##// END OF EJS Templates
Updates method for reading results according to the value type (vector or scalar)
Alexandre Leroux -
r564:c797ff6ef110
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@@ -45,6 +45,25 bool isCommentLine(const QString &line)
45 return line.startsWith("#");
45 return line.startsWith("#");
46 }
46 }
47
47
48 /// @return the number of lines to be read depending on the type of value passed in parameter
49 int nbValues(AmdaResultParser::ValueType valueType) noexcept
50 {
51 switch (valueType) {
52 case AmdaResultParser::ValueType::SCALAR:
53 return 1;
54 case AmdaResultParser::ValueType::VECTOR:
55 return 3;
56 case AmdaResultParser::ValueType::UNKNOWN:
57 // Invalid case
58 break;
59 }
60
61 // Invalid cases
62 qCCritical(LOG_AmdaResultParser())
63 << QObject::tr("Can't get the number of values to read: unsupported type");
64 return 0;
65 }
66
48 /**
67 /**
49 * Reads stream to retrieve x-axis unit
68 * Reads stream to retrieve x-axis unit
50 * @param stream the stream to read
69 * @param stream the stream to read
@@ -74,10 +93,13 Unit readXAxisUnit(QTextStream &stream)
74 * @param stream the stream to read
93 * @param stream the stream to read
75 * @return the pair of vectors x-axis data/values data that has been read in the stream
94 * @return the pair of vectors x-axis data/values data that has been read in the stream
76 */
95 */
77 QPair<QVector<double>, QVector<double> > readResults(QTextStream &stream)
96 QPair<QVector<double>, QVector<QVector<double> > >
97 readResults(QTextStream &stream, AmdaResultParser::ValueType valueType)
78 {
98 {
99 auto expectedNbValues = nbValues(valueType);
100
79 auto xData = QVector<double>{};
101 auto xData = QVector<double>{};
80 auto valuesData = QVector<double>{};
102 auto valuesData = QVector<QVector<double> >(expectedNbValues);
81
103
82 QString line{};
104 QString line{};
83
105
@@ -85,27 +107,31 QPair<QVector<double>, QVector<double> > readResults(QTextStream &stream)
85 // Ignore comment lines
107 // Ignore comment lines
86 if (!isCommentLine(line)) {
108 if (!isCommentLine(line)) {
87 auto lineData = line.split(RESULT_LINE_SEPARATOR, QString::SkipEmptyParts);
109 auto lineData = line.split(RESULT_LINE_SEPARATOR, QString::SkipEmptyParts);
88 if (lineData.size() == 2) {
110 if (lineData.size() == expectedNbValues + 1) {
89 // X : the data is converted from date to double (in secs)
111 // X : the data is converted from date to double (in secs)
90 auto x = doubleDate(lineData.at(0));
112 auto x = doubleDate(lineData.at(0));
91
113
92 // Value
93 bool valueOk;
94 auto value = lineData.at(1).toDouble(&valueOk);
95
96 // Adds result only if x is valid. Then, if value is invalid, it is set to NaN
114 // Adds result only if x is valid. Then, if value is invalid, it is set to NaN
97 if (!std::isnan(x)) {
115 if (!std::isnan(x)) {
98 xData.push_back(x);
116 xData.push_back(x);
99
117
118 // Values
119 for (auto valueIndex = 0; valueIndex < expectedNbValues; ++valueIndex) {
120 auto column = valueIndex + 1;
121
122 bool valueOk;
123 auto value = lineData.at(column).toDouble(&valueOk);
124
100 if (!valueOk) {
125 if (!valueOk) {
101 qCWarning(LOG_AmdaResultParser())
126 qCWarning(LOG_AmdaResultParser())
102 << QObject::tr(
127 << QObject::tr(
103 "Value from line %1 is invalid and will be converted to NaN")
128 "Value from (line %1, column %2) is invalid and will be "
104 .arg(line);
129 "converted to NaN")
130 .arg(line, column);
105 value = std::numeric_limits<double>::quiet_NaN();
131 value = std::numeric_limits<double>::quiet_NaN();
106 }
132 }
107
133 valuesData[valueIndex].append(value);
108 valuesData.push_back(value);
134 }
109 }
135 }
110 else {
136 else {
111 qCWarning(LOG_AmdaResultParser())
137 qCWarning(LOG_AmdaResultParser())
@@ -160,7 +186,8 std::shared_ptr<IDataSeries> AmdaResultParser::readTxt(const QString &filePath,
160
186
161 // Reads results
187 // Reads results
162 stream.seek(0); // returns to the beginning of the file
188 stream.seek(0); // returns to the beginning of the file
163 auto results = readResults(stream);
189 auto results = readResults(stream, valueType);
190
164
191
165 return std::make_shared<ScalarSeries>(std::move(results.first), std::move(results.second),
192 return std::make_shared<ScalarSeries>(std::move(results.first), std::move(results.second),
166 xAxisUnit, Unit{});
193 xAxisUnit, Unit{});
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