支道林
Multi tool usebody.skin-minerva .mw-parser-output table.infobox captiontext-align:center
 | 支遁 | |
|
|---|
| 字 |
道林 |
|---|
| 出生 |
314年
陈留
|
|---|
| 著名成就 |
提出“即色本空”，创立了般若学即色义 |
|---|
| 宗派 |
般若学
|
|---|
| 别称 |
支公、林公 |
|---|
| 駐錫於 |
支山寺、霊嘉寺 |
|---|
| 著作 |
文翰集 |
|---|
支道林（314年－366年），名遁，字道林，以字行。本為关姓，晉河南陈留人。
生平
河南陈留人，幼年随家人南渡到江南。早年曾隐居吳縣（今江蘇蘇州）餘杭山，年二十五出家，其师为西域月支人，改姓支。長相欠佳，“双眼黯黯明黑”，阮裕“欲闻其言，恶见其面”[1]。出家後雲遊京師，住白馬寺，潜心研究佛道，“沉思《道行》之品，委曲《慧印》之经”，好養名马，自云：“重其神骏。斯图也，非彼人之徒欤！”。又有贈鶴，他說：“爾沖天物，寧為耳目之玩乎”遂放之，今沃洲尚留有放鶴峰、養馬坡、支遁嶺遺跡[2]。王濛赞扬他“造微之功不减辅嗣”，孙绰称赞支道林“拔新领异，胸怀所及乃自佳”。陈郡殷融以为是卫玠再世。謝安說他“如九方皋之相马，略其玄黄，取其儁逸。”[3]王坦之认为支道林只会诡辩[4]。
支道林常在白马寺与劉系之、馮懷等人谈论《庄子逍遥篇》，西晉郭象的注解里面有一句说：各适性以为逍遥。支遁不这么认为，辩论说，桀纣以残害为本性，如果说适性就是逍遥，那么他们也是很逍遥的了。于是注《逍遥篇》，群儒旧学莫不叹服，为般若学六大家之一。升平元年（357年），移居剡縣石城山（今新昌縣縣城南郊）棲光寺[5]，勤於著書立說，晋太和元年闰四月四日圓寂於剡县石城山住所，享年五十三岁[6]。戴逵路經其墓，叹曰：“德音未远，而拱木已繁，冀神理绵绵，不与气运俱尽耳。”[7]
注釋
^ 裴启《语林》
^ 《嘉泰會稽志》卷九云：“沃州真覺院在縣東四十里，方新昌未為縣時，在剡縣南三十里，居沃州之陽，天姥之陰，南對天台山之華頂、赤城，北對四明山之金庭、石鼓，而北有支遁養馬坡，放鶴峰，……晉帛道猷、竺道潛、支道林……皆常居焉。會昌廢......治平三年賜今額。”
^ 《世说新语·轻诋》
^ 《世说新语·轻诋篇》
^ 《浙江分縣簡志．新昌縣．名勝古蹟》稱，粱朝時，隱岳、元化、棲光三寺合併為寶相寺，現稱大佛寺。
^ 《高僧传》卷四：“遁先经余姚坞山中住。至于名辰犹还坞中。或问其意。答云。谢安在昔数来见辄移旬日。今触情举目莫不兴想。后病甚。移还坞中。以晋太和元年闰四月四日终于所住。春秋五十有三。”
^ 《世說》引《建康實錄》記“墓在石城。戴安道過而嘆曰：‘德音未遠而拱木已繁，冀神理綿綿不於氣運懼盡耳’！”
參考文獻
bl9I3DQ Ped
Popular posts from this blog
Ramiro Burr's New Blog - to go back: www.ramiroburr.com From Latin rock to reggaeton, boleros to blues,Tex-Mex to Tejano, conjunto to corridos and beyond, Ramiro Burr has it covered. If you have a new CD release, a trivia question or are looking for tour info, post a message here or e-mail Ramiro directly at: musicreporter@gmail.com Top Tejano songwriter Luis Silva dead of heart attack at 64 By Ramiro Burr on October 23, 2008 8:40 AM | Permalink | Comments (12) | TrackBacks (0) UPDATE: Luis Silva Funeral Service details released Visitation 4-9 p.m. Saturday, Rosary service 6 p.m. Saturday at Porter Loring, 1101 McCullough Ave Funeral Service 10:30 a.m. Monday St. Anthony De Padua Catholic Church, Burial Service at Chapel Hills, 7735 Gibbs Sprawl Road. Porter Loring (210) 227-8221 Related New Flash: Irma Laura Lopez: long time record promoter killed in accident NewsFlash: 9:02 a.m. (New comments below) Luis Silva , one of the most well-known ...
1 I having trouble getting my ResourceDictionary.MergedDictionaries to load from app.xaml. My WPF app has a static class with a Main defined and startup object set to it. Within Main I created an instance of App and run it. The override OnStartup fires and the mainwindow.cs InitializeComponent gives the error "Message "Cannot find resource named 'MaterialDesignFloatingActionMiniAccentButton'. If I put the resources in the mainwindow.xaml everything is fine, but I wanted them to load at the app level so I they are not in each page. Any help appreciated. public partial class App protected override void OnStartup(StartupEventArgs e) base.OnStartup(e); var app = new MainWindow(); var context = new MainWindowViewModel(); app.DataContext = context; app.Show(); from the Main.. var app = new App(); app.Run(); app.xaml.. <Application x:Class="GS.Server.App" xmlns="http://schemas.microsoft.com/winfx/2006/xaml/presentation" xmlns:...
up vote 2 down vote favorite There is a clear pattern that show for two separate subsets (set of columns); If one value is missing in a column, values of other columns in the same subset are missing for any row. Here is a visualization of missing data My tries up until now, I used ycimpute library to learn from other values, and applied Iterforest. I noted, score of Logistic regression is so weak (0.6) and thought Iterforest might not learn enough or anyway, except from outer subset which might not be enough? for example the subset with 11 columns might learn from the other columns but not from within it's members, and the same goes for the subset with four columns. This bar plot show better quantity of missings So of course, dealing with missings is better than dropping rows because It would affect my prediction which does contain the same missings quantity relatively. Any better way to deal with these ? [EDIT] The nullity pattern is confirmed: machine-learning cor...
