st-scripts: comparison multiple-plots.rst

equal deleted inserted replaced

-:8835b2c071e6
+:2f30ecfd6007
 add legends to each plot to indicate what each plot represents. We
 will also learn how to switch between the plots and create multiple
 plots with different regular axes which are also called as subplots.
 .. #[Nishanth]: See diff - edited a grammatical mistake
+.. #[Madhu: Done]
 {{{ Shift to terminal and start ipython -pylab }}}
 To begin with let us start ipython with pylab, by typing::
 .. #[Nishanth]: pre requisite for this LO is basic plotting which
 covers linspace and plot. So you may not need to
 specify all that again. But not a problem if it is
 there also.
+.. #[Madhu: Since I thought the LOs are disconnected, I thought it is
+better to give a very short intro to it]
 Now let us draw a plot simple sine plot using these points::
 plot(x, sin(x))
 Oh! wait! Is that a nice sine plot? Does a sine plot actually look
 like that? We know that a sine plot is a smooth curve. Is it not? What
 really caused this?
 .. #[Nishanth]: See diff
+.. #[Madhu: Done]
 {{{ pause for a while }}}
 A small investigation on linspace tells us that we chose too few
 points in a large interval between 0 and 50 for the curve to be
-smooth. So now let us use linspace again to get 500 points between 0
+smooth. This should also indicate that the plot command actually plots
-and 100 and draw the sine plot
+the set of points given by x and sin(x) and it doesn't plot the
+analytical function itself i.e. it plots the points given by
+Analytical functions. So now let us use linspace again to get 500
+points between 0 and 100 and draw the sine plot
 .. #[Nishanth]: Here specify that when we do plot(x, sin(x)
 it is actually plotting two sets of points
 and not analytical functions. Hence the sharp
 curve.
+.. #[Madhu: Incorporated]
 {{{ Switch to ipython andtype }}} ::
 y = linspace(0, 50, 500)
 plot(y, sin(y))
 Now we see what we remember as a sine plot. A smooth curve. If we
 carefully notice we also have two plots now one overlaid upon
 another. In pylab, by default all the plots are overlaid.
-We now know how to draw multiple plots but we would like to have more
+Since we have two plots now overlaid upon each other we would like to
-control over it. Like switch between them, perform some operations or
+have a way to indicate what each plot represents to distinguish
-labelling on them individually and so on. Let us see how to accomplish
+between them. This is accomplished using legends. Equivalently, the
-this. Before we move on, let us clear our screen.
+legend command does this for us
+{{{ Switch to ipython }}}::
+legend(['sin(x)', 'cos(x)'])
+.. #[Nishanth]: This legend may go up in the script. May be before
+introducing the figure command itself.
+.. #[Madhu: brought up]
+The legend command takes a single list of parameters where each
+parameter is the text indicating the plots in the order of their
+serial number.
+{{{ Switch to plot window }}}
+Now we can see the legends being displayed for the respective sine and
+cosine plots on the plot area.
+We have learnt quite a lot of things now, so let us take up an
+exercise problem.
+%% 1 %% Draw two plots overlaid upon each other, with the first plot
+being a parabola of the form y = 4(x ^ 2) and the second being a
+straight line of the form y = 2x + 3 in the interval -5 to 5. Use
+colors to differentiate between the plots and use legends to
+indicate what each plot is doing.
+{{{ pause for a while and continue from paused state }}}
+We can obtain the two plots in different colors using the following
+commands::
+x = linspace(-5, 5, 100)
+plot(x, 4 * (x ^ 2), 'b')
+plot(x, (2 * x) + 3, 'g')
+Now we can use the legend command as::
+legend(['Parabola', 'Straight Line'])
+Or we can also just give the equations of the plot::
+legend(['y = 4(x ^ 2)', 'y = 2x + 3'])
+We now know how to draw multiple plots and use legends to indicate
+which plot represents what function, but we would like to have more
+control over the plots we draw. Like switch between them, perform some
+operations or labelling on them individually and so on. Let us see how
+to accomplish this. Before we move on, let us clear our screen.
 {{{ Switch to ipython }}}::
 clf()
 So clear the figure and plot cos and sin without
 introducing figure command. Then introduce legend
 and finish off the everything on legend.
 Then introduce figure command.
+.. #[Madhu: I have just moved up the text about legend command. I
+think that should take care of what you suggested. If there is
+some mistake with it, Punch please let me know in your next
+review.]
 {{{ Have both plot window and ipython side by side }}}
 The figure command takes an integer as an argument which is the serial
 number of the plot. This selects the corresponding plot. All the plot
 commands we run after this are applied to the selected plot. In this
 {{{ Have both plot window and ipython side by side }}}
 We also titled the our first plot as 'sin(y)' which we did not do for
 the second plot.
-Since we have two plots now overlaid upon each other we would like to
+Let us attempt another exercise problem
-have a way to indicate what each plot represents to distinguish
-between them. This is accomplished using legends. Equivalently, the
+%% 2 %% Draw a line of the form y = x as one figure and another line
-legend command does this for us
+of the form y = 2x + 3. Switch back to the first figure, annotate
+the x and y intercepts. Now switch to the second figure and
-{{{ Switch to ipython }}}::
+annotate its x and y intercepts. Save each of them.
-legend(['sin(x)', 'cos(x)'])
+{{{ Pause for a while and continue from the paused state }}}
-.. #[Nishanth]: This legend may go up in the script. May be before
+To solve this problem we should first create the first figure using
-introducing the figure command itself.
+the figure command. Before that, let us first run clf command to make
+sure all the previous plots are cleared::
-The legend command takes a single list of parameters where each
-parameter is the text indicating the plots in the order of their
+clf()
-serial number.
+figure(1)
+x = linspace(-5, 5, 100)
-{{{ Switch to plot window }}}
+plot(x, x)
-Now we can see the legends being displayed for the respective sine and
+Now we can use figure command to create second plotting area and plot
-cosine plots on the plot area.
+the figure::
+figure(2)
+plot(x, ((2 * x) + 3))
+Now to switch between the figures we can use figure command. So let us
+switch to figure 1. We are asked to annotate x and y intercepts of the
+figure 1 but since figure 1 passes through origin we will have to
+annotate the origin. We will annotate the intercepts for the second
+figure and save them as follows::
+figure(1)
+annotate('Origin', xy=(0.0, 0.0)
+figure(2)
+annotate('x-intercept', xy=(0, 3))
+annotate('y-intercept', xy=(0, -1.5))
+savefig('plot2.png')
+figure(1)
+savefig('plot1.png')
 At times we run into situations where we want to compare two plots and
 in such cases we want to draw both the plots in the same plotting
 area. The situation is such that the two plots have different regular
 axes which means we cannot draw overlaid plots. In such cases we can
 automatically erased. It is clear from the two subplots that both have
 different regular axes. For the cosine plot x-axis varies from 0 to
 100 and y-axis varies from 0 to 1 where as for the parabolic plot the
 x-axis varies from 0 to 10 and y-axis varies from 0 to 100
-.. #[Nishanth]: stress on the similarity between subplot and figure commands
+.. #[Nishanth]: stress on the similarity between subplot and figure
+commands
+.. #[Madhu: I think they are not really similar. Trying to bring in
+the similarity will confuse people I think.]
+%% 3 %% We know that the Pressure, Volume and Temperatures are held by
+the equation PV = nRT where nR is a constant. Let us assume nR = .01
+Joules/Kelvin and T = 200K. V can be in the range from 21cc to
+100cc. Draw two different plots as subplots, one being the Pressure
+versus Volume plot and the other being Pressure versus Temparature
+plot.
+{{{ Pause for a while and continue }}}
+To start with, we have been given the range of Volume using which we
+can define the variable V::
+V = linspace(21, 100, 500)
+Now we can create first subplot and draw Pressure versus Volume graph
+using this V. We know that nRT is a constant which is equal to 2.0
+since nR = 0.01 Joules/Kelvin and T = 200 Kelvin::
+subplot(2, 1, 1)
+plot(V, 2.0/V)
+Now we can create the second subplot and draw the Pressure versus
+Temparature plot as follows::
+subplot(2, 1, 2)
+plot(200, 2.0/V)
+Unfortunately we have an error now, telling x and y dimensions don't
+match. This is because our V contains a set of values as returned by
+linspace and hence 2.0/V which is the pressure also contains a set of
+values. But the first argument to the plot command is a single
+value. So to plot this data we need to create as many points as there
+are in Pressure or Volume data for Temperature too, all having the
+same value. This can be accomplished using::
+T = linspace(200, 200, 500)
+We now have 500 values in T each with the value 200 Kelvin. Plotting
+this data we get the required plot::
+plot(T, 2.0/V)
+It is left as a homework to label both X and Y axes for each of the
+two subplots.
 {{{ Show summary slide }}}
 .. #[Nishanth]: Exercises are missing in the script
 one exercise for overlaid plot and legend
 This brings us to the end of another session. In this tutorial session
 we learnt
 * How to draw multiple plots which are overlaid
 * the figure command
+* the legend command
 * how to switch between the plots and perform some operations on each
-of them like saving the plots
+of them like saving the plots and
-* the legend command and
 * creating and switching between subplots
 .. #[Nishanth]: legend command can be told right after overlaid plots
+.. #[Madhu: Incorporated]
 {{{ Show the "sponsored by FOSSEE" slide }}}
 This tutorial was created as a part of FOSSEE project, NME ICT, MHRD India

changeset 207	2f30ecfd6007
parent 184	a005328abdf0
child 210	bd7338e67289