C&D Pro

Sources
Map: Points to the base map to work with
Data: Points to the source of your data (xls, txt, ODBC)
Display: Displays the result on your screen
Representation
Symbols: Displays absolute values with symbols
Qualitative Symbols : Differenciate categories with distinctive symbols
Filling/shaded areas : Manage the colour palette that corresponds to the classes created by quantification
Pies: Creates a pie which shares represent a part of a percentage
Portions: Creates a pie which shares represent absolute values
Bar chart : Displays coherent statistical data sets. Most commonly used for timed data
Flows: Displays « Origin -> Destination» matrix data
Anamorphosis : Deforms the map according to the data entered
Elevation/3D : Used with Grid, it elevates the squares according to the data entered
Vectors: Displays matrix data
Sea urchins: Links geographical areas by a segment
Values: Displays labels on the map
Background image: Allows the use of georeferenced images behind the main base map
Point cloud: Randomly distributes points using map IDs
Outlines: Draws the borders of all the base maps entered in the organigram
Optimization modules
Setting-up simulation: Simulates a set up according to the data entered
Potential analysis : Targets areas that are more likely to welcome an activity according the data combined
Catchment and cannibalisation areas: Calculates the cannibalisation were several catchment areas interconnect
Operators
Quantification : Creates ensembles of values that look alike
Fusion: Creates new geographical entities by merging entities of the same classe or with the same quality
Agregation: Calculates the sum of a data from a detailled outcut to a larger outcut (e.g. from zip codes to counties)
Sectorization : Creates areas with the same weight
Polarization: Mesures the force of attraction generated by poles according to their weight (population for cities, commercial size for outlets, etc.)
Filter: Selects data according to criterias
Grid: Allows to avoid working with administrative borders by creating a grid that will spread values in a more even way
Pole selection: Selects entities on the map. Used for polarization or sectorization
Principal Component Analysis (PCA) : Summarizes and hierarchizes the information contained in a matrix
Correspondance Analysis (CA) : Summarizes and hierarchizes the information contained in a matrix
Ascending Hierarchical Classification (AHC): Enables an automatic classification of geographical entities to be obtained as a function of a number of statistical data items
Bertin matrix : Classifies the entities of a map as a function of several criteria, in accordance with the visual method of J.Bertin
Minimum distance: Calculates the flying distances between entities in the Target map and entities in the Operator map
The Winner: Find the biggest value among several continuous data
Intersection: Selects entities of a base map crossed by entities of another selected base map, such as roads
Isolines: Creates level lines from a point map or a group of polygons
Length: Calculates the length of each line, and the perimeter of each surface
Matrix operator : Balances data sets
Regression: Estimates if one phenomenon can explain another phenomenon
Box and whiskers : Displays the statistical information of a data
Triangular diagram : Compares three complementary data sets to visualize their relations
Inclusion / exclusion: Selects geographical entities whether they are inside or outside a determined area
Union: Applies the same processing to distinctive base maps
Calculation: Carries out the operation described by the formula entered by the user
Surface: Calculates the area of each polygone of the base map, in the scale use by this map (m or km)
Flying distance : computes the distances between every object in the map
Colouring: Fills every polygon with a colour different from any adjacent polygon