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59
boards/default_src/python_skulpt/templates/python/mixpy.py
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59
boards/default_src/python_skulpt/templates/python/mixpy.py
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import math
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def math_map(v, al, ah, bl, bh):
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return bl + (bh - bl) * (v - al) / (ah - al)
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def math_mean(myList):
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localList = [e for e in myList if type(e) == int or type(e) == float]
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if not localList: return
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return float(sum(localList)) / len(localList)
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def math_median(myList):
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localList = sorted([e for e in myList if type(e) == int or type(e) == float])
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if not localList: return
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if len(localList) % 2 == 0:
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return (localList[len(localList) // 2 - 1] + localList[len(localList) // 2]) / 2.0
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else:
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return localList[(len(localList) - 1) // 2]
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def math_modes(some_list):
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modes = []
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# Using a lists of [item, count] to keep count rather than dict
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# to avoid "unhashable" errors when the counted item is itself a list or dict.
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counts = []
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maxCount = 1
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for item in some_list:
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found = False
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for count in counts:
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if count[0] == item:
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count[1] += 1
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maxCount = max(maxCount, count[1])
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found = True
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if not found:
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counts.append([item, 1])
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for counted_item, item_count in counts:
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if item_count == maxCount:
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modes.append(counted_item)
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return modes
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def math_standard_deviation(numbers):
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n = len(numbers)
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if n == 0: return
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mean = float(sum(numbers)) / n
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variance = sum((x - mean) ** 2 for x in numbers) / n
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return math.sqrt(variance)
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def lists_sort(my_list, type, reverse):
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def try_float(s):
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try:
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return float(s)
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except:
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return 0
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key_funcs = {
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"NUMERIC": try_float,
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"TEXT": str,
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"IGNORE_CASE": lambda s: str(s).lower()
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}
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key_func = key_funcs[type]
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list_cpy = list(my_list)
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return sorted(list_cpy, key=key_func, reverse=reverse)
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