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Added two features. 1) to facilitate python access, we now preprocess

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input_table so that string variables are changed as cellstr and
multicolumn variables (e.g., scientaEkinRange_eV) are splitted into
independent variables. 2) we now support when there is no dataset columns (arrays) by creating a dummy dataset called DS_EMPTY. This is required to create a new h5 file for the first time using h5create.
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florez_j committed 2023-10-06 15:25:21 +02:00
1 parent ac7f34a30a
commit bb09c5fe28
1 file changed
+47 -36
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import/save_table_as_hdf5.m
+47 -36
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@@ -10,6 +10,11 @@ function success = save_table_as_hdf5(input_table, filename)
% Email: juan.florez-ospina@psi.ch
if istable(input_table)
string_columns = input_table(:,vartype("string")).Properties.VariableNames;
input_table = convertvars(input_table,string_columns,'cellstr');
% split multicolumn variables
input_table = splitvars(input_table);
column_names = input_table.Properties.VariableNames;
else
success = 0;
@@ -58,44 +63,50 @@ cell_table = input_table(:,rest_columns);
[rows, cols] = size(input_table);
for i = 1 : rows
group_name = strcat("/MEAS",string(i),"/");
for j = 1 : length(rest_columns)
dataset_name = strcat("DS",string(rest_columns_idx(j)));
% Some table entries do not provide direct access to the object
% of interest, but may contain either {object} or {{object}}.
% The following loop solves that problem. TODO: is this generic enough?
data = cell_table{i,column_names{rest_columns_idx(j)}}{1}; % <=> data = cell_table{i,rest_columns{j}}{1};
while iscell(data)
data = data{1};
group_name = strcat("/MEAS_",string(i),"/");
if ~isempty(rest_columns)
for j = 1 : length(rest_columns)
dataset_name = strcat("DS",string(rest_columns_idx(j)));
% Some table entries do not provide direct access to the object
% of interest, but may contain either {object} or {{object}}.
% The following loop solves that problem. TODO: is this generic enough?
data = cell_table{i,column_names{rest_columns_idx(j)}}{1}; % <=> data = cell_table{i,rest_columns{j}}{1};
while iscell(data)
data = data{1};
end
% when there is no data, we still need to provide a valid size
if ~isempty(data)
sz = size(data);
else
sz = [1,1];
end
%%%%
% Group's dataset: Create dataset of size sz in a certain group
h5create(filename, strcat(group_name,dataset_name),sz);
% Dataset's attribute: Add attribute with dataset_name equal to column_name
attr = "column_name";
attr_value = column_names{rest_columns_idx(j)}; % <=> rest_columns{j};
h5writeatt(filename,strcat(group_name,dataset_name),attr,attr_value)
%attr = "column_name_idx";
%attr_value = rest_columns_idx(j); % <=> rest_columns{j};
%h5writeatt(filename,strcat(group_name,dataset_name),attr,attr_value)
% Assign 'data' to the dataset. 'data' has to be of admissible type.
try
h5write(filename,strcat(group_name,dataset_name),data)
catch exception
disp(exception)
%h5write(filename,strcat(group_name,dataset_name),cell_table{i,rest_columns{j}})
end
end
% when there is no data, we still need to provide a valid size
if ~isempty(data)
sz = size(data);
else
sz = [1,1];
end
%%%%
% Group's dataset: Create dataset of size sz in a certain group
else
dataset_name = "DS_EMPTY";
sz = [1,1];
h5create(filename, strcat(group_name,dataset_name),sz);
% Dataset's attribute: Add attribute with dataset_name equal to column_name
attr = "column_name";
attr_value = column_names{rest_columns_idx(j)}; % <=> rest_columns{j};
h5writeatt(filename,strcat(group_name,dataset_name),attr,attr_value)
%attr = "column_name_idx";
%attr_value = rest_columns_idx(j); % <=> rest_columns{j};
%h5writeatt(filename,strcat(group_name,dataset_name),attr,attr_value)
% Assign 'data' to the dataset. 'data' has to be of admissible type.
try
h5write(filename,strcat(group_name,dataset_name),data)
catch exception
disp(exception)
%h5write(filename,strcat(group_name,dataset_name),cell_table{i,rest_columns{j}})
end
end
% Group's attribute: Assign group attributes