Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
versions View all 2 versions
addClaim

zachtong/pyALDIC: v0.6.0 - Session persistence & 35x faster export

Authors: Zixiang Tong;

zachtong/pyALDIC: v0.6.0 - Session persistence & 35x faster export

Abstract

Feature release. Two headliners: your computed results now survive closing the GUI, and exports are ~35× smaller and ~5× faster. Session persistence — save results, not just settings File → Save Session now writes the whole project — parameters, ROIs, view state, and computed results — into a single .aldic file (results deduplicated, stored pickle-free). Open Session restores the exact page: same frame, field, colormap, ranges — no recompute needed. Hours of computation survive closing the GUI. Async save / load with a progress dialog; legacy v0.5 session JSON still loads. Windows: optional double-click association for .aldic files (File → Associate .aldic files). Export overhaul ~35× smaller files, ~5× faster per image (LUT colormap + binary-alpha composite + rendering at output resolution). A 90-image 4K batch: 3.3 min / 2.8 GB → 40 s / 80 MB. Streaming GIF / MP4 writer — frames encode one at a time, no RAM spike; GIFs come out ~8× smaller. Resolution presets (512 / 768 / 1024 / 1536 / 2048 / native, long edge), JPEG default with quality control; PNG / TIFF still available. GIF / MP4 frame-step decimation (keep every Nth frame, playback duration preserved). New Preview & Colorbar tab: WYSIWYG preview through the real export path; colorbar position / font / thickness / background / margin; Apply to all fields; physical-unit-aware labels. Memory on large datasets Frames now stream on demand instead of loading four full float64 stacks — ~40 GB less RAM at Run click on 300× 4K images. LRU-bounded caches stop O(N) growth in incremental mode; worker no-copy + uint8 ROI masks. Fixes Locale-proof numeric input. On comma-decimal systems (de / fr / es / pt / it / ru), typing 0.070 into a range box silently became 70. Both 0.07 and 0,07 now parse as 0.07 everywhere. Strain window opens fitted to the screen (was fixed 1280×800). Color range is now an explicit Auto / Fixed radio choice; the run progress bar no longer jumps 90 → 100. All 8 GUI locales remain at 100% translation coverage. Install / upgrade: pip install -U al-dic PyPI: https://pypi.org/project/al-dic/0.6.0/ Full changelog: https://github.com/zachtong/pyALDIC/blob/main/CHANGELOG.md 📺 Video tutorials: YouTube — English · 中文 | Bilibili — P1 中文 / P2 English 中文版本说明 (Chinese release notes) 功能版本。两大亮点:计算结果现在可以随会话保存,关闭 GUI 不再丢失; 导出体积缩小约 35 倍、速度提升约 5 倍。 会话持久化 —— 保存的不只是参数 File → Save Session 现在会把整个项目 —— 参数、ROI、视图状态、 以及计算结果 —— 全部写入单个 .aldic 文件(结果去重存储, 不使用 pickle)。 Open Session 直接回到关闭时的页面:同一帧、同一物理场、同样的 colormap 和量程,无需重新计算 —— 数小时的计算成果不再因关闭 GUI 而丢失。 保存 / 读取均为异步执行,带进度对话框;v0.5 的旧版会话 JSON 仍可打开。 Windows 可选关联 .aldic 文件(File → Associate .aldic files), 双击即可打开会话。 导出全面提速 文件缩小约 35 倍、单张导出快约 5 倍(LUT colormap + 二值 alpha 合成 + 按输出分辨率渲染)。90 张 4K 批量导出: 3.3 分钟 / 2.8 GB → 40 秒 / 80 MB。 流式 GIF / MP4 写出:逐帧编码,不再堆积内存;GIF 体积约缩小 8 倍。 分辨率预设(512 / 768 / 1024 / 1536 / 2048 / native,按长边), 默认改为 JPEG 并可调质量;PNG / TIFF 仍然可用。GIF / MP4 支持 抽帧导出(每 N 帧取 1 帧,播放时长保持不变)。 导出对话框新增 Preview & Colorbar 标签页:经由真实导出管线的 WYSIWYG 预览;colorbar 位置 / 字体 / 粗细 / 背景 / 外边距均可调; 支持 Apply to all fields 一键套用;标签自动使用物理单位。 大数据集内存优化 图像帧改为按需流式读取,不再一次性加载 4 份完整 float64 图像栈 —— 300 张 4K 数据集点击 Run 时约省 40 GB 内存。 各级缓存改为 LRU 限界,incremental 模式下内存不再随帧数 O(N) 增长; worker 零拷贝 + uint8 ROI 掩膜。 修复 数字输入不再受系统区域设置影响。 在逗号小数制系统 (de / fr / es / pt / it / ru)上,量程框中输入 0.070 曾被静默解析为 70;现在 0.07 与 0,07 都能在所有输入框中正确解析为 0.07。 应变窗口按屏幕大小自适应打开(原为固定 1280×800,小屏笔记本会溢出, macOS 上无法缩小)。 色彩量程改为显式的 Auto / Fixed 单选(主窗口、应变窗口、导出 对话框一致);运行进度条不再在结尾从 90 跳到 100。 全部 8 种界面语言(en、zh_CN、zh_TW、ja、ko、de、fr、es)保持 100% 翻译覆盖。 安装 / 升级: pip install -U al-dic PyPI: https://pypi.org/project/al-dic/0.6.0/ 完整更新日志: https://github.com/zachtong/pyALDIC/blob/main/CHANGELOG.md 📺 视频教程: YouTube — English · 中文 | Bilibili — P1 中文 / P2 English

Related Organizations
  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average