Categories
Lucid Builder v4

Lucid Builder Creating subsets of Features and Entities

About subsets

Subsets of items provide a way for users to organise and arrange the features and entities in the key.

A subset is a named collection of features or entities. For example, a key to fungi may have feature sets named Macroscopic FeaturesMicroscopic Features and Chemical Features. A user of the key who wishes to use only macroscopic features (perhaps because the user does not have a microscope or access to chemical analysis facilities) will choose the Macroscopic Features subset, and only macroscopic features will be displayed in Features Available. Similarly, the key may have entity sets named Common Fungi and Rare Fungi. A user of the key may wish to use the Common Fungi subset to remove all rare fungi from the key.

Subsets can also be used in the deployment of the key to create a key that only contains those items found in the subsets selected. That is you can create sub keys from the selection of the feature and entity subsets. See the Key Deployment help topic for more information.

In Lucid Version 2, Subsets were called Sets, and many Lucid2 keys use sets to arrange features into morphological categories. For example, a key to plants may include the sets LeavesFlowersFruits etc. In a Lucid v4 key another way of arranging Features and Entities is provided by the hierarchy of items in the Features and Entities trees. However, feature subsets are still needed in order to reduce the key to one or more subsets of features, especially when using the key in List View and when using Best.

How to create subsets

Subsets are created and managed using the Subsets panel. Once a subset has been created, items are assigned to the subset by “scoring” them for a given subset, equivalent to scoring features and items.

To open the Subsets panel, click the Subsets button subsets icon on the toolbar.

Lucid Builder Feature Subset example
Lucid Builder Feature Subset example
Lucid Builder Entities Subset example
Lucid Builder Entities Subset example

To add a Subset right click within the Subsets panel and select either the Add…Feature subset or Entity subset from the context pop-up menu.

Add Subset context pop-up menu
Add Subset context pop-up menu

How to score subsets

Score subsets by clicking the Score Subset subset scoring icon button on the score toolbar, then selecting a subset in the Subsets panel. If the selected subset is a Features subset, round subset score boxes will appear against features in the Features panel; if the selected subset is an Entities subset, round subset score boxes will appear against entities in the Entities panel. Add an item to a subset by clicking on its score box.

Tip

When scoring subsets in feature or entity trees, holding down the Control key while clicking on a subset score box will cause all children of the scored item to be also included in the subset. If an item is included in the subset its parent (and other ancestors) must be included in the subset also.

Subsets can be added, deleted, moved, renamed and re-scored at any time.

Setting default subsets

Subsets can be set as default features and/or entities when the key is opened in the Lucid Player. To have a subset used by default select the Items tab and select the Default Subset check box.

Note

Subsets panel needs to be visible before the Default Subset check box is visible in the Items tab.

Subsets Set as Default
Subsets – Set as Default
Categories
Lucid Builder v4

Lucid Builder Score Analyser

Analysing a key’s scores

Once a key is partially scored, you may analyse the scoring using the Score Analyser. The Score Analyser provides two main types of analysis:

A Difference analysis is used to identify pairs or groups of Entities that a user of the key will have difficulty separating, because there are few differences in their scoring. Adding more Features that differ between such Entities would improve the key. While the Lucid Builder cannot tell you which Features to add, pointing out which Entities need more Features may help you improve the key.

A Polymorphism analysis identifies taxa that are more or less polymorphic in their scoring. A taxon is polymorphic when it is scored for two or more States of a Feature. Taxa that are highly polymorphic (I.e. frequently scored for two or more States per Feature) will be difficult to remove from Entities Remaining even when the particular set of States chosen does not occur in the Entity – that is, they may be falsely retained. Splitting highly polymorphic taxa into two or more less-polymorphic subtaxa will improve the efficiency of the key.

The Score Analyser is started by choosing the Score Analyser tab.

Lucid Builder Score Analyser tab
Lucid Builder Score Analyser tab

After analysis, choose Differences by Entity or Differences by group to perform a difference analysis, or Polymorphisms to produce a polymorphism analysis.

Difference Analysis

The Score Analyser displays a bar graph showing the number of differences between all pairs of Entities.

Lucid Builder Score Analyser example
Lucid Builder Score Analyser example

On the left of the graph are pairs of Entities that differ by relatively few Features; on the right of the graph are pairs of Entities that differ by many Features.

The slider on the bar graph is used to find those pairs of Entities that differ by less than a nominated number of features. Move the slider to a position on the left tail of the graph, and the middle panel of the Score Analyser will display all pairs of Entities that differ by less than the nominated number of features. Selecting an entity in the middle panel will display the Features that differ.

If Differences by Entity is selected, the middle panel will list Entities in order of each Entity. If Differences by groups is selected, the lower panel will display Entities that form mutually difficult groups.

Use Save to File to save the results of the lowermost panels to a text file.

Polymorphism Analysis

The Score Analyser displays a bar graph showing the distribution of polymorphisms for the Entities in the key. The polymorphism score of an Entity is a percentage of the total number of States scored non-absent for the Entity divided by the total number of States in the key.  

Lucid Builder Score Analyser Polymorphisms example
Lucid Builder Score Analyser Polymorphisms example

The slider on the bar graph is used to find those entities that are highly polymorphic. Move the slider to a position on the right tail of the graph, and the middle panel of the Score Analyser will display all Entities with a polymorphism value greater than the nominated value. Selecting an Entity in the middle panel will display the features that are scored polymorphically, with their scored States.

Use Save button to save the results of the lowermost panels to a text file.

Categories
Lucid Builder v4

Lucid Builder Measurement Units

Lucid Builder Properties Panel Change Measurement Units
Lucid Builder Properties Panel Change Measurement Units

Numeric features that represent a measurement (such as Antenna length) should have a specified measurement unit (e.g. cm).

Measurement units are set using the Measurement Unit dialog. This is accessed by clicking on the Change… button on the Items panel.

To specify an SI measurement unit, select a base unit and (if appropriate) a default prefix from the drop-down boxes. For example, to specify a unit of centimetres (cm), choose m (metres) as the base unit and c (centi) as the default prefix.

The possible base units values are:

  • none
  • m (metre)
  • m2 (square metre)
  • m3 (cubic metre)
  • l (litre)
  • °C (degrees Celsius)
  • ° (degrees planar)
  • other (user specified unit – string)

The possible unit prefixes are:

  • none
  • k (kilo)
  • h (hecto)
  • da (deca)
  • d (deci)
  • c (centi)
  • m (milli)
  • µ (micro)

To specify a non-SI unit (e.g. inches), type the name of the unit into the Base Unit box.

When scoring numeric features, the Numerics dialog box displays the default unit (a concatenation of the prefix and base unit). Clicking on the Units value will allow you to choose alternate units (based on the same base) from a dropdown box. For example, if the default measurement unit is cm, you may enter values for different taxa in cm, mm, dm etc. Lucid will automatically convert all measures to the default unit for storage.

Lucid Builder Numeric Feature Scoring example
Lucid Builder Numeric Feature Scoring example

Note

When using non-SI base units, alternate unit prefixes (e.g. milli-inch, kilo-inch etc) may be chosen in the Numeric Scores dialog. This should not be done, as non-SI units are not automatically converted to the default unit for storage.

No prefixes are available if the base unit chosen is °, °C or (none).

Categories
Lucid Builder v4

Lucid Builder About Lucid scores

Applies to Matrix key projects

Absent score icon Absent

The Lucid Absent score is used to record that a state of a feature does not occur in an entity. This should be a definitive statement: if you are uncertain whether a state does or does not occur, it is safer to use the Uncertain uncertain score icon score.

Absent is, in some ways, the most important score in Lucid. If an entity is scored as Absent for a state and a user of the Lucid Player chooses the state, the entity will be discarded from Entities Remaining into Entities Discarded, and hence will be removed from contention for the identification. A false Absent is a more serious error in a key than a false Present, since it will cause an entity to be falsely removed from Entities Remaining, and hence may preclude a correct identification.

Absent is the default score given to all entities for all states, until another score is given.

For numeric features, Absent is the default score if no numeric record has been entered for the entity. See the topic Scoring numeric features for more details.

common score icon Common

Common is the normal score given in Lucid when a state occurs in an entity. For example, if a species of plant always or usually has blue flowers, the state blue of the feature Flower colour would be scored using the Common score.

Common may be used in concert with other scores. For example, if a species of plant usually has blue flowers but occasionally has red flowers, then the state blue would be scored Common and the state red would be scored Rare.

For numeric features, Common and Rare values are coded by entering ranges of numbers in the Numeric Coding dialog box. See the topic Scoring numeric features  for more details.

rare score icon Rare

Rare is used to record that a state occurs uncommonly or rarely in an entity.

Rare will usually be used in concert with other scores. For example, if a species of plant usually has blue flowers but occasionally has red flowers, then the state blue would be scored Common and the state red would be scored Rare.

Note that Rare should be used only in the case where a state occurs rarely in an entity, not in the case that the entity is rare. If a state always or usually occurs in a rare entity, you should still use the Common score.

In the Lucid Player, Rare is used to rank the list of Entities Remaining. If entity e is scored Rare for state s, then e will be moved down the list of Entities Remaining (List Mode) when the user chooses s (compared with other entities that are scored Common for s). Hence, if Rare is widely used in a key and at the end of an identification several entities remain, entities at the top of the list are more likely to be correct than entities at the end of the list.

For numeric features, Common and Rare values are coded by entering ranges of numbers in the Numeric Coding dialog box. See the topic Scoring numeric features for more details.

uncertain score icon Uncertain

Uncertain is used to record that the key author is uncertain or does not know whether a given state occurs or does not occur in a given entity.

Uncertain will sometimes be applied to all states of a feature and sometimes only to one or a few states of a feature. For example, consider a key to plants which includes a feature referring to the colour of the fruit. It may be that one species in the key is known only from a few specimens and fruits have never been observed. In that case, all the states of the Fruit colour feature would be scored Uncertain. Another species may be poorly known and yet it is clear that the fruits are not white or coloured, but they could be black or dark grey. In that case, white and the coloured states could be scored Absent and dark grey and black both scored Uncertain.

In the Lucid Player in normal identification mode, Uncertain is treated the same as Common. That is, if an entity e is scored Uncertain for state e will remain in Entities Remaining when a user chooses s. This is appropriate behaviour for an identification, as e should not be falsely discarded if a key user has more information about it than was available to the key developer.

The behaviour of the Player can also be changed by un-checking the Retain Uncertains menu option, in which case Uncertain is treated the same as Absent. This would be appropriate if a user of the key is querying the Player to return a list of all entities known to have state s (rather than all entities that may have s).

For numeric features, Uncertain is coded as a special value in the Numeric Coding dialog box. See the topic Scoring numeric features for more details.

common misinterpreted score icon  Present by Misinterpretation, and rare misinterpreted score icon Rarely Present by Misinterpretation

While the Uncertain score in Lucid is used to capture uncertainty by the key developer, the Present by Misinterpretation scores are used to preempt likely uncertainty or mistakes by a key user.

Consider a key to fish with a feature Number of dorsal fins and the states one dorsal fin and two dorsal fins. Some species of fish clearly have a single dorsal fin, while others clearly have two dorsal fins. Angler fish have two dorsal fins, but the first is modified into a fleshy lure that does not look like a normal fin. In this case a user of the key may misinterpret an angler fish as having a single dorsal fin. If angler fish were scored correctly as having two dorsal fins many users would make a mistake at this point. Conversely, scoring angler fish as having a single dorsal fin (to account for the likely mistake) would introduce erroneous coding into the key.

In Lucid the Present by Misinterpretation scores are used to account for likely user mistakes while maintaining the integrity of the data. In the case of angler fish, the state two dorsal fins would be scored Present, and the state one dorsal fin would be scored Present by misinterpretation.

Lucid Builder Present by Misinterpretation score example
Lucid Builder Present by Misinterpretation score example

In the Lucid Player in normal identification mode, Present by Misinterpretation is treated the same as Common. That is, if an entity e is scored Present by Misinterpretation for state s, then e will remain in Entities Remaining when a user chooses s. This is appropriate behaviour for an identification, as it pre-empts e being discarded when a user makes a common and predictable mistake.

The behaviour of the Player can also be changed by un-checking the Allow Misinterpretations menu option, in which case Present by Misinterpretation is treated the same as Absent. This would be appropriate if a user of the key is querying the Player to return a list of all entities that truly have one dorsal fin (rather than all entities that may appear to have one dorsal fin).

The Rarely Present by Misinterpretation score is used to encode a case where it is occasionally the case that a state could be misinterpreted as being present. For example, a species of fish may normally clearly have two dorsal fins, but in occasional specimens one dorsal fin may be reduced to a small spine that could be overlooked. In the Lucid Player with Allow Misinterpretations check-marked, a Rarely Present by Misinterpretation score is treated the same as a Rare score; with Allow Misinterpretations unchecked, Rarely Present by Misinterpretation is treated the same as Absent.

Lucid Builder Present by Misinterpretation with other another score example
Lucid Builder Present by Misinterpretation with other another score example

Note that the Present by Misinterpretation scores are usually used in concert with other scores, as in the case above. Sometimes, however, Present by Misinterpretation or Rarely Present by Misinterpretation may be used alone, especially when a feature is controlled by a dependency. For example, consider a key to plants with the features Petals (with states present and absent) and Petal colour (with states white and blue). A species of plant in the key may lack petals but have white, petal-like bracts around the flower which could be misinterpreted as petals. This species would be coded as Common for the state Petals: absentPresent by misinterpretation for the state Petals: present and Present by misinterpretation for the state Petal colour: white.

For numeric features, the By Misinterpretation score is set as an annotation for a range of numbers in the Numeric Coding dialog box. See the topic Scoring numeric features for more details.

not scoped score icon Not Scoped

The Not Scoped score in Lucid is used to enable coding of features that are useful and applicable only for a subset of the entities in the key. In the Lucid Player, features scored using Not Scoped are initially hidden, and are inserted into the Features Available list only when they become applicable to the identification.

Consider a large key with 1000 Entities. It will be appropriate to score some features for all the entities, using the normal Lucid scores (AbsentCommonRare etc.). But consider a feature that is useful for identification only in a small subgroup of the entities, and which is inapplicable, ambiguous or insufficiently known for the bulk of entities. In Lucid, the entities in the subgroup can be coded for the feature, but all the other entities (not in the subgroup) will be given the Not Scoped score for that feature. In the Lucid Player, the feature will only become available when the list of Entities Remaining includes only entities that are scored for the feature using normal scores.

To explain the Not Scoped score further, consider a key to fishes with the following Entities and Features:

Features

Entities

Body shape in cross-section

          Rounded

          Laterally flattened

          Dorsoventrally flattened

Paired spots along flank

          Adjacent, forming figures of eight

          Separated by a thin line

Barracuda

Bluefin Tuna

Red Gurnard

Sand Mullet

Spotted Weedfish

Crested Weedfish

…etc*

*The key also includes many other species of fishes.

The feature Body shape in cross-section can be scored for all the fish in the key, and it would be good practice to do so. The feature Paired spots along flank, however, is very useful to distinguish the two species of weedfish, which are otherwise difficult to separate, but is difficult to answer unambiguously for most other species of fish (some other species may also have paired spots in various arrangements on the flank, but for these other species the pattern of spots is not a useful feature for identification).

In this key, it may be important to be able to make use of the feature Paired spots along flank to separate the weedfish, but it would be difficult or impossible to score it for all fish. The Not Scoped score would be used in this circumstance. For all species other than the weedfish, both states of Paired spots along the flank are given the score Not Scoped, while for the weedfish the feature is scored using the normal Lucid scores. The figure below shows the coding for two species as it would appear in the Lucid Builder

Lucid Builder Not Scoped scoring example
Lucid Builder Not Scoped scoring example

In the Lucid Player, when the key is started the feature Paired spots along flank is initially hidden. As a user of the key addresses the available features, the list of entities becomes progressively reduced. It may be that, at some point in the identification, only weedfish remain in Entities Remaining. All the weedfish are scored for the feature Paired spots along the flank, so at this point the feature is inserted into Features Available and can be used to help discriminate the species of weedfish.

For multi-state features, the Not Scoped score is automatically assigned to all the states of a feature – it cannot be given to a single state.

Categories
Lucid Builder v4

Lucid Builder Scoring the key

Lucid Builder Score toolbar options
Lucid Builder Score toolbar options.

About Lucid scores

Multi-state features in Lucid may be scored using seven possible scores:

A more in depth explanation of each score type is available. Below outlines a summary of each.

Absent score icon Absent – the state does not occur in the entity.

common score icon Common – the state occurs commonly (or always) in the entity.

rare score iconRare – the state occurs rarely in the entity.

uncertain score icon Uncertain – it is not known whether the state occurs in the entity or not

common misinterpreted score icon Common and Misinterpreted – the state does not occur in the entity, but it could be commonly misinterpreted that it does.

rare misinterpreted score icon Rare and Misinterpreted – the state does not occur in the entity, but it could be misinterpreted that it does, though only rarely.

not scoped score icon Not Scoped – all states of the feature are not scored and will not be scored for the entity.

Numeric features in Lucid may be scored using four possible scores:

Numeric score not set icon  Numeric absent – the numeric feature does not occur in the entity

Numeric score set icon Normal – the numeric feature occurs normally in the entity

Numeric score set icon Misinterpreted – the numeric feature does not occur in the entity, but it could be misinterpreted that it does.

Numeric score set icon Uncertain – the value for the numeric feature for the entity is not known.

not scoped score icon Not Scoped – the numeric feature is not scored and will not be scored for the entity

Note

Normal, Misinterpreted and Uncertain numeric scores are set and distinguished via the Numeric Score Dialog not within the item trees.

Once a numeric Feature has been scored the icon changes to bold.

Scoring

Scoring multi-state features in the Features and Entities panels

Lucid Builder Score Mode button and Score Mode toggle buttonThe simplest way to score entities and features in the Lucid Builder is to click the Enable Score Mode Toggle score mode icon  button  to the right of the Entities panel. If the currently active selected item is an entity, score boxes will appear in the Features tree; if the currently active selected item is a state, score boxes will appear in the Entities tree. At any time you can flip between scoring entities for a state, or states for an entity, by clicking on the Change Score Mode Toggle score mode type icon button.

Tip

If a Feature node is selected in the Features tree instead of a state node, clicking on the Enable Score Mode button will place the Entities tree into score mode but no score boxes will appear. In this case, select a state in the Features tree. Similarly, if nodes of the Features tree are closed so no states are visible, clicking on Enable Score Mode with an entity selected will place the Features tree into score mode but no score boxes will appear. In this case, open nodes in the Features tree to display some states.

Lucid Builder Score toolbarWhen the Lucid Builder is placed in score mode, a series of buttons providing the different possible scores will appear to the right hand side of the Entities panel. Choose the appropriate score by clicking on one of the score buttons, then click on one or more score boxes in the Features or Entities panels.

Scores can be changed at any time, simply by choosing a different score and clicking on a scored box again.

Note that the Not Scoped score can only be applied to all states of a feature. If the Not Scoped score is selected, clicking on the score box for any state will set all states of the feature to Not Scoped. Conversely, if the states of a feature are currently coded using Not Scoped, giving any other score to one state will cause all other states to be given the Absent score.

Propagate scores icon Score propagation

If your key has an Entity hierarchy it is possible to have the Lucid Builder propagate an applied score to a parent entity to propagated down to all the children. The score propagation option can be toggled on or off depending on your needs via the Propagate score mode button Propagate scores icon on the Score toolbar. Alternatively, if you only wish to enable score propagation temporarily you can hold down the Control (ctrl) key when you apply a score to a parent Entity.

Warning

Any score applied to the parent Entity, while Score Propagation is enabled, will overwrite any scores that have already been applied to the child Entities. You can override the propagated score with another score value at anytime. If you mistakenly override scores to child Entities use Undo (ctrl + z) to revert back to the original scores.

Scoring multi-state features in the Score Spreadsheet

Scoring in the Features or Entities trees provides a view of all state scores for one entity, or all entity scores for one state. The Spreadsheet Scoring panel allows you to see all scores arranged into a handy spreadsheet, with entities as columns and states as rows.

To use Spreadsheet score mode, click the Spreadsheet Scoring tab at the base of the tree panels.

Lucid Builder Spreadsheet scoring tab
Lucid Builder Spreadsheet scoring tab
Lucid Builder Spreadsheet scoring example
Lucid Builder Spreadsheet scoring example

To score, select the scoring type needed from the scoring buttons to the right, then click the scoring box corresponding to the entity and feature you wish to score.

The feature list can be expanded or contracted by clicking the plus or minus buttons located next to the parent items or by using the expand all and collapse all buttons in the main toolbar.

Spreadsheet “bulk” Scoring

Where common scores apply to a number of entities listed next to each other or character states you can use “bulk score” functionality. Use the context menu (mouse right click) to mark the start cell, then move the pointer to the last cell across where you wish to apply the scores, you will see the range of cells to be scored highlighted pink, then click to score the cell. All cells between the selected cells will take on this new score value. This same technique can be also used to un-score or change scores in cells. It can also be applied across multiple rows. You can exit bulk scoring mode using the escape key.

Display settings in the Spreadsheet Scoring panel are set through the Builder Preferences dialog box.

See the topic Configuring the Lucid Builder for more information.

Scoring numeric features

In score mode in the Features or Entities trees or in the Spreadsheet Scoring panel, numeric features are shown with a hash symbol in the score box Numeric score set icon. Clicking on a numeric feature’s score box will open the Numeric Scores panel. In this panel, enter the values that the entity can have for the feature.

Four values may be entered – for the outside minimum, normal minimum, normal maximum and outside maximum. Think of the outside scores as rare ranges and the inside as a normal range. For instance, a plant may have leaves that are normally 10-20 mm long, but are occasionally as low as 8 mm or as high as 25 mm. In text, this is often written (8-)10-20(-25). In the dialog box, use 8 for Outside Minimum, 10 for Normal Minimum, 20 for Normal Maximum and 25 for Outside Maximum.

It is not necessary for all these values to be different. The following table gives some examples of valid scores:

Valid Numeric Scores table example

Note

Sometimes a taxon will need to be scored with a disjunct range. For instance, consider a plant that may have 5 or 10-15 petals. In this case, click on the Add Numeric Record button in the Numeric Features panel. A new row will be inserted into the Numeric Scores panel. Score the two (or more) disjunct ranges in separate rows:

Numeric Scoring disjunct range example
Numeric Scoring disjunct range example

The Score Type column in the Numeric Scores panel can be used to assign numeric scores of type NormalUncertain and Misinterpreted.

Use Normal when the values entered are normal for the entity being scored. This is equivalent to the Normally Present and Rarely Present scores for a multi-state feature.

Use the Misinterpreted score type when you are scoring a numeric range for a Feature that may be misinterpreted as being present. For example, a key to insects may include a species that has very small antennae, but large antenna-like structures that could be misinterpreted by a user as being antennae. In this case record the length of the real antennae using a Normal numeric score, and record the length of the antenna-like structures using a Misinterpreted numeric score:

Numeric Scoring Misinterpreted example
Numeric Scoring Misinterpreted example

In this way, a key builder can preempt a mistake made by a user measuring the length of the pseudo-antennae instead of the real antennae.

Use the Uncertain score type to record that a value for a numeric feature is currently unknown.

For more information on the way Misinterpreted and Uncertain scores are handled in the Lucid Player, see How to use the Lucid scores.

Numeric Precision

It is recommend that you maintain a consistent precision level through the scoring of numerics. Take the following example,

 Festuca occidentalis, with scored anther lengths of (1) 1.5 – 2.5 (3) mm

A user of the key enters the following value for the anthers in the Player of 0.5-0.6

Because of the difference between precision on the first compared anther value (1) for Festuca occidentalis, Lucid rounds the 0.5 to 1, leaving Festuca occidentalis in the entities remaining. If the precision level was set to (1.0) then no rounding would occur and Festuca occidentalis would be discarded as a match.

Categories
Lucid Builder v4

Lucid Builder Undoing and Redoing edits

Applies to Matrix and Pathway key projects

Some types of edits to a key (such as adding or deleting items in the trees, scoring and changing feature types) may be undone undo iconby pressing Ctrl-Z or choosing Undo from the Edit menu

The following operations may be undone:

  • Add Item
  • Delete Item
  • Rename Item
  • Change Item Type (e.g. Feature/State)
  • Change Feature Type (Grouping/Multistate/Numeric)
  • Cut
  • Paste
  • Drag and Drop
  • Set Score
  • Clear Score

The undo history is limited to 200 edits. As additional edits are performed the undo edits at the tail of the queue are removed.

The following operations reset the undo history:

  • New Key
  • Open Key
  • Open Recent Key
  • Import Key (LIF/LIF3)
  • Import Item Lists (Feature/Entity)

Any changes made prior to performing these operations cannot be undone or redone.

Operations undone using Ctrl-Z may be redone by pressing Ctrl-Shift-Z or choosing Redo redo icon from the Edit menu.

Categories
Lucid Builder v4

Lucid Builder Finding features, states and entities

Lucid Builder Find Features or States dialog
Lucid Builder Find Features or States dialog
Lucid Builder Find Entities dialog
Lucid Builder Find Entities dialog

To search for a feature or state, activate the Features panel by clicking within it, then choose Find feature/state from the main menu.

To search for an entity, activate the Entities panel by clicking within it, then choose Find entity.

In the Find dialog, type the text to search for in the Find text box. Set the direction of the search using the Forward or Backward radio button options to specify a direction to search from the currently selected item.

The Match Options allow for a case sensitive search and/or to only match on whole words.

To replace existing text enter the find text along with the replacement text in the Replace With text box. Then to selectively replace text use the Find button followed by the Replace button. Alternatively use the Replace All button to replace every instance found of the Find What text.

Tip

The Find function can also be invoked using the keyboard shortcut Ctrl+F or the Find button find/search icon on the main button bar.

Categories
Lucid Builder v4

Lucid Builder Deleting Items in the Feature and Entity trees

Items in the Features and Entities trees may be deleted at any stage by selecting the item and pressing the Delete key, using the Delete button delete icon on the toolbar or choosing Delete from the Edit menu.

If the Builder Preferences option Prompt for confirmation during tree delete operations is checked, a Confirm Delete dialog will appear, to confirm that the operation should go ahead.

Lucid Builder Delete Entity confirmation dialog
Lucid Builder Delete Entity confirmation dialog

If Prompt for confirmation during tree delete operations is unchecked, the item will be deleted immediately without confirmation.

The selected item will be deleted from the key.

Tip

This operation can be undone via the undo operation (ctrl + z).

Warning

If an item to be deleted has children, all descendents will be deleted along with the selected item.

You may also delete several items at a time, by selecting multiple items before choosing Delete:

  • To select a contiguous range of items, select the first item then hold down the Shift key and select the last item in the range.
  • To select a non-contiguous range of items, hold down the Control key while selecting each item.
Categories
Lucid Builder v4

Lucid Builder Sorting items in the Feature and Entity trees

Items in the Features and Entities trees may be sorted into alphabetical order. Select an item in either the Features or Entities panel, then click the Sort button or choose Sort tree items from the Edit menu.

Lucid Builder Sort Entities dialog
Lucid Builder Sort Entities dialog
Lucid Builder Sort Features dialog
Lucid Builder Sort Features dialog

A dialog box will provide three options.

Choose Sort all descendents to alphabetically sort the descendents of the selected feature;

Choose Sort siblings to alphabetically sort the siblings of the selected item;

Choose Sort entire tree to sort all items in the tree.

Categories
Lucid Builder v4

Lucid Builder Moving items in the Feature and Entity trees

Applies to Matrix key projects

Arranging and managing items within the Features and Entities panel can be achieved by using standard operating system methods of Drag and Drop and Cut, Copy and Paste. The Lucid Builder will automatically prevent any movement of items that don’t match logical groupings or inbuilt rules that maintain data consistency.

Drag and Drop items

Items in the Features and Entities trees may be moved to new positions in the tree by dragging and dropping. An item may be dragged to any position within its tree as long as the following rules are not violated:

  • A feature may not be dropped in a position where it would become the sibling of a state
  • A state may not be dropped in a position where there is a sibling feature already present.
  • Items may not be dropped as siblings of existing items with identical names

The Builder will confirm what you wish to do with the item(s) on the destination you have dropped to, via a confirmation dialog.

Lucid Builder Confirm drop action
Lucid Builder Confirm drag and drop action dialog

You may also drag and drop several items at a time:

  • To select a contiguous range of items, select the first item then hold down the Shift key and select the last item in the range
  • To select a non-contiguous range of items, hold down the Control key while selecting each item.

To drag a selection of items:

  • on Microsoft Windows or Linux, click and drag using the left mouse button.
  • on a Macintosh, hold down the Shift key while dragging.

Tip

You may only drag and drop a multiple selection if all the selected items are siblings.

Merge Drop

Merge Drop allows two items to be merged by dragging the merge item and dropping it onto a recipient item while holding down the Ctrl key.

Merge Drop has an important role to play when importing a key for merging, particularly for resolving conflicts after the import. These conflicts can often be resolved by manually merging items using Merge Drop.

Merge Drop can be used in the following ways:

  • State merging: Dropping a state onto another state will result in scores of the dropped state being merged with the receiving state using the score merging rules defined under Import Merging. The receiving state retains its name and the dropped state is removed from its original position in the tree.
  • Feature merging: Dropping a feature onto another feature will result in its states, and all scores for those states, being merged with the receiving feature. Dropped features must be of the same type as the receiving feature (that is, you may not merge a multistate with a numeric feature). In the case of multistate features, any states present in the dropped feature that are not present in the receiving feature are added to the receiving feature. Any common states have their scores merged using the score merging rules defined under Import Merging. The receiving feature retains its name and the dropped feature is removed from its original position in the tree.
  • Entity merging: Dropping an entity onto another entity will result in the scores for both entities being merged together. The receiving entity retains its name and the dropped entity is removed from its original position in the tree.

Moving items using Cut, Copy and Paste

Items in the Features and Entities trees may be moved to new positions in the tree using the familiar Cut, Copy and Paste operations.

To cut or copy an item, select it by clicking on it with the mouse then either:

Choose Cut cut icon or Copy copy icon from the Edit menu or right click context pop-up menu, or

Click the Cut or Copy buttons on the toolbar (see below), or

Use the keyboard shortcut Ctrl-C (copy) or Ctrl-X (cut)

To paste an item that you have copied or cut, select another item in the tree then either:

  • Choose Paste as child or Paste as sibling from the Edit menu.
  • Click the Paste as child or Paste as sibling buttons on the toolbar, or;
  • Use the keyboard shortcut Ctrl-V.

Note

There are restrictions on where an item can be pasted in the tree. For example, a state cannot logically be pasted as a child of a feature that has other features as children, and a feature cannot be pasted in a position where it would become a sibling of a state. Accordingly, some menu options and buttons will be disabled depending on the positions in the tree where you are attempting the paste.

You may also paste several items at a time, by selecting multiple items before choosing Cut or Copy:

  • To select a contiguous range of items, select the first item then hold down the Shift key and select the last item in the range.
  • To select a non-contiguous range of items, hold down the Control key while selecting each item.

Note

You may only paste a multiple selection if all the selected items are siblings.