vamseeachanta
vamseeachanta/workspace-hub
相关职业SOC
基于 SOC 职业分类
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/vamseeachanta/workspace-hub --skill plotly-vertical-legends-avoid-toolbar-clash命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
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基于 SOC 职业分类
Write outbound email and external messages in Vamsee Achanta's voice — a subtle offer to help, never bold or rash claims. Load before drafting ANY email, LinkedIn/Collide reply, proposal note, or outreach sent under his name.
Save/publish analysis or computation results from ANY ecosystem repo to Hugging Face as a queryable, viewer-renderable dataset. Use when the user wants to "save results to hugging face", "publish dataset to HF", "hugging face data saving", "save analysis results", "hf dataset", "make results queryable", or "render via datasets-server API". Reshapes nested results into flat parquet tables, writes a dataset card with a viewer `configs:` block and provenance, applies license/public-vs-private routing, enforces a domain data-quality gate (faithful-to-source != correct), publishes to `aceengineer/<repo>-<projection>`, and verifies via the datasets-server API.
Clone, create, fork, configure, and manage GitHub repositories. Manage remotes, secrets, releases, and workflows. Works with gh CLI or falls back to git + GitHub REST API via curl.
| name | plotly-vertical-legends-avoid-toolbar-clash |
| description | Sub-skill of plotly: Vertical Legends (Avoid Toolbar Clash) (+5). |
| version | 1.0.0 |
| category | data-visualization |
| type | reference |
| scripts_exempt | true |
Horizontal legends at the top clash with Plotly's toolbar (zoom, pan, etc.). Place legends vertically on the right side:
fig.update_layout(
legend=dict(
orientation="v",
yanchor="top", y=1.0,
xanchor="left", x=1.02,
font=dict(size=10),
tracegroupgap=2,
),
margin=(l=, r=, t=, b=),
)
When comparing solvers across headings, loop headings first then solvers.
This groups legend entries as: H0-AQWA / H0-OrcaWave / H45-AQWA / H45-OrcaWave
making it easy to toggle all solvers for a given heading:
for heading_idx in heading_indices:
heading_label = f"{headings[heading_idx]:.0f}"
for solver_name in solver_names:
fig.add_trace(go.Scatter(
x=frequencies, y=values,
name=f"H{heading_label} {solver_name}",
legendgroup=f"H{heading_label}",
))
Omit headings where response is physically insignificant (< 1% of DOF peak). This avoids plotting zero-response cases like surge@90deg or sway@0deg:
def get_significant_headings(dof_data, all_headings, threshold=0.01):
overall_peak = max(np.max(np.abs(solver_data)) for solver_data in all_solvers)
cutoff = overall_peak * threshold
return [h for h in all_headings
if any(np.max(np.abs(solver[h])) > cutoff for solver in all_solvers)]
For multi-plot single-page reports, load Plotly CDN once in <head> and use
include_plotlyjs=False for each inline plot div to avoid duplicate loading:
# In HTML <head>:
# <script src="https://cdn.plot.ly/plotly-2.27.0.min.js"></script>
# For each plot div:
plot_html = fig.to_html(full_html=False, include_plotlyjs=False)
Use engineering-appropriate monospace fonts for tables and numeric values:
.solver-table td {
font-family: 'SF Mono', 'Cascadia Code', 'Consolas', 'Monaco', monospace;
font-size: 0.85em;
}
/* Alternating rows */
tbody tr:nth-child(even) { background: #f8f9fa; }
tbody tr:nth-child(odd) { background: #fff; }
tbody tr:hover { background: #ebf5fb; }
/* Dark header */
th { background: #34495e; color: #fff; padding: 0.5em 0.75em; }
/* Section rows in tables */
*See sub-skills for full details.*