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Merge pull request #952 from janezd/svm-layout
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Improve layout of SVM widgets
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@BlazZupan
BlazZupan committed Dec 27, 2015
2 parents 4a2a85c + 8c3707e commit 26b9fb4
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Showing 2 changed files with 175 additions and 226 deletions.
244 changes: 139 additions & 105 deletions Orange/widgets/classify/owsvmclassification.py
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Original file line number Diff line number Diff line change
@@ -1,8 +1,7 @@
# -*- coding: utf-8 -*-
import numpy as np
from collections import OrderedDict

from PyQt4 import QtCore, QtGui
from PyQt4 import QtGui
from PyQt4.QtCore import Qt

from Orange.data import Table
Expand All @@ -12,7 +11,112 @@
from Orange.widgets.utils.sql import check_sql_input


class OWSVMClassification(OWProvidesLearner, widget.OWWidget):
class SVMBaseMixin(OWProvidesLearner):
#: Kernel types
Linear, Poly, RBF, Sigmoid = 0, 1, 2, 3
#: Selected kernel type
kernel_type = settings.Setting(RBF)
#: kernel degree
degree = settings.Setting(3)
#: gamma
gamma = settings.Setting(1.0)
#: coef0 (adative constant)
coef0 = settings.Setting(0.0)

#: numerical tolerance
tol = settings.Setting(0.001)

want_main_area = False
resizing_enabled = False

kernels = (("Linear", "x鈰厃"),
("Polynomial", "(g x鈰厃 + c)<sup>d</sup>"),
("RBF", "exp(-g|x-y|虏)"),
("Sigmoid", "tanh(g x鈰厃 + c)"))

def _add_kernel_box(self):
# Initialize with the widest label to measure max width
self.kernel_eq = self.kernels[-1][1]

self.kernel_box = box = gui.widgetBox(
self.controlArea, "Kernel", orientation="horizontal")

buttonbox = gui.radioButtonsInBox(
box, self, "kernel_type", btnLabels=[k[0] for k in self.kernels],
callback=self._on_kernel_changed, addSpace=20)
buttonbox.layout().setSpacing(10)
gui.rubber(buttonbox)

parambox = gui.widgetBox(box)
gui.label(parambox, self, "Kernel: %(kernel_eq)s")
common = dict(orientation="horizontal",
alignment=Qt.AlignRight, controlWidth=80)
spbox = gui.widgetBox(parambox, orientation="horizontal")
gui.rubber(spbox)
inbox = gui.widgetBox(spbox)
gamma = gui.doubleSpin(
inbox, self, "gamma", 0.0, 10.0, 0.01, label=" g: ", **common)
coef0 = gui.doubleSpin(
inbox, self, "coef0", 0.0, 10.0, 0.01, label=" c: ", **common)
degree = gui.doubleSpin(
inbox, self, "degree", 0.0, 10.0, 0.5, label=" d: ", **common)
self._kernel_params = [gamma, coef0, degree]
gui.rubber(parambox)

# This is the maximal height (all double spins are visible)
# and the maximal width (the label is initialized to the widest one)
box.layout().activate()
box.setFixedHeight(box.sizeHint().height())
box.setMinimumWidth(box.sizeHint().width())

def _add_optimization_box(self):
self.optimization_box = gui.widgetBox(
self.controlArea, "Optimization parameters")

gui.doubleSpin(
self.optimization_box, self, "tol", 1e-7, 1.0, 5e-7,
label="Numerical Tolerance",
decimals=4, alignment=Qt.AlignRight, controlWidth=80
)

def _setup_layout(self):
gui.lineEdit(self.controlArea, self, "learner_name", box="Name")

self._add_type_box()
self._add_kernel_box()
self._add_optimization_box()

box = gui.widgetBox(self.controlArea, True, orientation="horizontal")
box.layout().addWidget(self.report_button)
gui.separator(box, 20)
gui.button(box, self, "&Apply", callback=self.apply, default=True)

def _on_kernel_changed(self):
enabled = [[False, False, False], # linear
[True, True, True], # poly
[True, False, False], # rbf
[True, True, False]] # sigmoid

self.kernel_eq = self.kernels[self.kernel_type][1]
mask = enabled[self.kernel_type]
for spin, enabled in zip(self._kernel_params, mask):
[spin.box.hide, spin.box.show][enabled]()

def _report_kernel_parameters(self, items):
if self.kernel_type == 0:
items["Kernel"] = "Linear"
elif self.kernel_type == 1:
items["Kernel"] = \
"Polynomial, ({g:.4} x鈰厃 + {c:.4})<sup>{d}</sup>".format(
g=self.gamma, c=self.coef0, d=self.degree)
elif self.kernel_type == 2:
items["Kernel"] = "RBF, exp(-{:.4}|x-y|虏)".format(self.gamma)
else:
items["Kernel"] = "Sigmoid, tanh({g:.4} x鈰厃 + {c:.4})".format(
g=self.gamma, c=self.coef0)


class OWSVMClassification(SVMBaseMixin, widget.OWWidget):
name = "SVM"
description = "Support vector machines classifier with standard " \
"selection of kernels."
Expand All @@ -25,107 +129,56 @@ class OWSVMClassification(OWProvidesLearner, widget.OWWidget):
("Classifier", SVMClassifier),
("Support vectors", Table)]

want_main_area = False
resizing_enabled = False

learner_name = settings.Setting("SVM Learner")

# 0: c_svc, 1: nu_svc
svmtype = settings.Setting(0)
C = settings.Setting(1.0)
nu = settings.Setting(0.5)
# 0: Linear, 1: Poly, 2: RBF, 3: Sigmoid
kernel_type = settings.Setting(0)
degree = settings.Setting(3)
gamma = settings.Setting(0.0)
coef0 = settings.Setting(0.0)
shrinking = settings.Setting(True),
probability = settings.Setting(False)
tol = settings.Setting(0.001)
max_iter = settings.Setting(100)
limit_iter = settings.Setting(True)

def __init__(self):
super().__init__()

self.data = None
self.preprocessors = None

box = gui.widgetBox(self.controlArea, self.tr("Name"))
gui.lineEdit(box, self, "learner_name")

form = QtGui.QGridLayout()
typebox = gui.radioButtonsInBox(
self.controlArea, self, "svmtype", [],
box=self.tr("SVM Type"),
orientation=form,
)

c_svm = gui.appendRadioButton(typebox, "C-SVM", addToLayout=False)
form.addWidget(c_svm, 0, 0, Qt.AlignLeft)
form.addWidget(QtGui.QLabel(self.tr("Cost (C)")), 0, 1, Qt.AlignRight)
c_spin = gui.doubleSpin(
typebox, self, "C", 1e-3, 1000.0, 0.1,
decimals=3, addToLayout=False
)

form.addWidget(c_spin, 0, 2)

nu_svm = gui.appendRadioButton(typebox, "谓-SVM", addToLayout=False)
form.addWidget(nu_svm, 1, 0, Qt.AlignLeft)

form.addWidget(
QtGui.QLabel(self.trUtf8("Complexity bound (\u03bd)")),
1, 1, Qt.AlignRight
)

nu_spin = gui.doubleSpin(
typebox, self, "nu", 0.05, 1.0, 0.05,
decimals=2, addToLayout=False
)
form.addWidget(nu_spin, 1, 2)

box = gui.widgetBox(self.controlArea, self.tr("Kernel"))
buttonbox = gui.radioButtonsInBox(
box, self, "kernel_type",
btnLabels=["Linear, x鈭檡",
"Polynomial, (g x鈭檡 + c)^d",
"RBF, exp(-g|x-y|虏)",
"Sigmoid, tanh(g x鈭檡 + c)"],
callback=self._on_kernel_changed
)
parambox = gui.widgetBox(box, orientation="horizontal")
gamma = gui.doubleSpin(
parambox, self, "gamma", 0.0, 10.0, 0.0001,
label=" g: ", orientation="horizontal",
alignment=Qt.AlignRight
)
coef0 = gui.doubleSpin(
parambox, self, "coef0", 0.0, 10.0, 0.0001,
label=" c: ", orientation="horizontal",
alignment=Qt.AlignRight
)
degree = gui.doubleSpin(
parambox, self, "degree", 0.0, 10.0, 0.5,
label=" d: ", orientation="horizontal",
alignment=Qt.AlignRight
)
self._kernel_params = [gamma, coef0, degree]
box = gui.widgetBox(self.controlArea, "Optimization parameters")
gui.doubleSpin(box, self, "tol", 1e-7, 1.0, 5e-7,
label="Numerical Tolerance")
gui.spin(box, self, "max_iter", 0, 1e6, 100,
label="Iteration Limit", checked="limit_iter")

box = gui.widgetBox(self.controlArea, True, orientation="horizontal")
box.layout().addWidget(self.report_button)
gui.separator(box, 20)
gui.button(box, self, "&Apply", callback=self.apply, default=True)

self._setup_layout()
self._on_kernel_changed()

self.apply()

def _add_type_box(self):
form = QtGui.QGridLayout()
self.type_box = box = gui.radioButtonsInBox(
self.controlArea, self, "svmtype", [], box="SVM Type",
orientation=form)

form.addWidget(gui.appendRadioButton(box, "C-SVM", addToLayout=False),
0, 0, Qt.AlignLeft)
form.addWidget(QtGui.QLabel("Cost (C)"),
0, 1, Qt.AlignRight)
form.addWidget(gui.doubleSpin(box, self, "C", 1e-3, 1000.0, 0.1,
decimals=3, alignment=Qt.AlignRight,
controlWidth=80, addToLayout=False),
0, 2)

form.addWidget(gui.appendRadioButton(box, "谓-SVM", addToLayout=False),
1, 0, Qt.AlignLeft)
form.addWidget(QtGui.QLabel(self.trUtf8("Complexity (\u03bd)")),
1, 1, Qt.AlignRight)
form.addWidget(gui.doubleSpin(box, self, "nu", 0.05, 1.0, 0.05,
decimals=2, alignment=Qt.AlignRight,
controlWidth=80, addToLayout=False),
1, 2)

def _add_optimization_box(self):
super()._add_optimization_box()
gui.spin(self.optimization_box, self, "max_iter", 0, 1e6, 100,
label="Iteration Limit", checked="limit_iter",
alignment=Qt.AlignRight, controlWidth=80)

@check_sql_input
def set_data(self, data):
"""Set the input train data set."""
Expand Down Expand Up @@ -167,16 +220,6 @@ def apply(self):
self.send("Classifier", classifier)
self.send("Support vectors", sv)

def _on_kernel_changed(self):
enabled = [[False, False, False], # linear
[True, True, True], # poly
[True, False, False], # rbf
[True, True, False]] # sigmoid

mask = enabled[self.kernel_type]
for spin, enabled in zip(self._kernel_params, mask):
spin.setEnabled(enabled)

def send_report(self):
self.report_items((("Name", self.learner_name),))

Expand All @@ -185,16 +228,7 @@ def send_report(self):
items["SVM type"] = "C-SVM, C={}".format(self.C)
else:
items["SVM type"] = "谓-SVM, 谓={}".format(self.nu)
if self.kernel_type == 0:
items["Kernel"] = "Linear"
elif self.kernel_type == 1:
items["Kernel"] = "Polynomial, ({g:.4} x鈭檡 + {c:.4})^{d}".format(
g=self.gamma, c=self.coef0, d=self.degree)
elif self.kernel_type == 2:
items["Kernel"] = "RBF, exp(-{:.4}|x-y|虏)".format(self.gamma)
else:
items["Kernel"] = "Sigmoid, tanh({g:.4} x鈭檡 + {c:.4})".format(
g=self.gamma, c=self.coef0)
self._report_kernel_parameters(items)
items["Numerical tolerance"] = "{:.6}".format(self.tol)
items["Iteration limt"] = \
self.max_iter if self.limit_iter else "unlimited"
Expand Down

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