generated from mwc/lab_scatter
8310dd9304
I think i am used to bottom-up problem solving. I like doing problems by first utilizing the knowledge I already have and expanding it. Top-down thinking, like we did in checkpoint 1 may sometimes make it difficult to proceed once you get stuck in a step. For bottom up, you can move onto a different part which you already know.
76 lines
2.0 KiB
Python
76 lines
2.0 KiB
Python
# transform.py
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# ------------
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# By MWC Contributors
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# The functions in this module transform data.
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# None of them are finished; this is your job!
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def maximum(data):
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"Returns the largest number in data"
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max= None
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for n in data:
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if max is None:
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max = n
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if n > max:
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max = n
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return max
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def minimum(data):
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"Returns the smallest number in data"
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min= None
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for n in data:
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if min is None:
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min = n
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if n < min:
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min = n
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return min
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def bounds(data):
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"Returns a list of the smallest and largest numbers in data"
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bounds=[]
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bounds.append(minimum(data))
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bounds.append(maximum(data))
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return bounds
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def clamp(value, low, high):
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"""Clamps a value to a range from low to high.
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Returns value if it is between low and high.
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If value is lower than low, returns low. If value is higher than high, returns high.
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"""
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val= None
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if value > low and value < high:
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val= value
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if value <= low:
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val = low
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if value >= high:
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val= high
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return val
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def ratio(value, start, end):
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"""Returns a number from 0.0 to 1.0, representing how far along value is from start to end.
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The return value is clamped to [0, 1], so even if value is lower than start, the return
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value will not be lower than 0.0.
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"""
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ratio= (value-start)/(end-start)
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return clamp(ratio, 0, 1)
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def scale(value, domain_min, domain_max, range_min, range_max):
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"Given a value within a domain, returns the scaled equivalent within range."
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r= ratio(value,domain_min, domain_max)
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scale= range_min+r*(range_max-range_min)
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return scale
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def get_x_values(points):
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"Returns the first value for each point in points."
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xs=[]
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for point in points:
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xs.append(point[0])
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return xs
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def get_y_values(points):
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"Returns the second value for each point in points."
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ys=[]
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for point in points:
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ys.append(point[1])
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return ys |