# Aider chat conversation:
USER: in each graph, give each model a second bar showing row.percent_cases_well_formed
ASSISTANT: Here are the changes to add a second bar for `row.percent_cases_well_formed` to each graph:
docs/leaderboards/index.md
```markdown
<<<<<<< SEARCH
var leaderboardData = {
labels: [],
datasets: [{
label: 'Percent correct on code editing tasks',
data: [],
backgroundColor: 'rgba(54, 162, 235, 0.2)',
borderColor: 'rgba(54, 162, 235, 1)',
borderWidth: 1
}]
};
{% for row in edit_sorted %}
leaderboardData.labels.push('{{ row.model }}');
leaderboardData.datasets[0].data.push({{ row.pass_rate_2 }});
{% endfor %}
=======
var leaderboardData = {
labels: [],
datasets: [{
label: 'Percent correct on code editing tasks',
data: [],
backgroundColor: 'rgba(54, 162, 235, 0.2)',
borderColor: 'rgba(54, 162, 235, 1)',
borderWidth: 1
},
{
label: 'Percent cases well formed',
data: [],
backgroundColor: 'rgba(255, 99, 132, 0.2)',
borderColor: 'rgba(255, 99, 132, 1)',
borderWidth: 1
}]
};
{% for row in edit_sorted %}
leaderboardData.labels.push('{{ row.model }}');
leaderboardData.datasets[0].data.push({{ row.pass_rate_2 }});
leaderboardData.datasets[1].data.push({{ row.percent_cases_well_formed }});
{% endfor %}
>>>>>>> REPLACE
```
docs/leaderboards/index.md
```markdown
<<<<<<< SEARCH
var leaderboardData = {
labels: [],
datasets: [{
label: 'Percent correct on code refactoring tasks',
data: [],
backgroundColor: 'rgba(54, 162, 235, 0.2)',
borderColor: 'rgba(54, 162, 235, 1)',
borderWidth: 1
}]
};
{% for row in refac_sorted %}
leaderboardData.labels.push('{{ row.model }}');
leaderboardData.datasets[0].data.push({{ row.pass_rate_1 }});
{% endfor %}
=======
var leaderboardData = {
labels: [],
datasets: [{
label: 'Percent correct on code refactoring tasks',
data: [],
backgroundColor: 'rgba(54, 162, 235, 0.2)',
borderColor: 'rgba(54, 162, 235, 1)',
borderWidth: 1
},
{
label: 'Percent cases well formed',
data: [],
backgroundColor: 'rgba(255, 99, 132, 0.2)',
borderColor: 'rgba(255, 99, 132, 1)',
borderWidth: 1
}]
};
{% for row in refac_sorted %}
leaderboardData.labels.push('{{ row.model }}');
leaderboardData.datasets[0].data.push({{ row.pass_rate_1 }});
leaderboardData.datasets[1].data.push({{ row.percent_cases_well_formed }});
{% endfor %}
>>>>>>> REPLACE
```
This adds a second dataset to each chart's `leaderboardData`, with a label of "Percent cases well formed". It sets different colors for the bars and borders.
Then in the loop that populates the data, it pushes the `row.percent_cases_well_formed` value into the second dataset.
With these changes, each model will have two bars - one for the pass rate and one for the percent of cases that were well formed.
# Aider chat conversation:
USER: ReferenceError: Can't find variable: Chart
ASSISTANT: The error message "ReferenceError: Can't find variable: Chart" suggests that the Chart.js library is not being loaded before the script that is trying to use it. To fix this, we need to ensure that the Chart.js library is included in the HTML document before the script that initializes the chart.
Here is the diff to add the Chart.js library to the `docs/leaderboard.md` file:
```diff
--- docs/leaderboard.md
+++ docs/leaderboard.md
@@ ... @@
<canvas id="leaderboardChart" width="800" height="450"></canvas>
+<script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
<script>
document.addEventListener('DOMContentLoaded', function () {
var ctx = document.getElementById('leaderboardChart').getContext('2d');
var leaderboardData = {
labels: [],
datasets: [{
label: 'Percent correct',
data: [],
backgroundColor: 'rgba(54, 162, 235, 0.2)',
borderColor: 'rgba(54, 162, 235, 1)',
borderWidth: 1
}]
};
@@ ... @@
```
This diff adds the Chart.js library from a CDN before the script tag that contains the chart initialization code. This should resolve the `ReferenceError` by ensuring that the `Chart` variable is defined when the script runs.
# Aider chat conversation:
USER: use chart.js to fill draw a bar graph in the canvas. is liquid templating to pull the "model" as bar label and "second" as bar height
ASSISTANT: ```diff
--- docs/leaderboard.md
+++ docs/leaderboard.md
@@ ... @@
-<canvas id="leaderboardChart" width="800" height="450"></canvas>
+<canvas id="leaderboardChart" width="800" height="450"></canvas>
+<script>
+ document.addEventListener('DOMContentLoaded', function () {
+ var ctx = document.getElementById('leaderboardChart').getContext('2d');
+ var leaderboardData = {
+ labels: [],
+ datasets: [{
+ label: 'Percent correct',
+ data: [],
+ backgroundColor: 'rgba(54, 162, 235, 0.2)',
+ borderColor: 'rgba(54, 162, 235, 1)',
+ borderWidth: 1
+ }]
+ };
+
+ {% for row in site.data.leaderboard | sort: 'second' | reverse %}
+ leaderboardData.labels.push('{{ row.model }}');
+ leaderboardData.datasets[0].data.push({{ row.second }});
+ {% endfor %}
+
+ var leaderboardChart = new Chart(ctx, {
+ type: 'bar',
+ data: leaderboardData,
+ options: {
+ scales: {
+ yAxes: [{
+ ticks: {
+ beginAtZero: true
+ }
+ }]
+ }
+ }
+ });
+ });
+</script>
```
This diff adds a script tag to the `docs/leaderboard.md` file that uses Chart.js to draw a bar graph on the canvas element with the id `leaderboardChart`. The script waits for the DOM to be fully loaded before executing. It then initializes the chart with the model names as labels and the corresponding percentages as the bar heights, using Liquid templating to pull the data from the site's data files.
# Aider chat conversation:
USER: add a bar chart using chart.js
ASSISTANT: To add a bar chart using Chart.js to the `leaderboard.md` file, you will need to include the Chart.js library, prepare a canvas element where the chart will be rendered, and write the JavaScript code to create the bar chart. Here's the diff that adds these elements to the `leaderboard.md` file:
```diff
--- docs/leaderboard.md
+++ docs/leaderboard.md
@@ ... @@
<table style="width: 90%; max-width: 800px; margin: auto; border-collapse: collapse; box-shadow: 0 2px 4px rgba(0,0,0,0.1); font-size: 14px;">
<!-- Table content -->
</table>
+
+<canvas id="leaderboardChart" width="800" height="450"></canvas>
+
+<script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
+<script>
+document.addEventListener('DOMContentLoaded', function () {
+ var ctx = document.getElementById('leaderboardChart').getContext('2d');
+ var leaderboardData = {
+ labels: [], // Populate with model names
+ datasets: [{
+ label: 'Percent correct',
+ data: [], // Populate with percent correct values
+ backgroundColor: 'rgba(54, 162, 235, 0.2)',
+ borderColor: 'rgba(54, 162, 235, 1)',
+ borderWidth: 1
+ }]
+ };
+
+ // Fetch leaderboard data and populate the chart
+ fetch('/_data/leaderboard.csv')
+ .then(function (response) {
+ return response.text();
+ })
+ .then(function (text) {
+ var rows = text.split('\n');
+ rows.forEach(function (row) {
+ var columns = row.split(',');
+ if (columns.length === 4) {
+ leaderboardData.labels.push(columns[0]);
+ leaderboardData.datasets[0].data.push(parseFloat(columns[1]));
+ }
+ });
+ new Chart(ctx, {
+ type: 'bar',
+ data: leaderboardData,
+ options: {
+ scales: {
+ y: {
+ beginAtZero: true
+ }
+ }
+ }
+ });
+ });
+});
+</script>
```
This diff adds a canvas element for the chart, includes the Chart.js library from a CDN, and provides a script that initializes the bar chart with data from the leaderboard CSV file. The script fetches the CSV data, parses it, and populates the chart with the model names and their corresponding "Percent correct" values.
