Files
lab_scatter/transform.py
grace-xing6 e45505fe9a updated transform
The first several one went very well, I also enjoy solving the problems.
I was stuck with 6 a bit, trying to understand the meaning of it.
I took longer time on the last two tasks, my initial plan is to redefine [x,y] = value, then let it return x
Then I found that there was a problem of return a list, i asked ChatGpt's help when I was stuck on it
it gave me a great suggestions on how to fix it. It also provides a much concise way to solve the problem: return [point[0] for point in points]
 I thinl the thinking way is different especially for 6. I also think the concise coding might be better to adpot in the future
2024-10-03 22:38:46 -04:00

77 lines
2.2 KiB
Python

# transform.py
# ------------
# By MWC Contributors
# The functions in this module transform data.
# None of them are finished; this is your job!
def maximum(data):
"Returns the largest number in data"
biggest = None
for number in data:
if biggest is None:
biggest = number
if number > biggest:
biggest = number
return biggest
def minimum(data):
"Returns the smallest number in data"
lowest = None
for number in data:
if lowest is None:
lowest = number
if number < lowest:
lowest = number
return lowest
def bounds(data):
"Returns a list of the smallest and largest numbers in data"
return [minimum(data), maximum(data)]
def clamp(value, low, high):
"""Clamps a value to a range from low to high.
Returns value if it is between low and high.
If value is lower than low, returns low. If value is higher than high, returns high.
"""
if value < low:
return low
if value > high:
return high
if value > low and value < high:
return value
def ratio(value, start, end):
"""Returns a number from 0.0 to 1.0, representing how far along value is from start to end.
The return value is clamped to [0, 1], so even if value is lower than start, the return
value will not be lower than 0.0.
"""
if (value - start)/(end - start) < 0:
return 0
if (value - start)/(end - start) > 0:
return (value - start)/(end - start)
def scale(value, domain_min, domain_max, range_min, range_max):
"Given a value within a domain, returns the scaled equivalent within range."
ratio = (value - domain_min) / (domain_max - domain_min)
"caculate the ratio first"
return range_min + ratio * (range_max - range_min)
def get_x_values(points):
"Returns the first value for each point in points."
x_values = []
for point in points:
[x, y] = point
x_values.append(x)
return x_values
def get_y_values(points):
"Returns the second value for each point in points."
y_values = []
for point in points:
[x, y] = point
y_values.append(y)
return y_values