Searched refs:grade (Results 1 – 25 of 39) sorted by relevance
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14 auto grade = [&](int x, int y){ in __anon5f72f5b40102() variable51 grade(50,50);65 grade(50,150);
14 auto grade = [&](int x, int y){ in __anon6ae844cb0102() variable51 grade(50,50);65 grade(50,150);
71 ... def __init__(self, name, grade, age):73 ... self.grade = grade76 ... return repr((self.name, self.grade, self.age))105 sort by *grade* then by *age*:110 >>> sorted(student_objects, key=attrgetter('grade', 'age'))141 steps. For example, to sort the student data by descending *grade* and then142 ascending *age*, do the *age* sort first and then sort again using *grade*:145 >>> sorted(s, key=attrgetter('grade'), reverse=True) # now sort on primary key, descending164 For example, to sort the student data by *grade* using the DSU approach:166 >>> decorated = [(student.grade, i, student) for i, student in enumerate(student_objects)][all …]
72 ... def __init__(self, name, grade, age):74 ... self.grade = grade77 ... return repr((self.name, self.grade, self.age))106 sort by *grade* then by *age*:111 >>> sorted(student_objects, key=attrgetter('grade', 'age'))152 steps. For example, to sort the student data by descending *grade* and then153 ascending *age*, do the *age* sort first and then sort again using *grade*:156 >>> sorted(s, key=attrgetter('grade'), reverse=True) # now sort on primary key, descending175 For example, to sort the student data by *grade* using the DSU approach:177 >>> decorated = [(student.grade, i, student) for i, student in enumerate(student_objects)][all …]
317 self.vlog.score = self.fc.mf.grade(avg)502 self.vlog.score = self.fc.mf.grade(deviation)666 self.vlog.score = self.fc.mf.grade(max_err)734 self.vlog.score = self.fc.mf.grade(deviation_ratio)772 self.vlog.score = self.fc.mf.grade(actual_count_tid)810 self.vlog.score = self.fc.mf.grade(max_distance)856 self.vlog.score = self.fc.mf.grade(gap_ratio)893 self.vlog.score = self.fc.mf.grade(sum_reversed_motions)926 self.vlog.score = self.fc.mf.grade(actual_count_packets)961 self.vlog.score = self.fc.mf.grade(actual_relative_motion)[all …]
76 def grade(self, x): member in FuzzySingletonMemberFunction115 def grade(self, x): member in FuzzySMemberFunction150 def grade(self, x): member in FuzzyZMemberFunction
35 dnam{"grade"}37 other{"{0} grade"}611 dnam{"grade Celsius"}613 other{"{0} grade Celsius"}616 dnam{"grade Fahrenheit"}618 other{"{0} grade Fahrenheit"}1033 dnam{"grade"}1609 dnam{"grade Celsius"}1614 dnam{"grade Fahrenheit"}
39 dnam{"grade"}40 few{"{0} grade"}42 other{"{0} de grade"}718 dnam{"grade Celsius"}719 few{"{0} grade Celsius"}721 other{"{0} de grade Celsius"}724 dnam{"grade Fahrenheit"}725 few{"{0} grade Fahrenheit"}727 other{"{0} de grade Fahrenheit"}1394 dnam{"grade"}
121 example uses :func:`bisect` to look up a letter grade for an exam score (say)125 >>> def grade(score, breakpoints=[60, 70, 80, 90], grades='FDCBA'):129 >>> [grade(score) for score in [33, 99, 77, 70, 89, 90, 100]]
714 grade, or gradian and equals 1/100-th of the right angle.)
1330 example, sort by department, then by salary grade).
119 example uses :func:`bisect` to look up a letter grade for an exam score (say)123 >>> def grade(score, breakpoints=[60, 70, 80, 90], grades='FDCBA'):127 >>> [grade(score) for score in [33, 99, 77, 70, 89, 90, 100]]
734 grade, or gradian and equals 1/100-th of the right angle.)
1433 example, sort by department, then by salary grade).
680 u32 grade; in clock_init() local689 grade = get_cpu_temp_grade(NULL, NULL); in clock_init()690 if (!grade) { in clock_init()
302 def grade(score, breakpoints=[60, 70, 80, 90], grades='FDCBA'): function306 result = [grade(score) for score in [33, 99, 77, 70, 89, 90, 100]]
85 SAX.elementDecl(grade, 3, ...)87 The Jouyou Kanji grade level. 1 through 6 indicate the grade in which
9 #include "am57xx-industrial-grade.dtsi"
11 #include "am57xx-commercial-grade.dtsi"
538 tempmon_temp_grade: temp-grade@10 {
43 …en a database or a data warehouse and TensorFlow. Apache Ignite is a high-grade database itself. B…
740 a set of evaluation metrics, which will grade the model's performance, and the
1199 the O(n\*n) required for the grade-school multiplication algorithm. (Original