| 135 | | -'''Nomenclature types:''' The ''nomenclature type'' is defined as the character string representing the index for the first file in the series, for instance '_1' for a single indexing and '_1-2' for a pair indexing, '_1_1' for a double index series. The second index j can be also represented as a letter suffix, for instance '01a'. For a field series in a single file, like a movie, the nomenclature type is defined as '*'. The functions ''fullfile_uvmat.m'' generates a file name from a root name, four numerical indices i1,i2,j1,j2 and the ''nomenclature type''. The reverse operation, splitting a name into a root and indices while detecting the ''nomenclature type'', is performed by the function ''fileparts_uvmat.m''. The function ''find_file_series.m'' is also needed to scan the whole file series, leading to a possible adjustement of the nomenclature type (for instance distinguishing '_001' from '_1' when the file with index 1000 has been opened). Once the nomenclature type has been detected by the browser of '''uvmat.fig''', it is displayed in the edit box '''[!NomType]''' and used to generate all the file names when the series is scanned. |
| 136 | | |
| 137 | | === 3.4 Navigation among file indices === |
| | 135 | -'''Nomenclature types:''' The ''nomenclature type'' is defined as the character string representing the index (or indices) for the first file in the series, for instance '_1' for a ''single indexing'' and '_1-2' for a ''pair indexing'', '_1_1' for a ''double index'' series. The second index j can be also represented as a letter suffix, for instance '01a'. For a field series in a single file, like a movie, the nomenclature type is defined as '*'. The functions ''fullfile_uvmat.m'' generates a file name from a root name, four numerical indices i1,i2,j1,j2 and the ''nomenclature type''. The reverse operation, splitting a name into a root and indices while detecting the ''nomenclature type'', is performed by the function ''fileparts_uvmat.m''. The function ''find_file_series.m'' is also needed to scan the whole file series, leading to a possible adjustement of the nomenclature type (for instance distinguishing '_001' from '_1' when the file with index 1000 has been opened). Once the nomenclature type has been detected by the browser of '''uvmat.fig''', it is displayed in the edit box '''[!NomType]''' and used to generate all the file names when the series is scanned. |
| | 136 | |
| | 137 | === 3.4 Navigation among field indices === |
| 302 | | Physical fields can be defined either on regular grids, either scattered on an unstructured set of positions. Some measurements techniques, like PIV or particle tracking, provided unstructured data, while most methods of analysis require data on a regular grid. This can be done by interpolation, defining a projection on a plane (with ProjMode='interp', see [#a6-Projectionobjects: next section]). The three possibilities of griding are defined as follows: |
| | 302 | Physical fields can be defined either on regular grids, either scattered on an unstructured set of positions. Some measurements techniques, like PIV or particle tracking, provided unstructured data, while most methods of analysis require data on a regular grid. This can be done by interpolation, defining a projection on a plane (with !ProjMode='interp...', see [#ProjObject next section]). The three possibilities of griding are defined as follows: |
| 314 | | Fields may be alternatively obtained on a unstructured (grid-less) set of positions. The coordinates are then described by coordinate arrays X(nb_points), Y(nb_points), Z(nb_points). The corresponding field values are then represented as variables |
| | 314 | Fields may be alternatively obtained on a unstructured (grid-less) set of positions. The coordinates are then described by coordinate arrays X(nb_points), Y(nb_points), Z(nb_points). The corresponding field values are then represented as variables U(nb_point),V(nb_point) for each vector component, or alternatively by V(nb_points, j, i), where i, j possibly stand for vector or tensor components. |
| 318 | | This is a multi-dimensional generalisation of the spline interpolation/smoothing, an optimum way to interpolate data with minimal curvature of the interpolating function. The result at an interpolation {site} ${\bf r}$ is expressed in the form, (see http://coriolis.legi.grenoble-inp.fr/spip.php?article73) |
| 319 | | |
| 320 | | $$\label{sol_gene} f({\bf r})=\sum S_i \phi({\bf|r-r_i}|)+a_0+a_1x+a_2y\; $$ where {\bf r_i} are the positions of the measurement points (the ''centres''). Each ''centre'' can be viewed as the source of an axisymmetric field $\phi$ of the form $\phi(r)=r^2\log (r)$. The weights $S_i$ and the linar coefficients $a_0,a_1,a_2$ are the tps coefficients which determine the interpolated value at any point. The spatial derivatives are similarly obtained at any point by analytical differentiation of the source functions $\phi(r)$. These tps coefficients therefore contain all the information for interpolation at any point. ^ |
| | 318 | This is a multi-dimensional generalisation of the spline interpolation/smoothing, an optimum way to interpolate data with minimal curvature of the interpolating function. The result at an interpolation position vector ${\bf r}$ is expressed in the form, (see http://coriolis.legi.grenoble-inp.fr/spip.php?article73) |
| | 319 | |
| | 320 | $$\label{sol_gene} f({\bf r})=\sum S_i \phi({\bf|r-r_i}|)+a_0+a_1x+a_2y\; $$ where ${\bf r_i}$ are the positions of the measurement points (the ''centres''). Each ''centre'' can be viewed as the source of an axisymmetric field $\phi$ of the form $\phi(r)=r^2\log (r)$. The weights $S_i$ and the linar coefficients $a_0,a_1,a_2$ are the thin plate shell (tps) coefficients which determine the interpolated value at any point. The spatial derivatives are similarly obtained at any point by analytical differentiation of the source functions $\phi(r)$. These tps weights, with the corresponding centre coordinates, therefore contain all the information needed for interpolation at any point. We call that a ''tps field representation''. |
| 329 | | This field has a specific organisation, mirroring the structure of netcdf files (see [#a7-Netcdffilesandget_field.fig: section 7]). The field is described by a set of (single or multidimensional) data arrays, called the ''variables''. The ''dimensions'' of these arrays have names, in order to identify correspondance between different arrays. For instance the arrays representing the velocity components U and V must have the same dimensions. A dimension has a specific value, which sets the common size of all arrays sharing this dimension. Field description furthermore involves optional ''attributes'' to document the field data, for instance to specify the role of variables or to provide units. These attributes can be global, or can be attached to a specific variable. |
| | 329 | This field has a specific organisation, mirroring the structure of netcdf files (see [#a7-Netcdffilesandget_field section 7]). The field is described by a set of (single or multidimensional) data arrays, called the ''variables''. The ''dimensions'' of these arrays have names, in order to identify correspondance between different arrays. For instance the arrays representing the velocity components U and V must have the same dimensions. A dimension has a specific value, which sets the common size of all arrays sharing this dimension. Field description furthermore involves optional ''attributes'' to document the field data, for instance to specify the role of variables or to provide units. These attributes can be global, or can be attached to a specific variable. |
| 333 | | * (optional) '''!ListGlobalAttribute:''' list (cell array of character strings) of the names of global attributes Att_1, Att_2... |
| 334 | | * (mandatory) '''!ListVarName:''' list of the variable names Var_1, Var_2....(cell array of character strings). |
| 335 | | * (mandatory) '''!VarDimName:''' list of the dimensions associated with each variable: this is a cell array whose number of element is equal to that of '''!ListVarName'''. Each element is the dimension name for a unidimensional variable, or a cell array specifying the list of dimension names for a multidimensional variable. |
| 336 | | * (optional) '''!VarAttribute:''' cell array of structures of the form !VarAttribute{ivar}.key=value, defining an attribute tag name and value for the variable #ivar (variable number in the list !ListVarName]). |
| | 333 | * (optional) '''ListGlobalAttribute:''' list (cell array of character strings) of the names of global attributes Att_1, Att_2... |
| | 334 | * (mandatory) '''ListVarName:''' list of the variable names Var_1, Var_2....(cell array of character strings). |
| | 335 | * (mandatory) '''VarDimName:''' list of the dimensions associated with each variable: this is a cell array whose number of element is equal to that of '''!ListVarName'''. Each element is the dimension name for a unidimensional variable, or a cell array specifying the list of dimension names for a multidimensional variable. |
| | 336 | * (optional) '''VarAttribute:''' cell array of structures of the form !VarAttribute{ivar}.key=value, defining an attribute tag name and value for the variable #ivar (variable number in the list !ListVarName]). |
| 370 | | * |
| 371 | | * |
| 372 | | * |
| | 370 | * !DataSeries: recalls the device name (s), if defined, of the raw data |
| | 371 | * !ObjectStyle: ='points', 'line', 'plane', denotes the style of geometric object on which the data have been 'projected'. For instance a profiler project a physical field along a line. |
| | 372 | * !ObjectCoord: Coordinates defining a geometric object on which the data have been projected. |
| 397 | | The variables of field objects are split into {field cells} representing spatial fields. Differerent types of field cells are identified for processing and plotting. This identification is performed by the function ''find_field_cells.m'' which first groups the variables into cells of variables sharing common variable dimensions, determines their spatial dimension, and idendify the following types. |
| 398 | | |
| 399 | | * Dimension variables: these are unique unidimensional variable arrays corresponding to a given dimension, leading to a cell with a single variable, dimension 1. This is interpreted as the set of coordinate values associated with this dimension. An alternative possibility, suitable for a coordiante with a constant grid mesh, is a variable array with two values with the same name as a dimension: it then specifies the lower and upper bounds of the coordinate. |
| 400 | | * Field cell with unstructured coordinates: this is a cell of variables sharing the same set of unstructured coordinates, indicated by the attribute Role=coord_x, coord_y, coord_z. |
| 401 | | * Field cell with structured coordinates: this is a cell of several variable(s) sharing the same set of dimensions associated with variables. (addditional dimension may indicate for instance a vector component, not associated with a coordinate). |
| 402 | | * Thin plate shell (tps) field cell: represents a set of coordinates and tps weights in a way suitable for tps interpolation/filter. |
| | 397 | The variables of field structures can be grouped into ''field cells'' representing data sharing the same coordinates. Differerent types of field cells are identified for processing and plotting. This identification is performed by the function ''find_field_cells.m'' which first groups the variables into cells sharing common array dimensions, determines their spatial dimension, and idendify the following types of field cells, corresponding to the different kinds of data griding described in [wiki:#a5.1Gridingofdata section 5.1] |
| | 398 | |
| | 399 | * '''Dimension variables:''' these are unique unidimensional variable arrays corresponding to a given dimension, leading to a cell with a single variable, dimension 1. This is interpreted as the set of coordinate values associated with this dimension. An alternative possibility, suitable for a coordiante with a constant grid mesh, is a variable array with two values with the same name as a dimension: it then specifies the lower and upper bounds of the coordinate. |
| | 400 | * '''Field cell with structured coordinates:''' this is a cell of several variable(s) sharing the same set of dimensions associated with variables. (addditional dimension may indicate for instance a vector component, not associated with a coordinate). |
| | 401 | * '''Field cell with unstructured coordinates:''' this is a cell of variables sharing the same set of unstructured coordinates, indicated by the attribute Role=coord_x, coord_y, coord_z. |
| | 402 | * '''Thin plate shell (tps) field cell:''' represents an (unstructured) set of coordinates and tps weights in a way suitable for tps interpolation. |
| 474 | | * |
| 475 | | * ProjMode='interp_lin': non-false data are linearly interpolated on the line, with mesh =DX along the line. Data which are 'discrete','warnflag' or 'errorflag' (as defined by the attribute 'Role') are not projected. |
| | 474 | * !ProjMode='projection': in the case of unstructured coordinates, each data point in the region of action (width max(RangeY) around the line) is projected onto the line. The direction of projection is normal except if 'Phi' is non equal to 0 (only possible for 'line'). For structured coordinates with meshes DX,DY (DZ), data are interpolated on the line with a mesh =min(DX,DY,DZ). For each field component U, a corresponding projected field U is produced. If DX is defined on the line, a smoothed field U_smooth is also calculated, as well as the mean U_mean along the line. |
| | 475 | * !ProjMode='interp_lin': non-false data are linearly interpolated on the line, with mesh =DX along the line. Data which are 'discrete','warnflag' or 'errorflag' (as defined by the attribute 'Role') are not projected. |
