{ "cells": [ { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false }, "outputs": [], "source": [ "%matplotlib inline\n", "import numpy as np" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ ">作者 : *Didrik Pinte*\n", "\n", "Traits项目允许你可以向Python项目属性方便的添加验证、初始化、委托、通知和图形化界面。\n", "\n", "在这个教程中，我们将研究Traits工具包并且学习如何动态减少你所写的锅炉片代码，进行快速的GUI应用开发，以及理解Enthought工具箱中其他部分的想法。\n", "\n", "Traits和Enthought工具箱是基于BSD-style证书的开源项目。\n", "\n", "---\n", "**目标受众**\n", "\n", "Python中高级程序员\n", "---\n", "\n", "---\n", "**要求**\n", "\n", "- [wxPython](http://www.wxpython.org/)、[PyQt](https://riverbankcomputing.com/software/pyqt/intro)或[PySide](https://pyside.github.io/docs/pyside/)之一\n", "- Numpy和Scipy\n", "- [Enthought工具箱](http://code.enthought.com/projects)\n", "- 所有需要的软件都可以通过安装[EPD免费版](https://store.enthought.com/)来获得\n", "---\n", "\n", "---\n", "\n", "**教程内容**\n", "- 介绍\n", "- 例子\n", "- Traits是什么\n", " - 初始化\n", " - 验证\n", " - 文档\n", " - 可视化: 打开一个对话框\n", " - 推迟\n", " - 通知\n", " - 一些更高级的特征\n", " \n", "## 3.4.1 介绍\n", "\n", "Enthought工具箱可以构建用于数据分析、2D绘图和3D可视化的精密应用框架。这些强力可重用的组块是在BSD-style证书下发布的。\n", "\n", "Enthought工具箱主要的包是：\n", "\n", "- Traits - 基于组块的方式构建我们的应用。\n", "- Kiva - 2D原生支持基于路径的rendering、affine转化、alpha混合及其它。\n", "- Enable - 基于对象的2D绘图画布。\n", "- Chaco - 绘图工具箱，用于构建复杂的交互2D图像。\n", "- Mayavi -基于VTK的3D科学数据可视化\n", "- Envisage - 应用插件框架，用于构建脚本化可扩展的应用\n", "\n", "![](http://www.scipy-lectures.org/_images/ETS.jpg)\n", "\n", "在这篇教程中，我们将关注Traits。\n", "\n", "## 3.4.2 例子\n", "\n", "在整个这篇教程中，我们将使用基于水资源管理简单案例的一个样例。我们将试着建模一个水坝和水库系统。水库和水坝有下列参数：\n", "\n", "- 名称\n", "- 水库的最小和最大容量 [$hm^3$]\n", "- 水坝的高度和宽度[$m$]\n", "- 蓄水面积[$km^2$]\n", "- 水压头[$m$]\n", "- 涡轮的动力[$MW$]\n", "- 最小和最大放水量[$m^3/s$]\n", "- 涡轮的效率\n", "\n", "水库有一个已知的运转情况。一部分是与基于放水量有关的能量产生。估算水力发电机电力生产的简单公式是$P = \\rho hrgk$, 其中\n", "\n", "- P 以瓦特为单位的功率, \n", "- \\rho 是水的密度 ($~1000 kg/m^3$),\n", "- h 是水的高度,\n", "- r 是以每秒立方米为单位的流动率,\n", "- g 重力加速度，9.8 $m/s^2$,\n", "- k 是效率系数，范围从0到1。\n", "\n", "年度的电能生产取决于可用的水供给。在一些设施中，水流率在一年中可能差10倍。\n", "\n", "运行状态的第二个部分是蓄水量，蓄水量(storage)依赖于控制和非控制参数：\n", "\n", "$storage_{t+1} = storage_t + inflows - release - spillage - irrigation$\n", "\n", "---\n", "本教程中使用的数据不是真实的，可能甚至在现实中没有意义。\n", "\n", "---\n", "\n", "## 3.4.3 Traits是什么\n", "\n", "trait是可以用于常规Python对象属性的类型定义，给出属性的一些额外特性:\n", "\n", "- 标准化:\n", " - 初始化\n", " - 验证\n", " - 推迟\n", "- 通知\n", "- 可视化\n", "- 文档\n", "\n", "类可以自由混合基于trait的属性与通用Python属性，或者选择允许在这个类中只使用固定的或开放的trait属性集。类定义的Trait属性自动继承自由这个类衍生的其他子类。\n", "\n", "创建一个traits类的常用方式是通过扩展**HasTraits**基础类，并且定义类的traits :" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from traits.api import HasTraits, Str, Float\n", "\n", "class Reservoir(HasTraits):\n", "\n", " name = Str\n", " max_storage = Float" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---\n", "\n", "对Traits 3.x用户来说\n", "\n", "如果使用Traits 3.x, 你需要调整traits包的命名空间:\n", "\n", "- traits.api应该为enthought.traits.api\n", "- traitsui.api应该为enthought.traits.ui.api\n", "\n", "---\n", "\n", "像这样使用traits类和使用其他Python类一样简单。注意，trait值通过关键词参数传递:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ "reservoir = Reservoir(name='Lac de Vouglans', max_storage=605)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 3.4.3.1 初始化\n", "\n", "所有的traits都有一个默认值来初始化变量。例如，基础python类型有如下的trait等价物:\n", "\n", "\n", "|Trait|Python类型|内置默认值|\n", "|-----|-----------|----------------------|\n", "|Bool|Boolean|False|\n", "|Complex|Complex number|0+0j|\n", "|Float|Floating point number|0.0|\n", "|Int|Plain integer|0|\n", "|Long|Long integer|0L|\n", "|Str|String|''|\n", "|Unicode|Unicode|u''|\n", "\n", "存在很多其他预定义的trait类型: Array, Enum, Range, Event, Dict, List, Color, Set, Expression, Code, Callable, Type, Tuple, etc。\n", "\n", "自定义默认值可以在代码中定义:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from traits.api import HasTraits, Str, Float\n", "\n", "class Reservoir(HasTraits):\n", "\n", " name = Str\n", " max_storage = Float(100)\n", "\n", "reservoir = Reservoir(name='Lac de Vouglans')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---\n", "复杂初始化\n", "\n", "当一个trait需要复杂的初始化时，可以实施\\_XXX\\_默认魔法方法。当调用XXX trait时，它会被懒惰的调用。例如：\n", "\n", "---" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def _name_default(self):\n", " \"\"\" Complex initialisation of the reservoir name. \"\"\"\n", "\n", " return 'Undefined'" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 3.4.3.2 验证\n", "\n", "当用户试图设置trait的内容时，每一个trait都会被验证:" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [ { "ename": "TraitError", "evalue": "The 'max_storage' trait of a Reservoir instance must be a float, but a value of '230' was specified.", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mTraitError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mreservoir\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mReservoir\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Lac de Vouglans'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmax_storage\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m605\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mreservoir\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmax_storage\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'230'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[0;32m/Library/Python/2.7/site-packages/traits/trait_handlers.pyc\u001b[0m in \u001b[0;36merror\u001b[0;34m(self, object, name, value)\u001b[0m\n\u001b[1;32m 170\u001b[0m \"\"\"\n\u001b[1;32m 171\u001b[0m raise TraitError( object, name, self.full_info( object, name, value ),\n\u001b[0;32m--> 172\u001b[0;31m value )\n\u001b[0m\u001b[1;32m 173\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 174\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mfull_info\u001b[0m \u001b[0;34m(\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobject\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mTraitError\u001b[0m: The 'max_storage' trait of a Reservoir instance must be a float, but a value of '230' was specified." ] } ], "source": [ "reservoir = Reservoir(name='Lac de Vouglans', max_storage=605)\n", "\n", "reservoir.max_storage = '230'" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 3.4.3.3 文档\n", "\n", "从本质上说，所有的traits都提供关于模型自身的文档。创建类的声明方式使它是自解释的:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from traits.api import HasTraits, Str, Float\n", "\n", "class Reservoir(HasTraits):\n", "\n", " name = Str\n", " max_storage = Float(100)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "trait的**desc**元数据可以用来提供关于trait更多的描述信息:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from traits.api import HasTraits, Str, Float\n", "\n", "class Reservoir(HasTraits):\n", "\n", " name = Str\n", " max_storage = Float(100, desc='Maximal storage [hm3]')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "现在让我们来定义完整的reservoir类:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Releasing 80 m3/s produces 1.3561344e+11 kWh\n" ] } ], "source": [ "from traits.api import HasTraits, Str, Float, Range\n", "\n", "class Reservoir(HasTraits):\n", " name = Str\n", " max_storage = Float(1e6, desc='Maximal storage [hm3]')\n", " max_release = Float(10, desc='Maximal release [m3/s]')\n", " head = Float(10, desc='Hydraulic head [m]')\n", " efficiency = Range(0, 1.)\n", "\n", " def energy_production(self, release):\n", " ''' Returns the energy production [Wh] for the given release [m3/s]\n", " '''\n", " power = 1000 * 9.81 * self.head * release * self.efficiency\n", " return power * 3600\n", "\n", "\n", "if __name__ == '__main__':\n", " reservoir = Reservoir(\n", " name = 'Project A',\n", " max_storage = 30,\n", " max_release = 100.0,\n", " head = 60,\n", " efficiency = 0.8\n", " )\n", "\n", " release = 80\n", " print 'Releasing {} m3/s produces {} kWh'.format(\n", " release, reservoir.energy_production(release)\n", " )" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 3.4.3.4 可视化: 打开一个对话框\n", "\n", "Traits库也关注用户界面，可以弹出一个Reservoir类的默认视图:" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "reservoir1 = Reservoir()\n", "reservoir1.edit_traits()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "![](http://www.scipy-lectures.org/_images/reservoir_default_view.png)\n", "\n", "TraitsUI简化了创建用户界面的方式。HasTraits类上的每一个trait都有一个默认的编辑器，将管理trait在屏幕上显示的方式 (即Range trait显示为一个滑块等)。\n", "\n", "与Traits声明方式来创建类的相同渠道，TraitsUI提供了声明的界面来构建用户界面代码:" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from traits.api import HasTraits, Str, Float, Range\n", "from traitsui.api import View\n", "\n", "class Reservoir(HasTraits):\n", " name = Str\n", " max_storage = Float(1e6, desc='Maximal storage [hm3]')\n", " max_release = Float(10, desc='Maximal release [m3/s]')\n", " head = Float(10, desc='Hydraulic head [m]')\n", " efficiency = Range(0, 1.)\n", "\n", " traits_view = View(\n", " 'name', 'max_storage', 'max_release', 'head', 'efficiency',\n", " title = 'Reservoir',\n", " resizable = True,\n", " )\n", "\n", " def energy_production(self, release):\n", " ''' Returns the energy production [Wh] for the given release [m3/s]\n", " '''\n", " power = 1000 * 9.81 * self.head * release * self.efficiency \n", " return power * 3600\n", "\n", "\n", "if __name__ == '__main__':\n", " reservoir = Reservoir(\n", " name = 'Project A',\n", " max_storage = 30,\n", " max_release = 100.0,\n", " head = 60,\n", " efficiency = 0.8\n", " )\n", "\n", " reservoir.configure_traits()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "![](http://www.scipy-lectures.org/_images/reservoir_view.png)\n", "\n", "### 3.4.3.5 推迟\n", "\n", "可以将trait定义和它的值推送给另一个对象是Traits的有用的功能。" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from traits.api import HasTraits, Instance, DelegatesTo, Float, Range\n", "\n", "from reservoir import Reservoir\n", "\n", "class ReservoirState(HasTraits):\n", " \"\"\"Keeps track of the reservoir state given the initial storage.\n", " \"\"\"\n", " reservoir = Instance(Reservoir, ())\n", " min_storage = Float\n", " max_storage = DelegatesTo('reservoir')\n", " min_release = Float\n", " max_release = DelegatesTo('reservoir')\n", "\n", " # state attributes\n", " storage = Range(low='min_storage', high='max_storage')\n", "\n", " # control attributes\n", " inflows = Float(desc='Inflows [hm3]')\n", " release = Range(low='min_release', high='max_release')\n", " spillage = Float(desc='Spillage [hm3]')\n", "\n", " def print_state(self):\n", " print 'Storage\\tRelease\\tInflows\\tSpillage'\n", " str_format = '\\t'.join(['{:7.2f}'for i in range(4)])\n", " print str_format.format(self.storage, self.release, self.inflows,\n", " self.spillage)\n", " print '-' * 79\n", "\n", "\n", "if __name__ == '__main__':\n", " projectA = Reservoir(\n", " name = 'Project A',\n", " max_storage = 30,\n", " max_release = 100.0,\n", " hydraulic_head = 60,\n", " efficiency = 0.8\n", " )\n", "\n", " state = ReservoirState(reservoir=projectA, storage=10)\n", " state.release = 90\n", " state.inflows = 0\n", " state.print_state()\n", "\n", " print 'How do we update the current storage ?'" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "特殊的trait允许用魔法\\_xxxx\\_fired方法管理事件和触发器函数:" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from traits.api import HasTraits, Instance, DelegatesTo, Float, Range, Event\n", "\n", "from reservoir import Reservoir\n", "\n", "class ReservoirState(HasTraits):\n", " \"\"\"Keeps track of the reservoir state given the initial storage.\n", "\n", " For the simplicity of the example, the release is considered in\n", " hm3/timestep and not in m3/s.\n", " \"\"\"\n", " reservoir = Instance(Reservoir, ())\n", " min_storage = Float\n", " max_storage = DelegatesTo('reservoir')\n", " min_release = Float\n", " max_release = DelegatesTo('reservoir')\n", "\n", " # state attributes\n", " storage = Range(low='min_storage', high='max_storage')\n", "\n", " # control attributes\n", " inflows = Float(desc='Inflows [hm3]')\n", " release = Range(low='min_release', high='max_release')\n", " spillage = Float(desc='Spillage [hm3]')\n", "\n", " update_storage = Event(desc='Updates the storage to the next time step')\n", "\n", " def _update_storage_fired(self):\n", " # update storage state\n", " new_storage = self.storage - self.release + self.inflows\n", " self.storage = min(new_storage, self.max_storage)\n", " overflow = new_storage - self.max_storage\n", " self.spillage = max(overflow, 0)\n", "\n", " def print_state(self):\n", " print 'Storage\\tRelease\\tInflows\\tSpillage'\n", " str_format = '\\t'.join(['{:7.2f}'for i in range(4)])\n", " print str_format.format(self.storage, self.release, self.inflows,\n", " self.spillage)\n", " print '-' * 79\n", "\n", "\n", "if __name__ == '__main__':\n", " projectA = Reservoir(\n", " name = 'Project A',\n", " max_storage = 30,\n", " max_release = 5.0,\n", " hydraulic_head = 60,\n", " efficiency = 0.8\n", " )\n", "\n", " state = ReservoirState(reservoir=projectA, storage=15)\n", " state.release = 5\n", " state.inflows = 0\n", "\n", " # release the maximum amount of water during 3 time steps\n", " state.update_storage = True\n", " state.print_state()\n", " state.update_storage = True\n", " state.print_state()\n", " state.update_storage = True\n", " state.print_state()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "对象间的依赖可以自动使用trait**Property**完成。**depends_on**属性表示property其他traits的依赖性。当其他traits改变了,property是无效的。此外，Traits为属性使用魔法函数的名字:\n", "- \\_get\\_XXX 来获得XXX属性的trait\n", "- \\_set\\_XXX 来设置XXX属性的trait" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from traits.api import HasTraits, Instance, DelegatesTo, Float, Range\n", "from traits.api import Property\n", "\n", "from reservoir import Reservoir\n", "\n", "class ReservoirState(HasTraits):\n", " \"\"\"Keeps track of the reservoir state given the initial storage.\n", "\n", " For the simplicity of the example, the release is considered in\n", " hm3/timestep and not in m3/s.\n", " \"\"\"\n", " reservoir = Instance(Reservoir, ())\n", " max_storage = DelegatesTo('reservoir')\n", " min_release = Float\n", " max_release = DelegatesTo('reservoir')\n", "\n", " # state attributes\n", " storage = Property(depends_on='inflows, release')\n", "\n", " # control attributes\n", " inflows = Float(desc='Inflows [hm3]')\n", " release = Range(low='min_release', high='max_release')\n", " spillage = Property(\n", " desc='Spillage [hm3]', depends_on=['storage', 'inflows', 'release']\n", " )\n", "\n", " ### Private traits.\n", " _storage = Float\n", "\n", " ### Traits property implementation.\n", " def _get_storage(self):\n", " new_storage = self._storage - self.release + self.inflows\n", " return min(new_storage, self.max_storage)\n", "\n", " def _set_storage(self, storage_value):\n", " self._storage = storage_value\n", "\n", " def _get_spillage(self):\n", " new_storage = self._storage - self.release + self.inflows\n", " overflow = new_storage - self.max_storage\n", " return max(overflow, 0)\n", "\n", " def print_state(self):\n", " print 'Storage\\tRelease\\tInflows\\tSpillage'\n", " str_format = '\\t'.join(['{:7.2f}'for i in range(4)])\n", " print str_format.format(self.storage, self.release, self.inflows,\n", " self.spillage)\n", " print '-' * 79\n", "\n", "if __name__ == '__main__':\n", " projectA = Reservoir(\n", " name = 'Project A',\n", " max_storage = 30,\n", " max_release = 5,\n", " hydraulic_head = 60,\n", " efficiency = 0.8\n", " )\n", "\n", " state = ReservoirState(reservoir=projectA, storage=25)\n", " state.release = 4\n", " state.inflows = 0\n", "\n", " state.print_state()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---\n", "**注意** 缓存属性\n", "当访问一个输入没有改变的属性时，大量计算或长时间运行的计算会是个问题。@cached_property修饰器可以用来缓存这个值，并且只有在失效时才会重新计算一次他们。\n", "\n", "---\n", "让我们用ReservoirState的例子来扩展TraitsUI介绍:" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from traits.api import HasTraits, Instance, DelegatesTo, Float, Range, Property\n", "from traitsui.api import View, Item, Group, VGroup\n", "\n", "from reservoir import Reservoir\n", "\n", "class ReservoirState(HasTraits):\n", " \"\"\"Keeps track of the reservoir state given the initial storage.\n", "\n", " For the simplicity of the example, the release is considered in\n", " hm3/timestep and not in m3/s.\n", " \"\"\"\n", " reservoir = Instance(Reservoir, ())\n", " name = DelegatesTo('reservoir')\n", " max_storage = DelegatesTo('reservoir')\n", " max_release = DelegatesTo('reservoir')\n", " min_release = Float\n", "\n", " # state attributes\n", " storage = Property(depends_on='inflows, release')\n", "\n", " # control attributes\n", " inflows = Float(desc='Inflows [hm3]')\n", " release = Range(low='min_release', high='max_release')\n", " spillage = Property(\n", " desc='Spillage [hm3]', depends_on=['storage', 'inflows', 'release']\n", " )\n", "\n", " ### Traits view\n", " traits_view = View(\n", " Group(\n", " VGroup(Item('name'), Item('storage'), Item('spillage'),\n", " label = 'State', style = 'readonly'\n", " ),\n", " VGroup(Item('inflows'), Item('release'), label='Control'),\n", " )\n", " )\n", "\n", " ### Private traits.\n", " _storage = Float\n", "\n", " ### Traits property implementation.\n", " def _get_storage(self):\n", " new_storage = self._storage - self.release + self.inflows\n", " return min(new_storage, self.max_storage)\n", "\n", " def _set_storage(self, storage_value):\n", " self._storage = storage_value\n", "\n", " def _get_spillage(self):\n", " new_storage = self._storage - self.release + self.inflows\n", " overflow = new_storage - self.max_storage\n", " return max(overflow, 0)\n", "\n", " def print_state(self):\n", " print 'Storage\\tRelease\\tInflows\\tSpillage'\n", " str_format = '\\t'.join(['{:7.2f}'for i in range(4)])\n", " print str_format.format(self.storage, self.release, self.inflows,\n", " self.spillage)\n", " print '-' * 79\n", "\n", "if __name__ == '__main__':\n", " projectA = Reservoir(\n", " name = 'Project A',\n", " max_storage = 30,\n", " max_release = 5,\n", " hydraulic_head = 60,\n", " efficiency = 0.8\n", " )\n", "\n", " state = ReservoirState(reservoir=projectA, storage=25)\n", " state.release = 4\n", " state.inflows = 0\n", "\n", " state.print_state()\n", " state.configure_traits()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "![](http://www.scipy-lectures.org/_images/reservoir_state_view.png)\n", "\n", "Some use cases need the delegation mechanism to be broken by the user when setting the value of the trait. The PrototypeFrom trait implements this behaviour." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "TraitsUI simplifies the way user interfaces are created. Every trait on a HasTraits class has a default editor that will manage the way the trait is rendered to the screen (e.g. the Range trait is displayed as a slider, etc.).\n", "In the very same vein as the Traits declarative way of creating classes, TraitsUI provides a declarative interface to build user interfaces code:" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.11" } }, "nbformat": 4, "nbformat_minor": 0 }