Extracting room numbers from a ‘Description’ column in a DataFrame using regular expressions:
Import the re module:
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import re ````
2. Define a function to extract the room number from a description:
```python defextract_room_number(description): match = re.search(r'(\d+\.\d+|\d+)(?=\s+of which are bedrooms)', description) ifmatch: returnfloat(match.group(1)) else: returnNone
Use the apply() method to apply the function to the ‘Description’ column and create a new ‘RoomNumber’ column:
A shell built-in command is contained in the shell itself (implemented by shell author) and runs on the same shell without creating a new process, e.g. cd, pwd, exit, alias.
By contrast: For a regular(linux) command, it is run from a binary file (found in $PATH or specified file) by forking the existing process in a subshell, e.g. ls, cat, rm.
How to implement
1. Judge whether is build-in command
Assume we have already got the parsed arguments
char * parsedArgs[MAXPARSE].
For example, a input char * input = "cd .." can be parsed as char * parsedArgs[MAXPARSE] = {"cd", ".."}
Then, we just need to judge whether parsedArgs[0] is contained in our build-in command set {"exit", "cd", "pwd" ...} (by using strcmp)
2. Implementation
In this project (as of milestone 2) , we need to implement exit, pwd, cd.
exit
In Bash, exit is a built-in command used to terminate the current shell session (same in our mumsh).
Each running shell is a process, so we can use the exit() in stdlib.h to terminate the shell process, achieving the goal of exiting the shell.
Running a crude (or minimal?) shell and have no idea where you are? Just type pwd and it will print the name of the current/working directory.
In C, we can implement the similar functionality using the getcwd() in unistd.h.
if success, getcwd() will return the pointer to the result, else ( e.g. no enough space) return NULL
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voidexec_pwd(){ char buf[1024]; // memory space need for storage printf("%s\n", getcwd(buf,sizeof(buf))); }
However, the working directory is not guaranteed to be shorter than 1024, so we may need to dynamically allocate the buffer to suit the length.
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int size = 100; char *buffer = malloc(size);
while (getcwd(buffer, size) == NULL) { if (errno == ERANGE) { // buffer too small size *= 2; buffer = realloc(buffer, size); } else { // other error ... free(buffer); return1; } }
printf("%s\n", buffer);
free(buffer);
cd
cd is used for changing working directory.
In C, we can implement the similar functionality using the chdir() in unistd.h.
if success, chdir() will return 0, else ( e.g. no such directory) return -1
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voidexec_cd(char * path){ chdir(path); }
Very straight forward, but if we want to implement more advanced features of the cd command such as changing to the home directory or the previous directory, we would need to handle these cases manually.
For example, you could check if the argument is ~ or -, and then call chdir() with the appropriate path
central command center send instructions Some win, some lose
Decentralized
plan trip independently, selfish little communication Sometime efficient, sometime inefficient
In-trip decisions
offline info
static, in form of map
online info
enable the route to be adapted to changing traffic conditions
Post-trip decision
Speed tracking
Dynamic system
State Variable
$v[t]$
State space
$R>= 0$
Control input
$u[t]$(accel)
System dynamic
$v[t+dt] = v[t]+u[t]*dt$
Open-loop control
Specify the control input $u[t]$ for all t in $[0,T]$ not a good idea for autonomous driving.
In practice, we need to consider the uncertainty of the system. We should have: $$ v[t+dt]=v[t]+u[t]dt+w(t) $$ Where w(t) is the noise term capturing the uncertainty of the system.
Closed-loop control
Specify the control input $u[t]$ as a function of the state $v[t]$ able to adapt to the uncertainty of the system. Compare the state $v[t]$ with the desired state $v_desired[t]$ Essentially, we need a mapping from state to control input like map speed to acceleration $$ v[t+dt]=v[t]+mu[v[t]]dt+w(t) $$
Linear controller
the $u[t]$ has linear relationship with $v[t]$ $$ \mu[v] = k[v-v_{desired}] $$
LTI system
linear time-invariant
Control of LTI system
exponential convergence is stronger than asymptotic convergent if LTI system is asymptotic convergent, it is also exponential convergent $$ x[t+1]=ax[t]+bu[t] $$
