generated from mwc/lab_scatter
	As of right this moment i have not a clue in the world how to make a scatter plot graph.
This commit is contained in:
		@@ -4,9 +4,17 @@
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  - Draw the axes.
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					  - Draw the axes.
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    - Draw the x-axis.
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					    - Draw the x-axis.
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      - Draw the line.
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					      - Draw the line.
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      - ...
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					      - label the axis
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					      choose a scale for the values
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    - Draw the y-axis.
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					    - Draw the y-axis.
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      - Draw the line.
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					      - Draw the line.
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      - ...
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					      - label the axis
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					      - choose a scale for the values
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  - Plot the points.
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					  - Plot the points.
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    - ...
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					    - erad the data (x, y) pairs.
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					    - for each pair:
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					      - find where it belongs on the x and y scales
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					      - draw a small dot at that position
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					    - add finishing touches
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					      - add axis names
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					       - check that all points and labels are visible and clear
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@@ -26,7 +26,7 @@ from transform import (
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    get_x_values,
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					    get_x_values,
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    get_y_values,
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					    get_y_values,
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)
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					)
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					#67
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def draw_scatterplot(data, size=5, color="black"):
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					def draw_scatterplot(data, size=5, color="black"):
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    "Draws a scatter plot, showing the data"
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					    "Draws a scatter plot, showing the data"
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    prepare_screen()
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					    prepare_screen()
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										51
									
								
								transform.py
									
									
									
									
									
								
							
							
						
						
									
										51
									
								
								transform.py
									
									
									
									
									
								
							@@ -6,38 +6,73 @@
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def maximum(data):
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					def maximum(data):
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    "Returns the largest number in data"
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					    "Returns the largest number in data"
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    raise NotImplementedError
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					    highest = None
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					    for number in data:
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					        if highest is None:
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					            highest = number
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					        if number > highest:
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					            highest = number
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					    return highest
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def minimum(data):
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					def minimum(data):
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    "Returns the smallest number in data"
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					    "Returns the smallest number in data"
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    raise NotImplementedError
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					    lowest = None
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					    for number in data:
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					        if lowest is None:
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					            lowest = number
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					        if number < lowest:
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					            lowest = number
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					    return lowest
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def bounds(data):
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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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					    "Returns a list of the smallest and largest numbers in data"
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    raise NotImplementedError
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					    highest = maximum(data)
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					    lowest = minimum(data)
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					    return [lowest, highest]
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def clamp(value, low, high):
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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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					    """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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					    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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					    If value is lower than low, returns low. If value is higher than high, returns high.
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    """
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					    """
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    raise NotImplementedError
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					    if value < low:
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					        return low
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					    elif value > high:
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					        return high
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					    else:
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					        return value
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def ratio(value, start, end):
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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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					    """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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					    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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					    value will not be lower than 0.0.
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    """
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					    """
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    raise NotImplementedError
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					    number = (value-start)/(end-start)
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					    number = clamp(number, 0.0, 1.0)
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					    return number
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def scale(value, domain_min, domain_max, range_min, range_max):
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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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					    "Given a value within a domain, returns the scaled equivalent within range."
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    raise NotImplementedError
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					    scale = range_min + ((ratio(value, domain_min, domain_max))*(range_max - range_min))
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					    return scale
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def get_x_values(points):
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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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					    "Returns the first value for each point in points."
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    raise NotImplementedError
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					    x_list = []
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					    for point in points:
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					        x = point[0]
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					        x_list.append (x)
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					    return x_list
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def get_y_values(points):
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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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					    "Returns the second value for each point in points."
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    raise NotImplementedError
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					    y_list = []
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					    for point in points:
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					        y = point[1]
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					        y_list.append (y)
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					    return y_list
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