This book is about using Python to get jobs done on Windows.This intended to be a practical book focused on tasks. It doesn t aim to teach Python programming, although we do provide a brief tutorial. Instead, it aims to cover:How Python works on Windows The key integration technologies supported by Python on Windows, such as the Win32 extensions, which let you call the Windows API, and the support for COM Examples in many topic areas showing what Python can do and how to put it to work.
The module LSQ is for unconstrained linear least-squares fitting. It is
based upon Applied Statistics algorithm AS 274 (see comments at the start
of the module). A planar-rotation algorithm is used to update the QR-
factorization. This makes it suitable for updating regressions as more
data become available. The module contains a test for singularities which
is simpler and quicker than calculating the singular-value decomposition.
An important feature of the algorithm is that it does not square the condition
number. The matrix X X is not formed. Hence it is suitable for ill-
conditioned problems, such as fitting polynomials.
By taking advantage of the MODULE facility, it has been possible to remove
many of the arguments to routines. Apart from the new function VARPRD,
and a back-substitution routine BKSUB2 which it calls, the routines behave
as in AS 274.
he LPC932 can be used to create a Pulse Width Modulated PWM signal. That s an analog signal, with only 2 discrete levels, for example 0V and 5V and a constant period. The current value of this signal at a certain poiTnt of time is proportional to its Duty Cycle. That s the High Time during one period divided by the period. It can also be calculated as the average value during a particular period. That means after low pass filtering, (e.g. RC circuit) the signal becomes analog, with an actual value controlled by the microcontroller. The PWM functionality enables the LPC932 to control for example the speed of DC motors or the brightness of electric lighting.
數字運算，判斷一個數是否接近素數
A Niven number is a number such that the sum of its digits divides itself. For example, 111 is a Niven number because the sum of its digits is 3, which divides 111. We can also specify a number in another base b, and a number in base b is a Niven number if the sum of its digits divides its value.
Given b (2 <= b <= 10) and a number in base b, determine whether it is a Niven number or not.
Input
Each line of input contains the base b, followed by a string of digits representing a positive integer in that base. There are no leading zeroes. The input is terminated by a line consisting of 0 alone.
Output
For each case, print "yes" on a line if the given number is a Niven number, and "no" otherwise.
Sample Input
10 111
2 110
10 123
6 1000
8 2314
0
Sample Output
yes
yes
no
yes
no
2^x mod n = 1 acm競賽題 Give a number n, find the minimum x that satisfies 2^x mod n = 1.
Input
One positive integer on each line, the value of n.
Output
If the minimum x exists, print a line with 2^x mod n = 1.
Print 2^? mod n = 1 otherwise.
You should replace x and n with specific numbers.
Sample Input
2
5
Sample Output
2^? mod 2 = 1
2^4 mod 5 = 1
Expert Choice represents a significant contribution to the decision making process 工t assists a decision maker in solving complex problems involving many criteria and several courses of action . An Expert Choice solution to a problem reflects the expertise of the decision maker , not the computer .
Behavioral scientists have spent many years studying the human mind and how it makes decisions . They have found that humans are influenced by their previous experiences and this causes them to have biases . Basic instincts , preferences and environmental factors also play key roles in how we analyze data and make decisions . There 15 way to remove these factors from human decision making , nor would we necessarily want to , but as the problems of our world become more and more complex , it 15 necessary for us to employ a framework to help make more logical and less biased decisions while still taking our feelings and intuition into consideration .
This a simple genetic algorithm implementation where the
evaluation function takes positive values only and the
fitness of an individual is the same as the value of the
objective function
