MindPlot

Il tuo co-scienziato AI personale

Trasforma dati grezzi in informazioni pronte per la pubblicazione. Dalla pulizia dei dati, alla modellizzazione e all'analisi statistica, fino a visualizzazioni e report professionali — il tuo kit completo di strumenti AI.

Mindplot Demo

MindPlot Offer

Grafici scientifici curati e pronti per la pubblicazione

Intelligenza artificiale
Intelligenza artificiale
Grafici scientifici
Grafici scientifici
3D
3D
Grafici accademici
Grafici accademici
Test statistico
Test statistico
Modelli di regressione
Modelli di regressione
Machine learning
Machine learning
analisi bioinformatica
analisi bioinformatica

Funzionalità di MindPlot

Dialoga con i tuoi dati

AI conversazionale per comandi naturali. Nessuna programmazione necessaria.

Pulizia automatica dei dati

Correggi istantaneamente valori mancanti e anomalie

Modifica al volo

Cambia caratteri, colori e scale all'istante

AI Power

Più intelligente. L'AI ti capisce.

Inserisci qualsiasi cosa

Immagini, Excel, CSV

Esportazione flessibile

Bitmap (png,jpg), vettoriale (svg,pdf)

Report statistici completi

Word/PDF generato automaticamente con metodi e risultati

Esporta codice

Scarica il codice Python per verificare le analisi

MindPlot research blog

Ideas, methods, and evidence.

View all blogs →
01

如何用 Aeon 分析时间序列:DTW 分类、聚类与相似度计算

Aeon 提供了一套面向时间序列的 Python 工具,可以在保留观测顺序的前提下比较曲线、识别类别并探索分组。下面的例子从六条容易核对的短曲线出发:DTW 最近邻模型判断两条未参与训练的曲线是上升还是下降,时间序列 k 均值恢复两个趋势组,距离计算则解释相似曲线与相反曲线为何会被区别对待。两条留出曲线都得到正确分类;两条相似上升曲线的 DTW 距离是 0.06,上升曲线与下降曲线之间的距离是 70.0。这些结果适合验证分析流程是否真正工作,但六条刻意简化的曲线不能代表模型在真实传感器、临床或实验数据上的准确率。

Read article →
02

如何用 Dask DataFrame、Array、Delayed 与 Distributed 分析分区科学数据

可复现的 Dask 工作流能够惰性读取分区测量数据,执行筛选和分组汇总,写出分区 Parquet 数据集,变换分块数值数组,并求值具有明确依赖关系的任务图,而不必把所有中间数据同时塞入内存。经过验证的演示中,三个 CSV 分区共包含 12 行,value 总和为 306。按 value = 18 筛选后,control 的计数、和、均值分别为 4、96、24.0;treated 分别为 6、186、31.0。另一个 6 × 8 分块数组得到从 33.5 到 44.0 的八个列均值;六个延迟平方任务之和为 91。Dask 2026.3.0 在保留的第 5 次尝试中完成这些功能。由于聊天沙箱不允许

Read article →
03

如何使用 Python、psutil 与可复现系统清单检测科学计算资源

开展科学计算之前,最重要但经常被忽略的一步,是先测量真正执行任务的机器,而不是根据设备型号、云主机名称或经验猜测可用资源。本次经过完整验证的实例检测到:Linux x8664 主机拥有 8 个物理 CPU 核心、16 个逻辑核心、31.06 GiB 总内存、16.06 GiB 当前可用内存、103.12 GiB 项目文件系统可用空间,并且没有检测到可用 GPU 加速器。原生检测器给出的并行上限建议为 14 个工作进程;结合内存和 I/O 风险,更稳妥的操作建议是从 8–12 个工作进程开始,再依据真实负载逐步扩展。

Read article →
04

如何使用 GNU Octave 求解并审计 MATLAB 兼容的线性代数流程

GNU Octave 将线性方程组求解为 x=[2,3],并独立核验该预期向量。5个信号观测的均值为6,样本标准差为6.59545297913646。流程保留了MATLAB兼容的MAT工作区以及栅格和矢量图。。该结果在保留的第11次尝试中通过原生执行、真实聊天端到端执行和语义产物验证,只能在本演示的数据、方法和限制范围内解释。

Read article →
05

如何使用 Matplotlib 创建可发表的多面板科学图

流程读取6条测量记录,使用Matplotlib面向对象接口创建两个坐标轴,并绘制折线、误差棒、散点、注释与图例。输出为1823×1223像素、200 dpi的PNG,以及保留可编辑文字的SVG。。该结果在保留的第9次尝试中通过原生执行、真实聊天端到端执行和语义产物验证,只能在本演示的数据、方法和限制范围内解释。

Read article →

Domande frequenti

01

Cos'è MindPlot e come funziona?

MindPlot transforms complex datasets into publication-ready plots without coding. Upload your data, describe what you want, and get professional visualizations in one click.

02

Servono competenze di programmazione per usare MindPlot?

Nessuna programmazione richiesta! La nostra interfaccia conversazionale ti permette di creare visualizzazioni sofisticate usando il linguaggio naturale, perfetta per qualsiasi livello di competenza.

03

Cosa rende MindPlot diverso e posso personalizzare i grafici?

Il nostro sistema multi-agente unico consente la personalizzazione dei grafici in tempo reale senza lente rielaborazioni. Regola stili, colori e layout istantaneamente tramite la nostra interfaccia conversazionale.

04

What chart and plot types can MindPlot make?

MindPlot generates publication-ready scientific charts of every kind — Kaplan-Meier survival curves, meta-analysis forest plots, volcano plots, correlation-matrix heatmaps, ROC curves, box, violin and beeswarm plots, regression, scatter and PCA plots, and more. Just upload a CSV and describe what you need.

05

I miei dati sono al sicuro? Li usate per addestrare i modelli?

La privacy dei tuoi dati è la nostra priorità. NON utilizziamo i tuoi dati per addestrare i nostri modelli. Tutta l'elaborazione è sicura e riservata.

MindPlot® AI Scientific Data Toolkit

MindPlot® is an AI co-scientist for the entire research workflow — read, analyze, write, visualize, and present. Our unified suite (MindReader, MindChat, MindSheet, MindWriter, MindPlot, MindChart, MindDraw, MindFlow, MindVector, MindSlide, MindNote) helps researchers go from papers and raw data to publication-quality results in one place.

The Complete AI Research Suite

  • MindReader: AI paper reader and literature summarizer — upload PDFs to summarize methods, extract findings, and translate.
  • MindChat: One AI chat for ChatGPT, Claude, Gemini, and DeepSeek — switch models mid-conversation, pay per token.
  • MindSheet: AI spreadsheet to clean, transform, and analyze research data with natural language — no formulas required.
  • MindWriter: AI academic writing assistant for drafting papers, grants, and latex manuscripts.
  • MindPlot: Publication-quality scientific static plots (Matplotlib/Seaborn) with APA/Nature styling — Kaplan-Meier survival curves, forest plots, volcano plots, heatmaps, box & violin plots, and more.
  • MindChart: Interactive data exploration charts (ECharts) for presentations and web sharing — correlation matrix heatmaps, ROC curves, regression and time-series plots.
  • MindDraw: Scientific illustration generator for graphical abstracts and mechanism diagrams.
  • MindFlow: AI diagramming tool for research workflows, process maps, and experiment logic.
  • MindVector: AI vector graphics editor for figures, scientific diagrams, and editable SVG artwork.
  • MindSlide: AI presentation maker for academic talks, lab meetings, and thesis defense slides.
  • MindNote: AI knowledge hub that captures and links your papers, chats, and figures into a searchable second brain.

Key Capability: Publication-Ready Scientific Visualization

  • Automated statistical analysis (t-test, ANOVA) integrated with visualization
  • High-DPI exports (300dpi+) for journal submission (PDF, SVG, PNG, EPS)
  • Strict adherence to academic styling guidelines (APA, Nature, Science)

Scientific Chart & Plot Types We Generate

Describe your data and MindPlot's AI builds the exact chart you need: Kaplan-Meier survival curves and survival-plot generators, meta-analysis forest plots, volcano plots for differential expression, correlation-matrix heatmaps, ROC curves, box, violin, beeswarm and density plots, regression and scatter plots, PCA plots, dendrograms, and confusion matrices — all publication-ready, no coding.

  • Kaplan-Meier survival curve generator (survival analysis, log-rank)
  • Forest plot maker for meta-analysis and effect sizes
  • Volcano plot generator for RNA-seq and proteomics
  • Heatmap and correlation-matrix generator (CSV to heatmap)
  • Box, violin, and beeswarm plots with built-in statistical tests
  • ROC curves, regression plots, and confusion matrices
  • CSV to chart in one click — upload data, get a figure

Trusted by Scientists Worldwide

  • Ricerca accademica e pubblicazioni scientifiche
  • Ricerca biomedica e farmaceutica
  • Scienze ambientali e ricerca sul clima
  • Scienze sociali e psicologia
  • Ingegneria e analisi tecnica
  • Business intelligence e ricerche di mercato
  • Controllo qualità e produzione
  • Analisi e rendicontazione finanziaria

Informazioni su Cosinx AI

Developed by Cosinx AI, a leading artificial intelligence company specializing in scientific visualization and drug discovery. Our mission is to democratize data science and make advanced analytics accessible to researchers and professionals across all disciplines.