SharedHandouts / Group 11 Lab 2 Shared .sagewsOpen in CoCalc
Authors: shouq Alshahrani, Hannah Kravitz, Leslie Rueda, Jazmin Santiago, Tearra Sheidler
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##### Group 11 Lab 2 Grade: 15/20 # Group 11 # Math 119A Lab 2 # 1) a=5 show(a) b="5" show(b) # 2) a=5+1 show(a) b="5"+"1" show(b)
5\displaystyle 5
5
6\displaystyle 6
51
# 3) type(a) type(b)
<type 'sage.rings.integer.Integer'> <type 'str'>
# 4) type(0.2) type(x^2)
<type 'sage.rings.real_mpfr.RealLiteral'> <type 'sage.symbolic.expression.Expression'>
# 5) bacteria=[100,200,400,800] ##### Good. -HK # 6) bacteria # 7) type(bacteria) ##### Good. -HK
[100, 200, 400, 800] <type 'list'>
# 8) bacteria[1] bacteria[0]
200 100
# 9) bacteria.append(1600) ##### Good. -HK
bacteria
[100, 200, 400, 800, 1600]
# 10) bacteria.append(3200)
bacteria
[100, 200, 400, 800, 1600, 3200]
# 11) kingdoms=["Bacteria","Protists","Plants","Fungi","Animals"]
kingdoms[0]
'Bacteria'
kingdoms.append("Archaea") kingdoms.append("Archaea") kingdoms
['Bacteria', 'Protists', 'Plants', 'Fungi', 'Animals', 'Archaea', 'Archaea']
# We got the results above because we ran kingdoms.append("Archaea") twice, so it added Archaea twice.
# 12) g=[(1,3),(2,5),(3,7),(4,9),(5,11)]
list_plot(g)
# 13) m=[(1,10),(2,7),(3,15),(4,25),(5,3)] list_plot(m)
# 14) Africa=[(62,20),(81,34),(75,18),(90,25),(67,31)]
list_plot(Africa, axes_labels=["hippo", "crocodiles"], color="red")
# 15) days=[(1/24,100),(2/24,200),(3/24,400),(4/24,800),(5/24,1600)] list_plot(days, axes_labels=["days","bacteria"], color= "purple")
# 16) wt5_time = [0,0.25,0.5,0.75,1,1.25,1.5,1.75,2,2.25,2.5,2.75,3,3.25,3.5,3.75,4,4.25,4.5,4.75,5,5.25,5.5,5.75,6,6.25,6.5,6.75,7,7.25,7.5,7.75,8,8.25,8.5,8.75,9,9.25,9.5,9.75,10,10.25,10.5,10.75,11,11.25,11.5,11.75,12,12.25,12.5,12.75,13,13.25,13.5,13.75,14,14.25,14.5,14.75,15,15.25,15.5,15.75,16,16.25,16.5,16.75,17,17.25,17.5,17.75,18,18.25,18.5,18.75,19,19.25,19.5,19.75,20,20.25,20.5,20.75,21,21.25,21.5,21.75,22,22.25,22.5,22.75,23,23.25,23.5,23.75,24,24.25,24.5,24.75,25,25.25,25.5,25.75,26,26.25,26.5,26.75,27,27.25,27.5,27.75,28,28.25,28.5,28.75,29,29.25,29.5,29.75,30,30.25,30.5,30.75,31,31.25,31.5,31.75,32,32.25,32.5,32.75,33,33.25,33.5,33.75,34,34.25,34.5,34.75,35,35.25,35.5,35.75,36,36.25,36.5,36.75,37,37.25,37.5,37.75,38,38.25,38.5,38.75,39,39.25,39.5,39.75,40,40.25,40.5,40.75,41,41.25,41.5,41.75,42,42.25,42.5,42.75,43,43.25,43.5,43.75,44,44.25,44.5,44.75,45,45.25,45.5,45.75,46,46.25,46.5,46.75,47,47.25,47.5,47.75,48,48.25,48.5,48.75,49,49.25,49.5,49.75,50,50.25,50.5,50.75,51,51.25,51.5,51.75,52,52.25,52.5,52.75,53,53.25,53.5,53.75,54,54.25,54.5,54.75,55,55.25,55.5,55.75,56,56.25,56.5,56.75,57,57.25,57.5,57.75,58,58.25,58.5,58.75,59,59.25,59.5,59.75,60,60.25,60.5,60.75,61,61.25,61.5,61.75,62,62.25,62.5,62.75,63,63.25,63.5,63.75,64,64.25,64.5,64.75,65,65.25,65.5,65.75,66,66.25,66.5,66.75,67,67.25,67.5,67.75,68,68.25,68.5,68.75,69,69.25,69.5,69.75,70,70.25,70.5,70.75,71,71.25,71.5,71.75,72] wt5_temp = [35.77,37.23,37.32,36.75,36.09,35.68,35.46,35.35,35.3,35.21,35.21,35.25,35.4,35.92,36.52,36.56,36.07,35.6,35.39,35.27,35.09,34.91,34.85,34.81,34.78,34.85,34.88,34.96,35.05,34.96,34.8,34.76,34.73,34.74,35.18,35.91,36.31,36.39,36.12,35.59,35.27,35.17,35,34.69,34.53,34.85,35.49,35.98,35.89,35.34,35,35.37,36.25,36.62,36.51,36.77,37.32,37.76,37.95,38.01,38.03,38.05,38.02,37.95,37.93,37.88,37.69,37.53,37.51,37.56,37.61,37.6,37.6,37.65,37.61,37.51,37.14,36.4,35.72,35.44,35.36,35.27,35.32,35.65,36.2,36.61,36.96,37.33,37.62,37.8,37.86,37.84,37.82,37.81,37.75,37.68,37.63,37.52,37.3,36.82,36.13,35.68,35.52,35.57,35.66,35.62,35.42,35.28,35.64,36.13,36.01,35.61,35.37,35.29,35.2,35.15,35.18,35.18,35.07,35.02,35.05,35,35.02,35.1,35.02,35.08,35.49,35.89,35.78,35.38,35.11,34.96,34.97,35.09,35.07,34.85,34.69,34.99,35.45,35.38,35.02,34.81,34.83,35.34,36.18,36.83,37.14,37.06,36.5,35.94,36.06,36.65,37.23,37.66,37.86,37.84,37.73,37.68,37.67,37.63,37.48,37.3,37.45,37.7,37.78,37.8,37.78,37.71,37.68,37.75,37.75,37.69,37.6,37.48,36.91,36.01,35.3,35.09,35.12,35.21,35.41,35.84,36.59,37.13,37.42,37.64,37.71,37.77,37.91,37.96,37.92,37.87,37.76,37.59,37.27,36.75,36.08,35.53,35.23,35.05,34.95,35.06,35.26,35.35,35.39,35.26,35.13,35.37,36.06,36.48,36.11,35.6,35.31,35.09,34.94,34.96,34.97,34.89,34.88,34.96,35.07,34.99,34.77,34.62,34.67,34.85,35.08,35.5,35.63,35.25,34.9,34.8,34.81,34.85,34.87,34.84,34.92,35.35,36.03,36.64,37.08,37.23,36.85,36.07,35.64,35.75,35.89,36.23,36.96,37.56,37.87,37.97,37.98,37.93,37.81,37.65,37.58,37.62,37.49,36.99,36.27,35.89,36.29,37.03,37.51,37.71,37.77,37.76,37.74,37.79,37.85,37.8,37.78,37.68,37.45,37.31,37.2,36.81,36.15,35.69,35.62,35.64,35.5,35.35,35.4,35.93,36.72,37.25,37.47] wt5_heartrate = [331.47,410.62,463.32,480.56,473.31,459.9,452.98,454.75,461.56,470.87,484.46,505.84,534.55,562.83,578.89,574.82,552.25,520.8,491.4,470.81,460.3,457.16,456.96,456.11,453.75,451.48,451.06,452.29,453.44,453.55,454.49,461.06,478.03,505.51,536.27,558.56,563.27,549.66,525.12,499.9,481.87,475.01,480.79,498.93,525.28,549.9,560.69,552.6,533.76,520.3,523.28,540.41,560.34,573.63,578.49,578.02,574.9,570.02,564.09,558.59,554.81,552.92,552.29,552.27,552.39,552.24,551.57,550.63,550.19,550.88,552.73,555.04,556.38,554.57,547.06,532.59,512.76,491.6,473.03,459.32,452.36,455.58,472.62,503.18,540.53,574.07,595.23,601.76,597.62,589.4,582.49,579.13,578.75,579.31,578.58,574.91,567.41,556.08,541.99,527.21,514.02,503.74,496.21,490.82,488.54,492.6,505.66,525.36,543.11,549.4,541.17,523.96,506.83,495.72,491.37,491.71,494.49,497.69,498.8,495.44,487.4,478.19,473.99,480.22,497.57,520.13,537.52,540.95,529.09,508.91,490.2,479.05,476.1,479.64,488.66,501.97,515.35,521.91,517.48,506.06,498.71,505.08,525.26,549.53,565.84,568.35,560.79,553.23,554.81,567.03,582.81,592.37,590.95,581.33,569.71,560.1,552.83,546.82,542.14,540.11,541.58,545.37,548.68,549.15,546.78,543.85,543.01,545.34,549.85,554.01,554.52,548.03,532.35,508.52,481.79,459.69,448.17,449.67,464.37,491.41,526.74,561.1,583.36,587.92,578.53,564.48,553.59,548.63,548.51,551.01,554.27,556.99,557.78,554.81,546.51,532.93,516.34,499.85,485.46,473.6,464.31,458.29,456.62,460.16,469.8,486.63,509.82,533.63,548.04,545.19,526.28,501.47,481.99,472.29,469.38,467.99,465.25,461.21,457.09,454.15,453.41,455.56,461.25,471.6,487.59,507.33,524.65,532.4,528.34,516.93,504.55,494.12,485.64,481.11,486.37,506.26,538.25,571.75,593.88,596.72,580.97,555.18,532.03,522.91,532.44,556.03,582.79,602.15,609.44,606.79,599.74,593.11,588.75,585.99,583.12,578.26,569.53,556.26,541.45,532.31,535.95,552.76,574.56,590.46,594.96,590.47,583.31,578.29,576.74,577.61,579.03,579.39,577.66,573.25,565.19,551.64,530.99,504.17,475.89,452.9,440.63,441.7,457.24,487.39,528.77,572.1,605.2,619.96,616.62]
temp_list=zip(wt5_time, wt5_temp)
list_plot(temp_list, axes_labels=["time", "temp"], plotjoined=True, color= "turquoise")
list_plot?
File: /ext/sage/sage-8.8_1804/local/lib/python2.7/site-packages/sage/misc/decorators.py Signature : list_plot(data, plotjoined=False, aspect_ratio='automatic', **kwds) Docstring : "list_plot" takes either a list of numbers, a list of tuples, a numpy array, or a dictionary and plots the corresponding points. If given a list of numbers (that is, not a list of tuples or lists), "list_plot" forms a list of tuples "(i, x_i)" where "i" goes from 0 to "len(data)-1" and "x_i" is the "i"-th data value, and puts points at those tuple values. "list_plot" will plot a list of complex numbers in the obvious way; any numbers for which "CC()" makes sense will work. "list_plot" also takes a list of tuples "(x_i, y_i)" where "x_i" and "y_i" are the "i"-th values representing the "x"- and "y"-values, respectively. If given a dictionary, "list_plot" interprets the keys as x-values and the values as y-values. The "plotjoined=True" option tells "list_plot" to plot a line joining all the data. For other keyword options that the "list_plot" function can take, refer to "plot()". It is possible to pass empty dictionaries, lists, or tuples to "list_plot". Doing so will plot nothing (returning an empty plot). EXAMPLES: sage: list_plot([i^2 for i in range(5)]) # long time Graphics object consisting of 1 graphics primitive Here are a bunch of random red points: sage: r = [(random(),random()) for _ in range(20)] sage: list_plot(r, color='red') Graphics object consisting of 1 graphics primitive This gives all the random points joined in a purple line: sage: list_plot(r, plotjoined=True, color='purple') Graphics object consisting of 1 graphics primitive You can provide a numpy array.: sage: import numpy sage: list_plot(numpy.arange(10)) Graphics object consisting of 1 graphics primitive sage: list_plot(numpy.array([[1,2], [2,3], [3,4]])) Graphics object consisting of 1 graphics primitive Plot a list of complex numbers: sage: list_plot([1, I, pi + I/2, CC(.25, .25)]) Graphics object consisting of 1 graphics primitive sage: list_plot([exp(I*theta) for theta in [0, .2..pi]]) Graphics object consisting of 1 graphics primitive Note that if your list of complex numbers are all actually real, they get plotted as real values, so this sage: list_plot([CDF(1), CDF(1/2), CDF(1/3)]) Graphics object consisting of 1 graphics primitive is the same as "list_plot([1, 1/2, 1/3])" -- it produces a plot of the points (0,1), (1,1/2), and (2,1/3). If you have separate lists of x values and y values which you want to plot against each other, use the "zip" command to make a single list whose entries are pairs of (x,y) values, and feed the result into "list_plot": sage: x_coords = [cos(t)^3 for t in srange(0, 2*pi, 0.02)] sage: y_coords = [sin(t)^3 for t in srange(0, 2*pi, 0.02)] sage: list_plot(list(zip(x_coords, y_coords))) Graphics object consisting of 1 graphics primitive If instead you try to pass the two lists as separate arguments, you will get an error message: sage: list_plot(x_coords, y_coords) Traceback (most recent call last): ... TypeError: The second argument 'plotjoined' should be boolean (True or False). If you meant to plot two lists 'x' and 'y' against each other, use 'list_plot(list(zip(x,y)))'. Dictionaries with numeric keys and values can be plotted: sage: list_plot({22: 3365, 27: 3295, 37: 3135, 42: 3020, 47: 2880, 52: 2735, 57: 2550}) Graphics object consisting of 1 graphics primitive Plotting in logarithmic scale is possible for 2D list plots. There are two different syntaxes available: sage: yl = [2**k for k in range(20)] sage: list_plot(yl, scale='semilogy') # long time # log axis on vertical Graphics object consisting of 1 graphics primitive sage: list_plot_semilogy(yl) # same Graphics object consisting of 1 graphics primitive Warning: If "plotjoined" is "False" then the axis that is in log scale must have all points strictly positive. For instance, the following plot will show no points in the figure since the points in the horizontal axis starts from (0,1). Further, matplotlib will display a user warning. sage: list_plot(yl, scale='loglog') # both axes are log doctest:warning ... Graphics object consisting of 1 graphics primitive Instead this will work. We drop the point (0,1).: sage: list_plot(list(zip(range(1,len(yl)), yl[1:])), scale='loglog') # long time Graphics object consisting of 1 graphics primitive We use "list_plot_loglog()" and plot in a different base.: sage: list_plot_loglog(list(zip(range(1,len(yl)), yl[1:])), base=2) # long time Graphics object consisting of 1 graphics primitive We can also change the scale of the axes in the graphics just before displaying: sage: G = list_plot(yl) # long time sage: G.show(scale=('semilogy', 2)) # long time
# 17) #number 15 is exponentially growing whereas number 16 is increasing and decreasing. Number 15 only has coordinates and number 16 shows a line without distinct coordinates, this is because for number 16 we said plot joined=true # ##### Where is problem 18? (-3 points)
# 19) print "one of my favorite drinks is coffee"
one of my favorite drinks is coffee
print "The Man On The Middle Floor is one of my favorite books"
The Man On The Middle Floor is one of my favorite books
print "Vienna is one of my favorite songs"
Vienna is one of my favorite songs
print "a cheeseburger is one of my favorite foods"
a cheeseburger is one of my favorite foods
print "water is one of my favorite beverages"
water is one of my favorite beverages
# 20) for name in "SHOUQ": print name ##### Good. -HK
S H O U Q
# 21) for val in [15, 27, 39, 84 ]: val^2
225 729 1521 7056
#22) mult3=[] for n in [1,2,3,4,5]: mult3.append(3*n) mult3
3 6 9 12 15
#23) num=[] for n in [0.1,0.2,0.3,0.4,0.5,0.6,0.7]: num.append(n^2) num
[0.0100000000000000] [0.0100000000000000, 0.0400000000000000] [0.0100000000000000, 0.0400000000000000, 0.0900000000000000] [0.0100000000000000, 0.0400000000000000, 0.0900000000000000, 0.160000000000000] [0.0100000000000000, 0.0400000000000000, 0.0900000000000000, 0.160000000000000, 0.250000000000000] [0.0100000000000000, 0.0400000000000000, 0.0900000000000000, 0.160000000000000, 0.250000000000000, 0.360000000000000] [0.0100000000000000, 0.0400000000000000, 0.0900000000000000, 0.160000000000000, 0.250000000000000, 0.360000000000000, 0.490000000000000]
numbers_=[0.0100000000000000,0.04000000000000000,0.09000000000000000,0.1600000000000000,0.2500000000000000,0.3600000000000000,0.4900000000000000] plot(numbers_)
#24) fun=[] for n in [0,1,2,3,4,5]: fun.append(n^2) fun
[0] [0, 1] [0, 1, 4] [0, 1, 4, 9] [0, 1, 4, 9, 16] [0, 1, 4, 9, 16, 25]
plot(func^2)
#25) wt5_time=[] for n in[0,0.25,0.5,0.75,1,1.25,1.5,1.75,2,2.25,2.5,2.75,3,3.25,3.5,3.75,4,4.25,4.5,4.75,5,5.25,5.5,5.75,6,6.25,6.5,6.75,7,7.25,7.5,7.75,8,8.25,8.5,8.75,9,9.25,9.5,9.75,10,10.25,10.5,10.75,11,11.25,11.5,11.75,12,12.25,12.5,12.75,13,13.25,13.5,13.75,14,14.25,14.5,14.75,15,15.25,15.5,15.75,16,16.25,16.5,16.75,17,17.25,17.5,17.75,18,18.25,18.5,18.75,19,19.25,19.5,19.75,20,20.25,20.5,20.75,21,21.25,21.5,21.75,22,22.25,22.5,22.75,23,23.25,23.5,23.75,24,24.25,24.5,24.75,25,25.25,25.5,25.75,26,26.25,26.5,26.75,27,27.25,27.5,27.75,28,28.25,28.5,28.75,29,29.25,29.5,29.75,30,30.25,30.5,30.75,31,31.25,31.5,31.75,32,32.25,32.5,32.75,33,33.25,33.5,33.75,34,34.25,34.5,34.75,35,35.25,35.5,35.75,36,36.25,36.5,36.75,37,37.25,37.5,37.75,38,38.25,38.5,38.75,39,39.25,39.5,39.75,40,40.25,40.5,40.75,41,41.25,41.5,41.75,42,42.25,42.5,42.75,43,43.25,43.5,43.75,44,44.25,44.5,44.75,45,45.25,45.5,45.75,46,46.25,46.5,46.75,47,47.25,47.5,47.75,48,48.25,48.5,48.75,49,49.25,49.5,49.75,50,50.25,50.5,50.75,51,51.25,51.5,51.75,52,52.25,52.5,52.75,53,53.25,53.5,53.75,54,54.25,54.5,54.75,55,55.25,55.5,55.75,56,56.25,56.5,56.75,57,57.25,57.5,57.75,58,58.25,58.5,58.75,59,59.25,59.5,59.75,60,60.25,60.5,60.75,61,61.25,61.5,61.75,62,62.25,62.5,62.75,63,63.25,63.5,63.75,64,64.25,64.5,64.75,65,65.25,65.5,65.75,66,66.25,66.5,66.75,67,67.25,67.5,67.75,68,68.25,68.5,68.75,69,69.25,69.5,69.75,70,70.25,70.5,70.75,71,71.25,71.5,71.75,72]: wt5_time.append(n*60) wt5_time
[0] [0, 15.0000000000000] [0, 15.0000000000000, 30.0000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000, 165.000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000, 165.000000000000, 180] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000, 165.000000000000, 180, 195.000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000, 165.000000000000, 180, 195.000000000000, 210.000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000, 165.000000000000, 180, 195.000000000000, 210.000000000000, 225.000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000, 165.000000000000, 180, 195.000000000000, 210.000000000000, 225.000000000000, 240] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000, 165.000000000000, 180, 195.000000000000, 210.000000000000, 225.000000000000, 240, 255.000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000, 165.000000000000, 180, 195.000000000000, 210.000000000000, 225.000000000000, 240, 255.000000000000, 270.000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000, 165.000000000000, 180, 195.000000000000, 210.000000000000, 225.000000000000, 240, 255.000000000000, 270.000000000000, 285.000000000000] [0, 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1650.00000000000, 1665.00000000000, 1680, 1695.00000000000, 1710.00000000000, 1725.00000000000, 1740, 1755.00000000000, 1770.00000000000, 1785.00000000000, 1800, 1815.00000000000, 1830.00000000000, 1845.00000000000, 1860, 1875.00000000000, 1890.00000000000, 1905.00000000000, 1920, 1935.00000000000, 1950.00000000000, 1965.00000000000, 1980, 1995.00000000000, 2010.00000000000, 2025.00000000000, 2040, 2055.00000000000, 2070.00000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000, 165.000000000000, 180, 195.000000000000, 210.000000000000, 225.000000000000, 240, 255.000000000000, 270.000000000000, 285.000000000000, 300, 315.000000000000, 330.000000000000, 345.000000000000, 360, 375.000000000000, 390.000000000000, 405.000000000000, 420, 435.000000000000, 450.000000000000, 465.000000000000, 480, 495.000000000000, 510.000000000000, 525.000000000000, 540, 555.000000000000, 570.000000000000, 585.000000000000, 600, 615.000000000000, 630.000000000000, 645.000000000000, 660, 675.000000000000, 690.000000000000, 705.000000000000, 720, 735.000000000000, 750.000000000000, 765.000000000000, 780, 795.000000000000, 810.000000000000, 825.000000000000, 840, 855.000000000000, 870.000000000000, 885.000000000000, 900, 915.000000000000, 930.000000000000, 945.000000000000, 960, 975.000000000000, 990.000000000000, 1005.00000000000, 1020, 1035.00000000000, 1050.00000000000, 1065.00000000000, 1080, 1095.00000000000, 1110.00000000000, 1125.00000000000, 1140, 1155.00000000000, 1170.00000000000, 1185.00000000000, 1200, 1215.00000000000, 1230.00000000000, 1245.00000000000, 1260, 1275.00000000000, 1290.00000000000, 1305.00000000000, 1320, 1335.00000000000, 1350.00000000000, 1365.00000000000, 1380, 1395.00000000000, 1410.00000000000, 1425.00000000000, 1440, 1455.00000000000, 1470.00000000000, 1485.00000000000, 1500, 1515.00000000000, 1530.00000000000, 1545.00000000000, 1560, 1575.00000000000, 1590.00000000000, 1605.00000000000, 1620, 1635.00000000000, 1650.00000000000, 1665.00000000000, 1680, 1695.00000000000, 1710.00000000000, 1725.00000000000, 1740, 1755.00000000000, 1770.00000000000, 1785.00000000000, 1800, 1815.00000000000, 1830.00000000000, 1845.00000000000, 1860, 1875.00000000000, 1890.00000000000, 1905.00000000000, 1920, 1935.00000000000, 1950.00000000000, 1965.00000000000, 1980, 1995.00000000000, 2010.00000000000, 2025.00000000000, 2040, 2055.00000000000, 2070.00000000000, 2085.00000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000, 165.000000000000, 180, 195.000000000000, 210.000000000000, 225.000000000000, 240, 255.000000000000, 270.000000000000, 285.000000000000, 300, 315.000000000000, 330.000000000000, 345.000000000000, 360, 375.000000000000, 390.000000000000, 405.000000000000, 420, 435.000000000000, 450.000000000000, 465.000000000000, 480, 495.000000000000, 510.000000000000, 525.000000000000, 540, 555.000000000000, 570.000000000000, 585.000000000000, 600, 615.000000000000, 630.000000000000, 645.000000000000, 660, 675.000000000000, 690.000000000000, 705.000000000000, 720, 735.000000000000, 750.000000000000, 765.000000000000, 780, 795.000000000000, 810.000000000000, 825.000000000000, 840, 855.000000000000, 870.000000000000, 885.000000000000, 900, 915.000000000000, 930.000000000000, 945.000000000000, 960, 975.000000000000, 990.000000000000, 1005.00000000000, 1020, 1035.00000000000, 1050.00000000000, 1065.00000000000, 1080, 1095.00000000000, 1110.00000000000, 1125.00000000000, 1140, 1155.00000000000, 1170.00000000000, 1185.00000000000, 1200, 1215.00000000000, 1230.00000000000, 1245.00000000000, 1260, 1275.00000000000, 1290.00000000000, 1305.00000000000, 1320, 1335.00000000000, 1350.00000000000, 1365.00000000000, 1380, 1395.00000000000, 1410.00000000000, 1425.00000000000, 1440, 1455.00000000000, 1470.00000000000, 1485.00000000000, 1500, 1515.00000000000, 1530.00000000000, 1545.00000000000, 1560, 1575.00000000000, 1590.00000000000, 1605.00000000000, 1620, 1635.00000000000, 1650.00000000000, 1665.00000000000, 1680, 1695.00000000000, 1710.00000000000, 1725.00000000000, 1740, 1755.00000000000, 1770.00000000000, 1785.00000000000, 1800, 1815.00000000000, 1830.00000000000, 1845.00000000000, 1860, 1875.00000000000, 1890.00000000000, 1905.00000000000, 1920, 1935.00000000000, 1950.00000000000, 1965.00000000000, 1980, 1995.00000000000, 2010.00000000000, 2025.00000000000, 2040, 2055.00000000000, 2070.00000000000, 2085.00000000000, 2100]
Output too long: 150354 -- MAX_OUTPUT (=150000) exceeded (type 'smc?' to learn how to raise this limit): attempting to terminate...
#26) wt5_temp=[] for n in [35.77,37.23,37.32,36.75,36.09,35.68,35.46,35.35,35.3,35.21,35.21,35.25,35.4,35.92,36.52,36.56,36.07,35.6,35.39,35.27,35.09,34.91,34.85,34.81,34.78,34.85,34.88,34.96,35.05,34.96,34.8,34.76,34.73,34.74,35.18,35.91,36.31,36.39,36.12,35.59,35.27,35.17,35,34.69,34.53,34.85,35.49,35.98,35.89,35.34,35,35.37,36.25,36.62,36.51,36.77,37.32,37.76,37.95,38.01,38.03,38.05,38.02,37.95,37.93,37.88,37.69,37.53,37.51,37.56,37.61,37.6,37.6,37.65,37.61,37.51,37.14,36.4,35.72,35.44,35.36,35.27,35.32,35.65,36.2,36.61,36.96,37.33,37.62,37.8,37.86,37.84,37.82,37.81,37.75,37.68,37.63,37.52,37.3,36.82,36.13,35.68,35.52,35.57,35.66,35.62,35.42,35.28,35.64,36.13,36.01,35.61,35.37,35.29,35.2,35.15,35.18,35.18,35.07,35.02,35.05,35,35.02,35.1,35.02,35.08,35.49,35.89,35.78,35.38,35.11,34.96,34.97,35.09,35.07,34.85,34.69,34.99,35.45,35.38,35.02,34.81,34.83,35.34,36.18,36.83,37.14,37.06,36.5,35.94,36.06,36.65,37.23,37.66,37.86,37.84,37.73,37.68,37.67,37.63,37.48,37.3,37.45,37.7,37.78,37.8,37.78,37.71,37.68,37.75,37.75,37.69,37.6,37.48,36.91,36.01,35.3,35.09,35.12,35.21,35.41,35.84,36.59,37.13,37.42,37.64,37.71,37.77,37.91,37.96,37.92,37.87,37.76,37.59,37.27,36.75,36.08,35.53,35.23,35.05,34.95,35.06,35.26,35.35,35.39,35.26,35.13,35.37,36.06,36.48,36.11,35.6,35.31,35.09,34.94,34.96,34.97,34.89,34.88,34.96,35.07,34.99,34.77,34.62,34.67,34.85,35.08,35.5,35.63,35.25,34.9,34.8,34.81,34.85,34.87,34.84,34.92,35.35,36.03,36.64,37.08,37.23,36.85,36.07,35.64,35.75,35.89,36.23,36.96,37.56,37.87,37.97,37.98,37.93,37.81,37.65,37.58,37.62,37.49,36.99,36.27,35.89,36.29,37.03,37.51,37.71,37.77,37.76,37.74,37.79,37.85,37.8,37.78,37.68,37.45,37.31,37.2,36.81,36.15,35.69,35.62,35.64,35.5,35.35,35.4,35.93,36.72,37.25,37.47]: wt5_temp.append(n*9/5 +32) wt5_temp
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94.4420000000000, 94.1540000000000, 94.7300000000000, 95.8820000000000, 96.7640000000000, 96.6020000000000, 95.6120000000000, 95, 95.6660000000000, 97.2500000000000, 97.9160000000000, 97.7180000000000, 98.1860000000000, 99.1760000000000, 99.9680000000000, 100.310000000000, 100.418000000000, 100.454000000000, 100.490000000000, 100.436000000000, 100.310000000000, 100.274000000000, 100.184000000000, 99.8420000000000, 99.5540000000000, 99.5180000000000, 99.6080000000000, 99.6980000000000, 99.6800000000000, 99.6800000000000, 99.7700000000000, 99.6980000000000, 99.5180000000000, 98.8520000000000, 97.5200000000000, 96.2960000000000, 95.7920000000000, 95.6480000000000, 95.4860000000000, 95.5760000000000, 96.1700000000000, 97.1600000000000, 97.8980000000000, 98.5280000000000, 99.1940000000000, 99.7160000000000, 100.040000000000, 100.148000000000, 100.112000000000, 100.076000000000, 100.058000000000, 99.9500000000000, 99.8240000000000, 99.7340000000000, 99.5360000000000, 99.1400000000000, 98.2760000000000, 97.0340000000000, 96.2240000000000, 95.9360000000000, 96.0260000000000, 96.1880000000000, 96.1160000000000, 95.7560000000000, 95.5040000000000, 96.1520000000000, 97.0340000000000, 96.8180000000000, 96.0980000000000, 95.6660000000000, 95.5220000000000, 95.3600000000000, 95.2700000000000, 95.3240000000000, 95.3240000000000, 95.1260000000000, 95.0360000000000, 95.0900000000000, 95, 95.0360000000000, 95.1800000000000, 95.0360000000000, 95.1440000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000, 95.5400000000000, 95.3780000000000, 95.3780000000000, 95.4500000000000, 95.7200000000000, 96.6560000000000, 97.7360000000000, 97.8080000000000, 96.9260000000000, 96.0800000000000, 95.7020000000000, 95.4860000000000, 95.1620000000000, 94.8380000000000, 94.7300000000000, 94.6580000000000, 94.6040000000000, 94.7300000000000, 94.7840000000000, 94.9280000000000, 95.0900000000000, 94.9280000000000, 94.6400000000000, 94.5680000000000, 94.5140000000000, 94.5320000000000, 95.3240000000000, 96.6380000000000, 97.3580000000000, 97.5020000000000, 97.0160000000000, 96.0620000000000, 95.4860000000000, 95.3060000000000, 95, 94.4420000000000, 94.1540000000000, 94.7300000000000, 95.8820000000000, 96.7640000000000, 96.6020000000000, 95.6120000000000, 95, 95.6660000000000, 97.2500000000000, 97.9160000000000, 97.7180000000000, 98.1860000000000, 99.1760000000000, 99.9680000000000, 100.310000000000, 100.418000000000, 100.454000000000, 100.490000000000, 100.436000000000, 100.310000000000, 100.274000000000, 100.184000000000, 99.8420000000000, 99.5540000000000, 99.5180000000000, 99.6080000000000, 99.6980000000000, 99.6800000000000, 99.6800000000000, 99.7700000000000, 99.6980000000000, 99.5180000000000, 98.8520000000000, 97.5200000000000, 96.2960000000000, 95.7920000000000, 95.6480000000000, 95.4860000000000, 95.5760000000000, 96.1700000000000, 97.1600000000000, 97.8980000000000, 98.5280000000000, 99.1940000000000, 99.7160000000000, 100.040000000000, 100.148000000000, 100.112000000000, 100.076000000000, 100.058000000000, 99.9500000000000, 99.8240000000000, 99.7340000000000, 99.5360000000000, 99.1400000000000, 98.2760000000000, 97.0340000000000, 96.2240000000000, 95.9360000000000, 96.0260000000000, 96.1880000000000, 96.1160000000000, 95.7560000000000, 95.5040000000000, 96.1520000000000, 97.0340000000000, 96.8180000000000, 96.0980000000000, 95.6660000000000, 95.5220000000000, 95.3600000000000, 95.2700000000000, 95.3240000000000, 95.3240000000000, 95.1260000000000, 95.0360000000000, 95.0900000000000, 95, 95.0360000000000, 95.1800000000000, 95.0360000000000, 95.1440000000000, 95.8820000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000, 95.5400000000000, 95.3780000000000, 95.3780000000000, 95.4500000000000, 95.7200000000000, 96.6560000000000, 97.7360000000000, 97.8080000000000, 96.9260000000000, 96.0800000000000, 95.7020000000000, 95.4860000000000, 95.1620000000000, 94.8380000000000, 94.7300000000000, 94.6580000000000, 94.6040000000000, 94.7300000000000, 94.7840000000000, 94.9280000000000, 95.0900000000000, 94.9280000000000, 94.6400000000000, 94.5680000000000, 94.5140000000000, 94.5320000000000, 95.3240000000000, 96.6380000000000, 97.3580000000000, 97.5020000000000, 97.0160000000000, 96.0620000000000, 95.4860000000000, 95.3060000000000, 95, 94.4420000000000, 94.1540000000000, 94.7300000000000, 95.8820000000000, 96.7640000000000, 96.6020000000000, 95.6120000000000, 95, 95.6660000000000, 97.2500000000000, 97.9160000000000, 97.7180000000000, 98.1860000000000, 99.1760000000000, 99.9680000000000, 100.310000000000, 100.418000000000, 100.454000000000, 100.490000000000, 100.436000000000, 100.310000000000, 100.274000000000, 100.184000000000, 99.8420000000000, 99.5540000000000, 99.5180000000000, 99.6080000000000, 99.6980000000000, 99.6800000000000, 99.6800000000000, 99.7700000000000, 99.6980000000000, 99.5180000000000, 98.8520000000000, 97.5200000000000, 96.2960000000000, 95.7920000000000, 95.6480000000000, 95.4860000000000, 95.5760000000000, 96.1700000000000, 97.1600000000000, 97.8980000000000, 98.5280000000000, 99.1940000000000, 99.7160000000000, 100.040000000000, 100.148000000000, 100.112000000000, 100.076000000000, 100.058000000000, 99.9500000000000, 99.8240000000000, 99.7340000000000, 99.5360000000000, 99.1400000000000, 98.2760000000000, 97.0340000000000, 96.2240000000000, 95.9360000000000, 96.0260000000000, 96.1880000000000, 96.1160000000000, 95.7560000000000, 95.5040000000000, 96.1520000000000, 97.0340000000000, 96.8180000000000, 96.0980000000000, 95.6660000000000, 95.5220000000000, 95.3600000000000, 95.2700000000000, 95.3240000000000, 95.3240000000000, 95.1260000000000, 95.0360000000000, 95.0900000000000, 95, 95.0360000000000, 95.1800000000000, 95.0360000000000, 95.1440000000000, 95.8820000000000, 96.6020000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000, 95.5400000000000, 95.3780000000000, 95.3780000000000, 95.4500000000000, 95.7200000000000, 96.6560000000000, 97.7360000000000, 97.8080000000000, 96.9260000000000, 96.0800000000000, 95.7020000000000, 95.4860000000000, 95.1620000000000, 94.8380000000000, 94.7300000000000, 94.6580000000000, 94.6040000000000, 94.7300000000000, 94.7840000000000, 94.9280000000000, 95.0900000000000, 94.9280000000000, 94.6400000000000, 94.5680000000000, 94.5140000000000, 94.5320000000000, 95.3240000000000, 96.6380000000000, 97.3580000000000, 97.5020000000000, 97.0160000000000, 96.0620000000000, 95.4860000000000, 95.3060000000000, 95, 94.4420000000000, 94.1540000000000, 94.7300000000000, 95.8820000000000, 96.7640000000000, 96.6020000000000, 95.6120000000000, 95, 95.6660000000000, 97.2500000000000, 97.9160000000000, 97.7180000000000, 98.1860000000000, 99.1760000000000, 99.9680000000000, 100.310000000000, 100.418000000000, 100.454000000000, 100.490000000000, 100.436000000000, 100.310000000000, 100.274000000000, 100.184000000000, 99.8420000000000, 99.5540000000000, 99.5180000000000, 99.6080000000000, 99.6980000000000, 99.6800000000000, 99.6800000000000, 99.7700000000000, 99.6980000000000, 99.5180000000000, 98.8520000000000, 97.5200000000000, 96.2960000000000, 95.7920000000000, 95.6480000000000, 95.4860000000000, 95.5760000000000, 96.1700000000000, 97.1600000000000, 97.8980000000000, 98.5280000000000, 99.1940000000000, 99.7160000000000, 100.040000000000, 100.148000000000, 100.112000000000, 100.076000000000, 100.058000000000, 99.9500000000000, 99.8240000000000, 99.7340000000000, 99.5360000000000, 99.1400000000000, 98.2760000000000, 97.0340000000000, 96.2240000000000, 95.9360000000000, 96.0260000000000, 96.1880000000000, 96.1160000000000, 95.7560000000000, 95.5040000000000, 96.1520000000000, 97.0340000000000, 96.8180000000000, 96.0980000000000, 95.6660000000000, 95.5220000000000, 95.3600000000000, 95.2700000000000, 95.3240000000000, 95.3240000000000, 95.1260000000000, 95.0360000000000, 95.0900000000000, 95, 95.0360000000000, 95.1800000000000, 95.0360000000000, 95.1440000000000, 95.8820000000000, 96.6020000000000, 96.4040000000000]
Output too long: 151664 -- MAX_OUTPUT (=150000) exceeded (type 'smc?' to learn how to raise this limit): attempting to terminate...
#27) wt5_time2=[0] [0, 15.0000000000000] [0, 15.0000000000000, 30.0000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000, 165.000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000, 165.000000000000, 180] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000, 165.000000000000, 180, 195.000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000, 165.000000000000, 180, 195.000000000000, 210.000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000, 165.000000000000, 180, 195.000000000000, 210.000000000000, 225.000000000000] wt5_temp2=[96.3860000000000] [96.3860000000000, 99.0140000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000, 95.5400000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000, 95.5400000000000, 95.3780000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000, 95.5400000000000, 95.3780000000000, 95.3780000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000, 95.5400000000000, 95.3780000000000, 95.3780000000000, 95.4500000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000, 95.5400000000000, 95.3780000000000, 95.3780000000000, 95.4500000000000, 95.7200000000000] temp_list=zip(wt5_time2, wt5_temp2) list_plot(temp_list, axes_labels=["time","temperture"],plotjoined=True,color="green")
[0, 15.0000000000000] [0, 15.0000000000000, 30.0000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000, 165.000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000, 165.000000000000, 180] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000, 165.000000000000, 180, 195.000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000, 165.000000000000, 180, 195.000000000000, 210.000000000000] [0, 15.0000000000000, 30.0000000000000, 45.0000000000000, 60, 75.0000000000000, 90.0000000000000, 105.000000000000, 120, 135.000000000000, 150.000000000000, 165.000000000000, 180, 195.000000000000, 210.000000000000, 225.000000000000] [96.3860000000000, 99.0140000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000, 95.5400000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000, 95.5400000000000, 95.3780000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000, 95.5400000000000, 95.3780000000000, 95.3780000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000, 95.5400000000000, 95.3780000000000, 95.3780000000000, 95.4500000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000, 95.5400000000000, 95.3780000000000, 95.3780000000000, 95.4500000000000, 95.7200000000000]
#28) wt5_temp2=[96.3860000000000] [96.3860000000000, 99.0140000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000, 95.5400000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000, 95.5400000000000, 95.3780000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000, 95.5400000000000, 95.3780000000000, 95.3780000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000, 95.5400000000000, 95.3780000000000, 95.3780000000000, 95.4500000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000, 95.5400000000000, 95.3780000000000, 95.3780000000000, 95.4500000000000, 95.7200000000000] wt5_heartrate=[331.47,410.62,463.32,480.56,473.31,459.9,452.98,454.75,461.56,470.87,484.46,505.84,534.55,562.83,578.89,574.82,552.25,520.8,491.4,470.81,460.3,457.16,456.96,456.11,453.75,451.48,451.06,452.29,453.44,453.55,454.49,461.06,478.03,505.51,536.27,558.56,563.27,549.66,525.12,499.9,481.87,475.01,480.79,498.93,525.28,549.9,560.69,552.6,533.76,520.3,523.28,540.41,560.34,573.63,578.49,578.02,574.9,570.02,564.09,558.59,554.81,552.92,552.29,552.27,552.39,552.24,551.57,550.63,550.19,550.88,552.73,555.04,556.38,554.57,547.06,532.59,512.76,491.6,473.03,459.32,452.36,455.58,472.62,503.18,540.53,574.07,595.23,601.76,597.62,589.4,582.49,579.13,578.75,579.31,578.58,574.91,567.41,556.08,541.99,527.21,514.02,503.74,496.21,490.82,488.54,492.6,505.66,525.36,543.11,549.4,541.17,523.96,506.83,495.72,491.37,491.71,494.49,497.69,498.8,495.44,487.4,478.19,473.99,480.22,497.57,520.13,537.52,540.95,529.09,508.91,490.2,479.05,476.1,479.64,488.66,501.97,515.35,521.91,517.48,506.06,498.71,505.08,525.26,549.53,565.84,568.35,560.79,553.23,554.81,567.03,582.81,592.37,590.95,581.33,569.71,560.1,552.83,546.82,542.14,540.11,541.58,545.37,548.68,549.15,546.78,543.85,543.01,545.34,549.85,554.01,554.52,548.03,532.35,508.52,481.79,459.69,448.17,449.67,464.37,491.41,526.74,561.1,583.36,587.92,578.53,564.48,553.59,548.63,548.51,551.01,554.27,556.99,557.78,554.81,546.51,532.93,516.34,499.85,485.46,473.6,464.31,458.29,456.62,460.16,469.8,486.63,509.82,533.63,548.04,545.19,526.28,501.47,481.99,472.29,469.38,467.99,465.25,461.21,457.09,454.15,453.41,455.56,461.25,471.6,487.59,507.33,524.65,532.4,528.34,516.93,504.55,494.12,485.64,481.11,486.37,506.26,538.25,571.75,593.88,596.72,580.97,555.18,532.03,522.91,532.44,556.03,582.79,602.15,609.44,606.79,599.74,593.11,588.75,585.99,583.12,578.26,569.53,556.26,541.45,532.31,535.95,552.76,574.56,590.46,594.96,590.47,583.31,578.29,576.74,577.61,579.03,579.39,577.66,573.25,565.19,551.64,530.99,504.17,475.89,452.9,440.63,441.7,457.24,487.39,528.77,572.1,605.2,619.96,616.62] temp_list=zip(wt5_temp2,wt5_heartrate) list_plot(temp_list,axes_labels=["temperature","heartrate"],plotjoined=True,color="yellow")
[96.3860000000000, 99.0140000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000, 95.5400000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000, 95.5400000000000, 95.3780000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000, 95.5400000000000, 95.3780000000000, 95.3780000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000, 95.5400000000000, 95.3780000000000, 95.3780000000000, 95.4500000000000] [96.3860000000000, 99.0140000000000, 99.1760000000000, 98.1500000000000, 96.9620000000000, 96.2240000000000, 95.8280000000000, 95.6300000000000, 95.5400000000000, 95.3780000000000, 95.3780000000000, 95.4500000000000, 95.7200000000000]
#29) plots = [] #Set up empty list to hold plots slopes = [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5] #Make a list ofslopes for m in slopes: #For each m in slope, create plot, add to list p=plot(m*x, (x,-10,10), ymin=-50, ymax=50, color="green") plots.append(p) a=animate(plots) #Create the animation show(a) #Necessary to display the animatio
#30) plots = [] #Set up empty list to hold plots slopes = [-3, -2.5, -2, -1.5, -1, -.5, 0, .5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5] #Make a list ofslopes for m in slopes: #For each m in slope, create plot, add to list p=plot(m*x, (x,-10,10), ymin=-50, ymax=50, color="green") plots.append(p) a=animate(plots) #Create the animation show(a) #Necessary to display the animation
#31) plots = [] #Set up empty list to hold plots slopes = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] #Make a list ofslopes for m in slopes: #For each m in slope, create plot, add to list p=plot(m*x, (x,-10,10), ymin=-5, ymax=5, color="green") plots.append(p) a=animate(plots) #Create the animation show(a) #Necessary to display the animation ##### Several things are going wrong here. The reason you are getting so many plots instead of just one is that you are animating and showing the plot in the loop (these lines are indented when they shouldn't be).That means that every time you run through the loop, the graph shows up again. Moreover, you are not changing the y-intercept in the loop. Exercise 31 asks you to keep the slope at 1 while changing the y-intercept. It should look like: plots = [] #Set up empty list to hold plots y_ints = [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5] #Make a list of y-intercepts for b in y_ints: #For each b in y_ints, create plot, add to list p=plot(1*x+b, (x,-10,10), ymin=-50, ymax=50, color="green") plots.append(p) a=animate(plots) #Create the animation show(a) #Necessary to display the animation ##### (-2 points) -HK