I want to implement a solution that allows me to draw Kinetic.Line with the mouse. My problem is that when I copy-paste my code in a .html file, and although everything works okay in the fiddle, I get this error:
TypeError: line.getPoints(...)[1] is undefined
This is the code I wrote, inspired by some jsfiddles and questions found in SO : http://jsfiddle.net/pg4fm/ What am I doing wrong?
PS: I'm using two KineticJS libraries (v4.7.2 along with v5.0.1) because getPoints() method doesn't work in the v5.0.1. And I need the v5 for other purposes (other functions)
EDIT :
This fiddle now work http://jsfiddle.net/pg4fm/2/ But I still need the lines to be straight, just like in the first fiddle
From v5.0.0 KineticJS return points in other way (see docs):
line.getPoints()
>> [x1, y1, x2, y2]
So. It is array of numbers, not objects. Your updated demo.
Related
raw_df.loc[:,'full_size'] = raw_df.loc[:,:].apply( full_size,axis="columns",).copy()
is throwing the warning:
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
I thought/recalled that normally I can fix this by making sure everything is .loc'd properly, or making the the right hand side a copy(). But this line has been stubbornly throwing the warning regardless. Maybe I'm misunderstanding the warning, but I cannot see what I'm doing here that is potentially-dodgy.
The warning is legit since you're calling pandas.Series.copy on a series where in the same line you assign this one to another series.
I can't tell what's your needs but you can try this approach instead:
raw_df['full_size']= raw_df.apply(full_size, axis='columns')
ser_fullsize= raw_df.loc[:,'full_size'].copy() # or raw_df['full_size'].copy()
I have been using matplotlib.rc in my scripts to preprocess my plots. But recently I have realized that using matplotlib.rcParams is much easier before doing a quick plot interactively (e.g. via IPython). This got me into thinking what difference between the two is.
I searched the matplotlib documentation wherein no clear answer was provided in this regard. Moreover, when I issue type(matplotlib.rc), the interpreter says that it is a function. On the other hand, when I issue type(matplotlib.rcParams), I am told that it is a class object. These two answers are not at all helpful and hence I would appreciate some help differentiating the two.
Additionally, I would like to know which one to prefer over the other.
Thanks in advance.
P.S. I went through this question: What's the difference between matplotlib.rc and matplotlib.pyplot.rc? but the answers are specific to the difference between the matplotlib instance and the pyplot instance of the two types I am enquiring about and, hence, is also not that helpful.
matplotlib.rc is a function that updates matplotlib.rcParams.
matplotlib.rcParams is a dict-subclass that provides a validate key-value map for Matplotlib configuration.
The docs for mpl.rc are at https://matplotlib.org/stable/api/matplotlib_configuration_api.html?highlight=rc#matplotlib.rc and the code is here.
The class definition of RcParams is here and it the instance is created here.
If we look at the guts of matplotlib.rc we see:
for g in group:
for k, v in kwargs.items():
name = aliases.get(k) or k
key = '%s.%s' % (g, name)
try:
rcParams[key] = v
except KeyError as err:
raise KeyError(('Unrecognized key "%s" for group "%s" and '
'name "%s"') % (key, g, name)) from err
where we see that matplotlib.rc does indeed update matplotlib.rcParams (after doing some string formatting).
You should use which ever one is more convenient for you. If you know exactly what key you want to update, then interacting with the dict-like is better, if you want to set a whole bunch of values in a group then mpl.rc is likely better!
In Dart/Flutter, suppose you have an instance a of Class Y.
Class Y has a property, property1.
You want to print that property using string interpolation like so:
print('the thing I want to see in the console is: $a.property1');
But you can't even finish typing that in without getting an error.
The only way I can get it to work is by doing this:
var temp = a.property1;
print ('the thing I want to see in the console is: $temp');
I haven't found the answer online... and me thinks there must be a way to just do it directly without having to create a variable first.
You need to enclose the property in curly braces:
print('the thing I want to see in the console is: ${a.property}');
That will then print the value of a.property.
It seems you can also do this, but it doesn't seem to be documented anywhere:
print('..... $a.$property1');
I am trying to solve a problem involving the equating of sums of exponentials.
This is how I would do it hardcoded:
#NLconstraint(m, exp(x[25])==exp(x[14])+exp(x[18]))
This works fine with the rest of the code. However, when I try to do it for an arbitrary set of equations like the above I get an error. Here's my code:
#NLconstraint(m,[k=1:length(LHSSum)],sum(exp.(LHSSum[k][i]) for i=1:length(LHSSum[k]))==sum(exp.(RHSSum[k][i]) for i=1:length(RHSSum[k])))
where LHSSum and RHSSum are arrays containing arrays of the elements that need to be exponentiated and then summed over. That is LHSSum[1]=[x[1],x[2],x[3],...,x[n]]. Where x[i] are variables of type JuMP.Variable. Note that length(LHSSum)=length(RHSSum).
The error returned is:
LoadError: exp is not defined for type Variable. Are you trying to build a nonlinear problem? Make sure you use #NLconstraint/#NLobjective.
So a simple solution would be to simply do all the exponentiating and summing outside of the #NLconstraint function, so the input would be a scalar. However, this too presents a problem since exp(x) is not defined since x is of type JuMP.variable, whereas exp expects something of type real. This is strange since I am able to calculate exponentials just fine when the function is called within an #NLconstraint(). I.e. when I code this line#NLconstraint(m,exp(x)==exp(z)+exp(y)) instead of the earlier line, no errors are thrown.
Another thing I thought to do would be a Taylor Series expansion, but this too presents a problem since it goes into #NLconstraint land for powers greater than 2, and then I get stuck with the same vectorization problem.
So I feel stuck, I feel like if JuMP would allow for the vectorized evaluation of #NLconstraint like it does for #constraint, this would not even be an issue. Another fix would be if JuMP implements it's own exp function to allow for the exponentiation of JuMP.Variable type. However, as it is I don't see a way to solve this problem in general using the JuMP framework. Do any of you have any solutions to this problem? Any clever workarounds that I am missing?
I'm confused why i isn't used in the expressions you wrote. Do you mean:
#NLconstraint(m, [k = 1:length(LHSSum)],
sum(exp(LHSSum[k][i]) for i in 1:length(LHSSum[k]))
==
sum(exp(RHSSum[k][i]) for i in 1:length(RHSSum[k])))
I know that tan(angle) gets me the tangent. But how do I do the "reverse tangent" so that I can get the angle given the length of both sides of the right triangle?
I'm assuming there is a method for this in math.h?
As others have mentioned, atan() is what you're looking for. Generally, the operation is referred to as "inverse tangent" or "arc tangent", not "reverse tangent". The name "atan" comes from "arc tangent". There's also an atan2() function which takes both the X and the Y coordinates as separate paramters and will give you an angle relative to the 0 mark whereas atan() will leave figuring out the quadrant as an exercise for the developer. Beware, however, that the atan2() function on certain older MS environments (or maybe visual studio libraries?) doesn't work quite right...
There should be an atan() function.
For example: http://www.acm.uiuc.edu/webmonkeys/book/c_guide/2.7.html
use atan()