conceptual metric created for this calculator. It's not a standard unit of measurement in physics or material science. It's designed to model the interplay between physical properties and perceived color intensity.

Q2: Can I use this to compare different shades of red?

Yes, you can. By using consistent values for mass, light, and reflectivity, you can compare the "Surface Color Index" (SCI) values needed to achieve a certain Reddish Weight, effectively comparing how inherently "red" different materials are.

Q3: What does a Reddish Weight of 0 mean?

A Reddish Weight of 0 indicates that either the object has no mass, its Surface Color Index is 0 (meaning it's not red at all), or the ambient light is effectively zero, preventing any perception of color.

Q4: How accurate is the 'Surface Color Index' input?

The accuracy depends entirely on how well you can estimate or measure the SCI for your specific object. For practical purposes, it might be a subjective rating (e.g., 0.1 for pale pink, 0.9 for deep crimson) or derived from spectrophotometer readings if available.

Q5: Does the calculator account for the color of the light source?

This simplified calculator uses "Ambient Light Intensity" (brightness) but doesn't explicitly model the color temperature of the light source. In reality, the color of light (e.g., warm incandescent vs. cool LED) significantly impacts perceived color. For advanced analysis, this would need to be considered.

Q6: What is the maximum possible Reddish Weight?

There isn't a strict theoretical maximum. It depends on extremely high inputs for mass, SCI, light intensity, and reflectivity. In practical terms, focusing on relative comparisons between scenarios is more meaningful than seeking an absolute maximum.

Q7: Can I use this for objects that aren't red?

While the metric is "Reddish Weight," you can input SCI values for other colors. An SCI of 0 would represent a non-red object. If you were interested in "bluish weight," you would conceptually modify the SCI to represent blueness. The calculator demonstrates the principle of scaling physical properties by perceived color intensity.

Q8: How does the calculator handle different units?

The calculator is designed for specific units: kilograms (kg) for mass, a unitless index for SCI, lux (lx) for ambient light, and percentage (%) for reflectivity. Ensure your inputs match these units for accurate results.

© 2023 Your Financial Website. All rights reserved.

This calculator and information are for educational and illustrative purposes only.

var maxLightReference = 50000; // Reference maximum light for normalization function validateInput(id, min, max, errorId, name) { var input = document.getElementById(id); var value = parseFloat(input.value); var errorElement = document.getElementById(errorId); errorElement.textContent = "; if (isNaN(value)) { errorElement.textContent = name + ' is required.'; return false; } if (min !== null && value max) { errorElement.textContent = name + ' cannot exceed ' + max + '.'; return false; } return true; } function calculateReddishWeight() { var isObjectMassValid = validateInput('objectMass', 0, null, 'objectMassError', 'Object Mass'); var isSurfaceColorIndexValid = validateInput('surfaceColorIndex', 0, null, 'surfaceColorIndexError', 'Surface Color Index'); var isAmbientLightIntensityValid = validateInput('ambientLightIntensity', 0, null, 'ambientLightIntensityError', 'Ambient Light Intensity'); var isSurfaceReflectivityValid = validateInput('surfaceReflectivity', 0, 100, 'surfaceReflectivityError', 'Surface Reflectivity'); if (!isObjectMassValid || !isSurfaceColorIndexValid || !isAmbientLightIntensityValid || !isSurfaceReflectivityValid) { return; } var objectMass = parseFloat(document.getElementById('objectMass').value); var surfaceColorIndex = parseFloat(document.getElementById('surfaceColorIndex').value); var ambientLightIntensity = parseFloat(document.getElementById('ambientLightIntensity').value); var surfaceReflectivity = parseFloat(document.getElementById('surfaceReflectivity').value); var effectiveLightFactor = ambientLightIntensity / maxLightReference; var reflectivityModifier = surfaceReflectivity / 100; var baseRednessValue = surfaceColorIndex * reflectivityModifier; var perceivedRednessValue = baseRednessValue * effectiveLightFactor; var reddishWeight = objectMass * perceivedRednessValue; document.getElementById('primaryResult').textContent = reddishWeight.toFixed(2) + ' kg'; document.getElementById('intermediate1').getElementsByTagName('span')[0].textContent = perceivedRednessValue.toFixed(4); document.getElementById('intermediate2').getElementsByTagName('span')[0].textContent = effectiveLightFactor.toFixed(4); document.getElementById('intermediate3').getElementsByTagName('span')[0].textContent = baseRednessValue.toFixed(4); // Renamed from Adjusted Redness Score for clarity document.getElementById('assumption1').getElementsByTagName('span')[0].textContent = objectMass.toFixed(2) + ' kg'; document.getElementById('assumption2').getElementsByTagName('span')[0].textContent = surfaceColorIndex.toFixed(2); document.getElementById('assumption3').getElementsByTagName('span')[0].textContent = ambientLightIntensity.toFixed(0) + ' lux'; document.getElementById('assumption4').getElementsByTagName('span')[0].textContent = surfaceReflectivity.toFixed(0) + ' %'; updateChart(surfaceColorIndex, ambientLightIntensity, perceivedRednessValue); } function resetCalculator() { document.getElementById('objectMass').value = '1000'; document.getElementById('surfaceColorIndex').value = '0.5'; document.getElementById('ambientLightIntensity').value = '10000'; document.getElementById('surfaceReflectivity').value = '75'; document.getElementById('objectMassError').textContent = "; document.getElementById('surfaceColorIndexError').textContent = "; document.getElementById('ambientLightIntensityError').textContent = "; document.getElementById('surfaceReflectivityError').textContent = "; document.getElementById('primaryResult').textContent = '–'; document.getElementById('intermediate1').getElementsByTagName('span')[0].textContent = '–'; document.getElementById('intermediate2').getElementsByTagName('span')[0].textContent = '–'; document.getElementById('intermediate3').getElementsByTagName('span')[0].textContent = '–'; document.getElementById('assumption1').getElementsByTagName('span')[0].textContent = '–'; document.getElementById('assumption2').getElementsByTagName('span')[0].textContent = '–'; document.getElementById('assumption3').getElementsByTagName('span')[0].textContent = '–'; document.getElementById('assumption4').getElementsByTagName('span')[0].textContent = '–'; // Clear chart var canvas = document.getElementById('reddishWeightChart'); if (canvas) { var ctx = canvas.getContext('2d'); ctx.clearRect(0, 0, canvas.width, canvas.height); } } function copyResults() { var primaryResult = document.getElementById('primaryResult').innerText; var intermediate1 = document.getElementById('intermediate1').innerText.replace('Perceived Redness Value: ', "); var intermediate2 = document.getElementById('intermediate2').innerText.replace('Effective Light Factor: ', "); var intermediate3 = document.getElementById('intermediate3').innerText.replace('Adjusted Redness Score: ', "); // Corrected label var assumption1 = document.getElementById('assumption1').innerText; var assumption2 = document.getElementById('assumption2').innerText; var assumption3 = document.getElementById('assumption3').innerText; var assumption4 = document.getElementById('assumption4').innerText; var textToCopy = "Reddish Weight Calculation Results:\n\n"; textToCopy += "Primary Result: " + primaryResult + "\n"; textToCopy += "Perceived Redness Value: " + intermediate1 + "\n"; textToCopy += "Effective Light Factor: " + intermediate2 + "\n"; textToCopy += "Base Redness Value: " + intermediate3 + "\n\n"; // Using Base Redness Value for consistency textToCopy += "Key Assumptions:\n"; textToCopy += "- " + assumption1 + "\n"; textToCopy += "- " + assumption2 + "\n"; textToCopy += "- " + assumption3 + "\n"; textToCopy += "- " + assumption4 + "\n"; var textArea = document.createElement("textarea"); textArea.value = textToCopy; 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!' : 'Copy failed!'; console.log(msg); // Optionally, provide user feedback var copyButton = document.querySelector('.btn-success'); var originalText = copyButton.innerText; copyButton.innerText = 'Copied!'; setTimeout(function() { copyButton.innerText = originalText; }, 2000); } catch (err) { console.log('Copy command failed.', err); } document.body.removeChild(textArea); } function updateChart(sci, light, perceivedRedness) { var canvas = document.getElementById('reddishWeightChart'); var ctx = canvas.getContext('2d'); // Clear previous chart ctx.clearRect(0, 0, canvas.width, canvas.height); var chartWidth = canvas.width; var chartHeight = canvas.height; var padding = 40; var chartAreaWidth = chartWidth – 2 * padding; var chartAreaHeight = chartHeight – 2 * padding; // Max values for scaling (adjust as needed) var maxSci = 1.0; var maxLight = 50000; // Based on reference var maxPerceivedRedness = 1.5; // Arbitrary realistic max for display // — Draw Axes — ctx.strokeStyle = '#ccc'; ctx.lineWidth = 1; // Y-axis (Perceived Redness) ctx.beginPath(); ctx.moveTo(padding, padding); ctx.lineTo(padding, chartHeight – padding); ctx.stroke(); ctx.textAlign = 'center'; ctx.textBaseline = 'bottom'; ctx.fillStyle = '#555′; ctx.font = '10px Arial'; ctx.fillText('Perceived Redness', padding – 20, padding / 2); // Y-axis label // X-axis (Ambient Light Intensity) ctx.beginPath(); ctx.moveTo(padding, chartHeight – padding); ctx.lineTo(chartWidth – padding, chartHeight – padding); ctx.stroke(); ctx.textAlign = 'center'; ctx.textBaseline = 'top'; ctx.fillStyle = '#555′; ctx.font = '10px Arial'; ctx.fillText('Ambient Light (lux)', chartWidth / 2, chartHeight – padding + 15); // X-axis label // — Draw Data Series 1: SCI's Influence — // Simulating how perceived redness might change with light for a fixed SCI var fixedSci = sci > 0 ? sci : 0.5; // Use input SCI or default var series1DataPoints = []; var lightSteps = 10; for (var i = 0; i maxPerceivedRedness) perceived = maxPerceivedRedness; series1DataPoints.push({ light: currentLight, perceived: perceived }); } ctx.strokeStyle = '#004a99'; // Primary color ctx.lineWidth = 2; ctx.beginPath(); series1DataPoints.forEach(function(point, index) { var x = padding + (point.light / maxLight) * chartAreaWidth; var y = chartHeight – padding – (point.perceived / maxPerceivedRedness) * chartAreaHeight; if (index === 0) { ctx.moveTo(x, y); } else { ctx.lineTo(x, y); } }); ctx.stroke(); // — Draw Data Series 2: SCI Variation — // Simulating how perceived redness changes at a fixed light level with varying SCI var fixedLight = light > 0 ? light : 10000; // Use input light or default var effectiveLightFactorFixed = fixedLight / maxLightReference; var series2DataPoints = []; var sciSteps = 10; for (var i = 0; i maxPerceivedRedness) perceived = maxPerceivedRedness; series2DataPoints.push({ sci: currentSci, perceived: perceived }); } ctx.strokeStyle = '#28a745'; // Success color ctx.lineWidth = 2; ctx.beginPath(); series2DataPoints.forEach(function(point, index) { // For this series, we need to map SCI to X-axis differently if we want to show it distinctly // For simplicity, let's overlay or rescale. Let's rescale X-axis to represent SCI variation visually. // Or, we can just draw points and label them conceptually. // Let's map perceived redness to Y-axis and use X-axis conceptually for SCI steps. var x = padding + (point.sci / maxSci) * chartAreaWidth; // Map SCI to X position var y = chartHeight – padding – (point.perceived / maxPerceivedRedness) * chartAreaHeight; if (index === 0) { ctx.moveTo(x, y); } else { ctx.lineTo(x, y); } }); ctx.stroke(); // — Add Legend — ctx.textAlign = 'left'; ctx.textBaseline = 'top'; ctx.font = '12px Arial'; // Legend Box var legendX = padding + 10; var legendY = padding + 10; var legendBoxWidth = 150; var legendBoxHeight = 50; ctx.fillStyle = 'rgba(255, 255, 255, 0.8)'; ctx.fillRect(legendX, legendY, legendBoxWidth, legendBoxHeight); ctx.strokeStyle = '#ddd'; ctx.strokeRect(legendX, legendY, legendBoxWidth, legendBoxHeight); // Legend Item 1 (SCI Influence) ctx.fillStyle = '#004a99'; ctx.fillRect(legendX + 10, legendY + 10, 15, 3); ctx.fillStyle = '#333'; ctx.fillText('Fixed SCI, Varying Light', legendX + 30, legendY + 8); // Legend Item 2 (Light Influence) ctx.fillStyle = '#28a745'; ctx.fillRect(legendX + 10, legendY + 30, 15, 3); ctx.fillStyle = '#333'; ctx.fillText('Fixed Light, Varying SCI', legendX + 30, legendY + 28); // — Add Axis Labels and Ticks (simplified) — ctx.fillStyle = '#555′; ctx.font = '10px Arial'; // Y-axis ticks var tickCountY = 5; for (var i = 0; i <= tickCountY; i++) { var value = (i / tickCountY) * maxPerceivedRedness; var yPos = chartHeight – padding – (value / maxPerceivedRedness) * chartAreaHeight; ctx.fillText(value.toFixed(1), padding – 25, yPos); ctx.beginPath(); ctx.moveTo(padding – 5, yPos); ctx.lineTo(padding, yPos); ctx.stroke(); } // X-axis ticks (representing Light Intensity) var tickCountX = 4; // Fewer ticks for clarity for (var i = 0; i <= tickCountX; i++) { var value = (i / tickCountX) * maxLight; var xPos = padding + (value / maxLight) * chartAreaWidth; ctx.fillText(value.toExponential(1) + ' lx', xPos, chartHeight – padding + 5); ctx.beginPath(); ctx.moveTo(xPos, chartHeight – padding); ctx.lineTo(xPos, chartHeight – padding + 5); ctx.stroke(); } } // Initial calculation and chart render on load document.addEventListener('DOMContentLoaded', function() { // Set canvas dimensions to match container for responsiveness var chartContainer = document.getElementById('chartContainer'); var canvas = document.getElementById('reddishWeightChart'); canvas.width = chartContainer.offsetWidth * 0.95; // Adjust for padding canvas.height = 300; // Fixed height, or make responsive // Add event listeners to inputs for real-time updates var inputs = document.querySelectorAll('.loan-calc-container input[type="number"], .loan-calc-container select'); inputs.forEach(function(input) { input.addEventListener('input', function() { // Only calculate if inputs are valid, to avoid intermediate errors if (validateInput('objectMass', 0, null, 'objectMassError', 'Object Mass') && validateInput('surfaceColorIndex', 0, null, 'surfaceColorIndexError', 'Surface Color Index') && validateInput('ambientLightIntensity', 0, null, 'ambientLightIntensityError', 'Ambient Light Intensity') && validateInput('surfaceReflectivity', 0, 100, 'surfaceReflectivityError', 'Surface Reflectivity')) { calculateReddishWeight(); } }); }); calculateReddishWeight(); // Initial calculation }); // Adjust canvas size on window resize window.addEventListener('resize', function() { var chartContainer = document.getElementById('chartContainer'); var canvas = document.getElementById('reddishWeightChart'); if (canvas && chartContainer) { canvas.width = chartContainer.offsetWidth * 0.95; // Re-calculate and update chart with current values var objectMass = parseFloat(document.getElementById('objectMass').value); var surfaceColorIndex = parseFloat(document.getElementById('surfaceColorIndex').value); var ambientLightIntensity = parseFloat(document.getElementById('ambientLightIntensity').value); var surfaceReflectivity = parseFloat(document.getElementById('surfaceReflectivity').value); updateChart(surfaceColorIndex, ambientLightIntensity, (surfaceColorIndex * (ambientLightIntensity / 50000) * (surfaceReflectivity / 100))); // Pass calculated perceived redness } });

Leave a Comment