[FIX] Change Variable Icons: Discrete -> Categorical, Continuous -> Numeric

Orange/classification/majority.py

@@ -22,7 +22,7 @@ class value is selected randomly. In order to produce consistent results on
     def fit_storage(self, dat):
         if not dat.domain.has_discrete_class:
             raise ValueError("classification.MajorityLearner expects a domain "
-                             "with a (single) discrete variable")
+                             "with a (single) categorical variable")
         dist = distribution.get_distribution(dat, dat.domain.class_var)
         N = dist.sum()
         if N > 0:

Orange/data/variable.py

@@ -452,7 +452,7 @@ class ContinuousVariable(Variable):
     set to 0 to prevent changes by `to_val`.
     """
 
-    TYPE_HEADERS = ('continuous', 'c')
+    TYPE_HEADERS = ('continuous', 'c', 'numeric', 'n')
 
     def __init__(self, name="", number_of_decimals=None, compute_value=None):
         """
@@ -549,7 +549,7 @@ class DiscreteVariable(Variable):
         for regression.
     """
 
-    TYPE_HEADERS = ('discrete', 'd')
+    TYPE_HEADERS = ('discrete', 'd', 'categorical')
 
     _all_vars = collections.defaultdict(list)
     presorted_values = []

Orange/widgets/data/owcontinuize.py

@@ -20,8 +20,8 @@
 
 class OWContinuize(widget.OWWidget):
     name = "Continuize"
-    description = ("Transform discrete attributes into continuous and, " +
-                   "optionally, normalize the continuous values.")
+    description = ("Transform categorical attributes into numeric and, " +
+                   "optionally, normalize numeric values.")
     icon = "icons/Continuize.svg"
     category = "Data"
     keywords = ["data", "continuize"]
@@ -50,7 +50,7 @@ class Outputs:
         ("Most frequent value as base", Continuize.FrequentAsBase),
         ("One attribute per value", Continuize.Indicators),
         ("Ignore multinomial attributes", Continuize.RemoveMultinomial),
-        ("Remove all discrete attributes", Continuize.Remove),
+        ("Remove categorical attributes", Continuize.Remove),
         ("Treat as ordinal", Continuize.AsOrdinal),
         ("Divide by number of values", Continuize.AsNormalizedOrdinal))
 
@@ -71,19 +71,19 @@ class Outputs:
     def __init__(self):
         super().__init__()
 
-        box = gui.vBox(self.controlArea, "Multinomial Attributes")
+        box = gui.vBox(self.controlArea, "Categorical Features")
         gui.radioButtonsInBox(
             box, self, "multinomial_treatment",
             btnLabels=[x[0] for x in self.multinomial_treats],
             callback=self.settings_changed)
 
-        box = gui.vBox(self.controlArea, "Continuous Attributes")
+        box = gui.vBox(self.controlArea, "Numeric Features")
         gui.radioButtonsInBox(
             box, self, "continuous_treatment",
             btnLabels=[x[0] for x in self.continuous_treats],
             callback=self.settings_changed)
 
-        box = gui.vBox(self.controlArea, "Discrete Class Attribute")
+        box = gui.vBox(self.controlArea, "Categorical Outcomes")
         gui.radioButtonsInBox(
             box, self, "class_treatment",
             btnLabels=[t[0] for t in self.class_treats],
@@ -141,9 +141,9 @@ def commit(self):
     def send_report(self):
         self.report_items(
             "Settings",
-            [("Multinominal attributes",
+            [("Categorical features",
               self.multinomial_treats[self.multinomial_treatment][0]),
-             ("Continuous attributes",
+             ("Numeric features",
               self.continuous_treats[self.continuous_treatment][0]),
              ("Class", self.class_treats[self.class_treatment][0]),
              ("Value range", self.value_ranges[self.zero_based])])

Orange/widgets/data/owdatainfo.py

@@ -131,14 +131,14 @@ def update_size():
             disc_class = count(domain.class_vars, DiscreteVariable)
             cont_class = count(domain.class_vars, ContinuousVariable)
             if not cont_class:
-                self.targets = "Multitarget data,\n%i discrete targets" % \
+                self.targets = "Multitarget data,\n%i categorical targets" % \
                                n_or_none(disc_class)
             elif not disc_class:
                 self.targets = "Multitarget data,\n%i numeric targets" % \
                                n_or_none(cont_class)
             else:
                 self.targets = "<p>Multi target data</p>\n" + pack_table(
-                    (("Discrete", disc_class), ("Numeric", cont_class)))
+                    (("Categorical", disc_class), ("Numeric", cont_class)))
 
         self.data_desc = dd = OrderedDict()
 
@@ -158,23 +158,23 @@ def join_if(items):
             return ", ".join(s.format(n) for s, n in items if n)
 
         dd["Features"] = len(domain.attributes) and join_if((
-            ("{} discrete", disc_features),
+            ("{} categorical", disc_features),
             ("{} numeric", cont_features)
         ))
         if domain.class_var:
             name = domain.class_var.name
             if domain.class_var.is_discrete:
-                dd["Target"] = "discrete outcome '{}'".format(name)
+                dd["Target"] = "categorical outcome '{}'".format(name)
             else:
                 dd["Target"] = "numeric target '{}'".format(name)
         elif domain.class_vars:
             tt = ""
             if disc_class:
-                tt += report.plural("{number} discrete outcome{s}", disc_class)
+                tt += report.plural("{number} categorical outcome{s}", disc_class)
             if cont_class:
                 tt += report.plural("{number} numeric target{s}", cont_class)
         dd["Meta attributes"] = len(domain.metas) > 0 and join_if((
-            ("{} discrete", disc_metas),
+            ("{} categorical", disc_metas),
             ("{} numeric", cont_metas),
             ("{} textual", str_metas)
         ))

Orange/widgets/data/owfeatureconstructor.py

@@ -341,7 +341,7 @@ class Outputs:
     ]
 
     class Error(OWWidget.Error):
-        more_values_needed = Msg("Discrete feature {} needs more values.")
+        more_values_needed = Msg("Categorical feature {} needs more values.")
         invalid_expressions = Msg("Invalid expressions: {}.")
 
     def __init__(self):
@@ -618,7 +618,7 @@ def send_report(self):
         items = OrderedDict()
         for feature in self.featuremodel:
             if isinstance(feature, DiscreteDescriptor):
-                items[feature.name] = "{} (discrete with values {}{})".format(
+                items[feature.name] = "{} (categorical with values {}{})".format(
                     feature.expression, feature.values,
                     "; ordered" * feature.ordered)
             elif isinstance(feature, ContinuousDescriptor):

Orange/widgets/data/owfile.py

@@ -371,7 +371,7 @@ def _describe(self, table):
         if domain.has_continuous_class:
             text += "<br/>Regression; numerical class."
         elif domain.has_discrete_class:
-            text += "<br/>Classification; discrete class with {} values.".\
+            text += "<br/>Classification; categorical class with {} values.".\
                 format(len(domain.class_var.values))
         elif table.domain.class_vars:
             text += "<br/>Multi-target; {} target variables.".format(

Orange/widgets/data/owpreprocess.py

@@ -67,7 +67,7 @@ class DiscretizeEditor(BaseEditor):
         NoDisc: "None",
         EqualWidth: "Equal width discretization",
         EqualFreq: "Equal frequency discretization",
-        Drop: "Remove continuous attributes",
+        Drop: "Remove numeric features",
         EntropyMDL: "Entropy-MDL discretization"
     }
 
@@ -194,9 +194,9 @@ class ContinuizeEditor(BaseEditor):
 
     Continuizers = OrderedDict([
         (Continuize.FrequentAsBase, "Most frequent is base"),
-        (Continuize.Indicators, "One attribute per value"),
-        (Continuize.RemoveMultinomial, "Remove multinomial attributes"),
-        (Continuize.Remove, "Remove all discrete attributes"),
+        (Continuize.Indicators, "One feature per value"),
+        (Continuize.RemoveMultinomial, "Remove non-binary features"),
+        (Continuize.Remove, "Remove categorical features"),
         (Continuize.AsOrdinal, "Treat as ordinal"),
         (Continuize.AsNormalizedOrdinal, "Divide by number of values")
     ])

Orange/widgets/data/owpurgedomain.py

@@ -35,11 +35,11 @@ class Outputs:
     resizing_enabled = False
     buttons_area_orientation = Qt.Vertical
 
-    feature_options = (('sortValues', 'Sort discrete feature values'),
+    feature_options = (('sortValues', 'Sort categorical feature values'),
                        ('removeValues', 'Remove unused feature values'),
                        ('removeAttributes', 'Remove constant features'))
 
-    class_options = (('sortClasses', 'Sort discrete class variable values'),
+    class_options = (('sortClasses', 'Sort categorical class values'),
                      ('removeClasses', 'Remove unused class variable values'),
                      ('removeClassAttribute', 'Remove constant class variables'))
 

Orange/widgets/data/owsql.py

@@ -159,7 +159,7 @@ def __init__(self):
         box.layout().addWidget(self.custom_sql)
 
         gui.checkBox(box, self, "guess_values",
-                     "Auto-discover discrete variables",
+                     "Auto-discover categorical variables",
                      callback=self.open_table)
 
         gui.checkBox(box, self, "download",

Orange/widgets/data/owtable.py

@@ -413,7 +413,7 @@ def __init__(self):
             callback=self._on_show_variable_labels_changed)
 
         gui.checkBox(box, self, "show_distributions",
-                     'Visualize continuous values',
+                     'Visualize numeric values',
                      callback=self._on_distribution_color_changed)
         gui.checkBox(box, self, "color_by_class", 'Color by instance classes',
                      callback=self._on_distribution_color_changed)

Orange/widgets/gui.py

@@ -1024,9 +1024,9 @@ class __AttributeIconDict(dict):
     def __getitem__(self, key):
         if not self:
             for tpe, char, col in ((vartype(ContinuousVariable()),
-                                    "C", (202, 0, 32)),
+                                    "N", (202, 0, 32)),
                                    (vartype(DiscreteVariable()),
-                                    "D", (26, 150, 65)),
+                                    "C", (26, 150, 65)),
                                    (vartype(StringVariable()),
                                     "S", (0, 0, 0)),
                                    (vartype(TimeVariable()),

Orange/widgets/unsupervised/owdistances.py

@@ -46,15 +46,15 @@ class Outputs:
     buttons_area_orientation = Qt.Vertical
 
     class Error(OWWidget.Error):
-        no_continuous_features = Msg("No continuous features")
+        no_continuous_features = Msg("No numeric features")
         dense_metric_sparse_data = Msg("Selected metric does not support sparse data")
         empty_data = Msg("Empty data set")
         mahalanobis_error = Msg("{}")
         distances_memory_error = Msg("Not enough memory.")
         distances_value_error = Msg("Error occurred while calculating distances\n{}")
 
     class Warning(OWWidget.Warning):
-        ignoring_discrete = Msg("Ignoring discrete features")
+        ignoring_discrete = Msg("Ignoring categorical features")
         imputing_data = Msg("Imputing missing values")
 
     def __init__(self):

Orange/widgets/unsupervised/owmds.py

@@ -1191,7 +1191,7 @@ def color_data(table, var=None, mask=None, plotstyle=None):
                 color_data = plotutils.continuous_colors(
                     col, palette=plotstyle.continuous_palette)
         else:
-            raise TypeError("Discrete/Continuous variable or None expected.")
+            raise TypeError("Categorical/Numeric variable or None expected.")
 
         return color_data
 

Orange/widgets/utils/domaineditor.py

@@ -35,7 +35,7 @@ class VarTableModel(QAbstractTableModel):
     DISCRETE_VALUE_DISPLAY_LIMIT = 20
 
     places = "feature", "target", "meta", "skip"
-    typenames = "nominal", "numeric", "string", "datetime"
+    typenames = "categorical", "numeric", "string", "datetime"
     vartypes = DiscreteVariable, ContinuousVariable, StringVariable, TimeVariable
     name2type = dict(zip(typenames, vartypes))
     type2name = dict(zip(vartypes, typenames))

Orange/widgets/utils/itemmodels.py

@@ -631,6 +631,8 @@ def data(self, index, role=Qt.DisplayRole):
     def variable_tooltip(self, var):
         if var.is_discrete:
             return self.discrete_variable_tooltip(var)
+        elif var.is_time:
+            return self.time_variable_toltip(var)
         elif var.is_continuous:
             return self.continuous_variable_toltip(var)
         elif var.is_string:
@@ -647,14 +649,19 @@ def variable_labels_tooltip(self, var):
         return text
 
     def discrete_variable_tooltip(self, var):
-        text = "<b>%s</b><br/>Discrete with %i values: " %\
+        text = "<b>%s</b><br/>Categorical with %i values: " %\
                (safe_text(var.name), len(var.values))
         text += ", ".join("%r" % safe_text(v) for v in var.values)
         text += self.variable_labels_tooltip(var)
         return text
 
+    def time_variable_toltip(self, var):
+        text = "<b>%s</b><br/>Time" % safe_text(var.name)
+        text += self.variable_labels_tooltip(var)
+        return text
+
     def continuous_variable_toltip(self, var):
-        text = "<b>%s</b><br/>Continuous" % safe_text(var.name)
+        text = "<b>%s</b><br/>Numeric" % safe_text(var.name)
         text += self.variable_labels_tooltip(var)
         return text
 

Orange/widgets/visualize/owdistributions.py

@@ -144,9 +144,9 @@ def __init__(self):
 
         self.cb_disc_cont = gui.checkBox(
             gui.indentedBox(box, sep=4),
-            self, "disc_cont", "Bin continuous variables",
+            self, "disc_cont", "Bin numeric variables",
             callback=self._on_groupvar_idx_changed,
-            tooltip="Show continuous variables as discrete.")
+            tooltip="Show numeric variables as categorical.")
 
         box = gui.vBox(self.controlArea, "Group by")
         self.icons = gui.attributeIconDict
@@ -260,11 +260,11 @@ def clear(self):
 
     def _setup_smoothing(self):
         if not self.disc_cont and self.var and self.var.is_continuous:
-            self.cb_disc_cont.setText("Bin continuous variables")
+            self.cb_disc_cont.setText("Bin numeric variables")
             self.l_smoothing_l.setText("Smooth")
             self.l_smoothing_r.setText("Precise")
         else:
-            self.cb_disc_cont.setText("Bin continuous variables into {} bins".
+            self.cb_disc_cont.setText("Bin numeric variables into {} bins".
                                       format(self.bins[self.smoothing_index]))
             self.l_smoothing_l.setText(" " + str(self.bins[0]))
             self.l_smoothing_r.setText(" " + str(self.bins[-1]))

Orange/widgets/visualize/owheatmap.py

@@ -430,13 +430,13 @@ class Outputs:
 
     class Information(widget.OWWidget.Information):
         sampled = Msg("Data has been sampled")
-        discrete_ignored = Msg("{} discrete column{} ignored")
+        discrete_ignored = Msg("{} categorical feature{} ignored")
         row_clust = Msg("{}")
         col_clust = Msg("{}")
         sparse_densified = Msg("Showing this data may require a lot of memory")
 
     class Error(widget.OWWidget.Error):
-        no_continuous = Msg("No continuous feature columns")
+        no_continuous = Msg("No numeric features")
         not_enough_features = Msg("Not enough features for column clustering")
         not_enough_instances = Msg("Not enough instances for clustering")
         not_enough_instances_k_means = Msg(

Orange/widgets/visualize/owlinearprojection.py

@@ -584,7 +584,7 @@ def _initialize(self, data):
         # Initialize the GUI controls from data's domain.
         cont_vars = [var for var in data.domain.variables
                      if var.is_continuous]
-        self.warning("Plotting requires continuous features.",
+        self.warning("Plotting requires numeric features.",
                      shown=not len(cont_vars))
         self.varmodel_selected[:] = cont_vars[:3]
         self.varmodel_other[:] = cont_vars[3:]

Orange/widgets/visualize/owmosaic.py

@@ -303,7 +303,7 @@ class Warning(OWWidget.Warning):
         incompatible_subset = Msg("Data subset is incompatible with Data")
         no_valid_data = Msg("No valid data")
         no_cont_selection_sql = \
-            Msg("Selection of continuous variables on SQL is not supported")
+            Msg("Selection of numeric features on SQL is not supported")
 
     def __init__(self):
         super().__init__()

Orange/widgets/visualize/ownomogram.py

@@ -650,7 +650,7 @@ def __init__(self):
             orientation=Qt.Horizontal, callback=self.update_scene)
 
         self.cont_feature_dim_combo = gui.comboBox(
-            box, self, "cont_feature_dim_index", label="Continuous features: ",
+            box, self, "cont_feature_dim_index", label="Numeric features: ",
             items=["1D projection", "2D curve"], orientation=Qt.Horizontal,
             callback=self.update_scene)
 

Orange/widgets/visualize/owparallelcoordinates.py

@@ -93,7 +93,8 @@ def add_annotation_settings(self, parent):
                      items=["No statistics", "Means, deviations", "Median, quartiles"], callback=self.update_graph,
                      sendSelectedValue=False, valueType=int)
         gui.checkBox(box, self, 'graph.show_distributions', 'Show distributions', callback=self.update_graph,
-                     tooltip="Show bars with distribution of class values (only for discrete attributes)")
+                     tooltip="Show bars with distribution of class values "
+                             "(only for categorical attributes)")
 
     def add_group_settings(self, parent):
         box = gui.vBox(parent, "Groups")

Orange/widgets/visualize/owscatterplot.py

@@ -188,7 +188,7 @@ def __init__(self):
             "None" if x == 0 else ("%.1f %%" if x < 1 else "%d %%") % x)
         gui.checkBox(
             gui.indentedBox(box), self, 'graph.jitter_continuous',
-            'Jitter continuous values', callback=self.reset_graph_data)
+            'Jitter numeric values', callback=self.reset_graph_data)
 
         self.sampling = gui.auto_commit(
             self.controlArea, self, "auto_sample", "Sample", box="Sampling",

Orange/widgets/visualize/owsilhouetteplot.py

@@ -189,7 +189,7 @@ def set_data(self, data):
                 data = None
                 error_msg = "No continuous columns"
             elif ncont < len(data.domain.attributes):
-                warning_msg = "{0} discrete columns will not be used for " \
+                warning_msg = "{0} categorical columns will not be used for " \
                               "distance computation".format(ndiscrete)
 
         self.data = data