Maple Questions and Posts

Verify a solution of a 2-equations system using ev...

Asked by: MaPal93 175

May 08 2024

1 2

I am trying to verify a solution by checking whether eval() returns 0 but it's taking me forever. If I recall correctly it once returned [0,0] so I am quite confident that the first and only positive root of that polynomial solves my system. I am now running again the same calculation but somehow eval() is stuck in "Evaluating...". I am not sure if it matters here, but parameters gamma, sigma_v, and sigma_d are strictly positive while -1<rho<+1 (rho is a correlation coefficient).

How else can I verify such solution?

EDIT: THIS IS NOT A DUPLICATE QUESTION AND SHOULDN'T BE TAGGED AS SUCH

>

restart;

>	local gamma:

Equations:

>

eq1 := (gamma*sigma__v^2*(-1 + rho__v) - 2*lambda__2)*(rho__v*sigma__v^2 + sigma__v^2)/((2*gamma*(lambda__1 + lambda__2)*(-1 + rho__v)*sigma__v^2 - 8*lambda__1*lambda__2)*((gamma*sigma__v^2*(-1 + rho__v) - 2*lambda__2)^2*(2*rho__v*sigma__v^2 + 2*sigma__v^2)/(2*gamma*(lambda__1 + lambda__2)*(-1 + rho__v)*sigma__v^2 - 8*lambda__1*lambda__2)^2 + (-lambda__1*(gamma*sigma__v^2*(-1 + rho__v) - 4*lambda__2)/(2*gamma*(lambda__1 + lambda__2)*(-1 + rho__v)*sigma__v^2 - 8*lambda__1*lambda__2) + 1)^2*sigma__d^2 + gamma^2*lambda__2^2*sigma__v^4*(-1 + rho__v)^2*sigma__d^2/(2*gamma*(lambda__1 + lambda__2)*(-1 + rho__v)*sigma__v^2 - 8*lambda__1*lambda__2)^2)):

eq2 := (gamma*sigma__v^2*(-1 + rho__v) - 2*lambda__1)*(rho__v*sigma__v^2 + sigma__v^2)/((2*gamma*(lambda__1 + lambda__2)*(-1 + rho__v)*sigma__v^2 - 8*lambda__1*lambda__2)*((gamma*sigma__v^2*(-1 + rho__v) - 2*lambda__1)^2*(2*rho__v*sigma__v^2 + 2*sigma__v^2)/(2*gamma*(lambda__1 + lambda__2)*(-1 + rho__v)*sigma__v^2 - 8*lambda__1*lambda__2)^2 + (-(gamma*sigma__v^2*(-1 + rho__v) - 4*lambda__1)*lambda__2/(2*gamma*(lambda__1 + lambda__2)*(-1 + rho__v)*sigma__v^2 - 8*lambda__1*lambda__2) + 1)^2*sigma__d^2 + gamma^2*lambda__1^2*sigma__v^4*(-1 + rho__v)^2*sigma__d^2/(2*gamma*(lambda__1 + lambda__2)*(-1 + rho__v)*sigma__v^2 - 8*lambda__1*lambda__2)^2)):

Eq1, Eq2 := eq1 - lambda__1, eq2 - lambda__2:

Solution:

>

Gamma := gamma*sigma__v*sigma__d:
L__2 := RootOf(-8*(rho + 1)^4*_Z^4 + 12*(rho + 1)^3*Gamma*(rho - 1)*_Z^3 - 5*(rho + 1)^2*(-4/5 + Gamma^2*rho^2 + 2*(-2/5 - Gamma^2)*rho + Gamma^2)*_Z^2 - 4*(rho + 1)*Gamma*(rho^2 - 1)*_Z + Gamma^2*(rho + 1)*(rho - 1)^2);
l__2 := L__2*sigma__v*(rho__v + 1)/sigma__d:
quartic_solution := lambda__2 = simplify(allvalues~([l__2]))[1]:

(1)

Check: TOO SLOW

>	simplify(eval([eval(Eq1, lambda__1 = lambda__2), eval(Eq2, lambda__1 = lambda__2)], quartic_solution));

Download solution_check.mw

Maple initialization file...

Asked by: charlie_fcl 130

May 07 2024

1 2

Hi,

I was just wondering if there is a init file for the Windows version of Maple, like there is one for the LInux version.

I'm not talking about the Maple.ini file located in the user's Application Data folder. In the Linux version, there is a file, .mapleinit, where you can place all of your initialization setups, like the packages you want to automatically load with the worksheet, defining constants, etc.

If someone has any ideas, I really appreciate it. Thanks very much in advance.

Wigner J, Clebsch-Gordon...

Asked by: saeedr12 10

May 07 2024

2 0

Hi,

is there any package out there to calculate Wigner J symbols and Clebsch-Gordon coefficients in Maple

Plot a vector field...

Asked by: emersondiaz 60

May 07 2024

1 2

Good day to all of you nice people.
I'm currently attempting to plot a vector field where each component of the vector is defined by the equations S_x, S_y, and S_z, which are functions of the radial coordinate. Here is a depiction of how the vectors change with respect to r:

The next step, which I'm unsure how to do, is to plot the vectors around the z-direction, or I should say, in phi direction, to achieve something similar to this example:

Thank you a lot for your kind help.

Here is my code:
Maple_Question.mw

Is this a bug or does Maple hate me? ...

Asked by: Hullzie16 333

May 07 2024

1 1

I am running Maple 2023 - yes I should update - and I found a weird "bug" if you could call it that. For different versions of the Physics package I am getting different answers on the same problem.

This is what I was getting when I run Version 1410:

>

restart;

>	with(Physics):

>	Physics:-Version()

(1)

>	Setup(mathematicalnotation=true):

>	g_[arbitrary]:

$`Default differentiation variables for d_, D_ and dAlembertian are:`*{X = (x1, x2, x3, x4)}$

(2)

>	LG :=(g_[~mu,~nu]Ricci[mu,nu])sqrt(-%g_[determinant]);

(3)

>	SG:=Intc(LG,X)

Int(Int(Int(Int(Physics:-g_[`~mu`, `~nu`]*Physics:-Ricci[mu, nu]*(-%g_[determinant])^(1/2), x1 = -infinity .. infinity), x2 = -infinity .. infinity), x3 = -infinity .. infinity), x4 = -infinity .. infinity)

(4)

>	EQ:=Fundiff(SG,%g_[~delta,~gamma])/sqrt(-%g_[determinant])

((1/2)*%g_[`~mu`, `~nu`]*Physics:-Ricci[mu, nu]*%g_[delta, gamma]*%g_[determinant]/(-%g_[determinant])^(1/2)+Physics:-Ricci[mu, nu]*(-%g_[determinant])^(1/2)*%g_[delta, `~mu`]*%g_[gamma, `~nu`])/(-%g_[determinant])^(1/2)

(5)

>	Simplify(subs(%g_=g_,EQ))

-(1/2)*Physics:-g_[delta, gamma]*Physics:-Ricci[nu, `~nu`]+Physics:-Ricci[delta, gamma]

(6)

>

And this is what I get if I used the latet update for 2023, Version 1683:

>

restart;

>	with(Physics):

>	Physics:-Version();

(1)

>	Setup(mathematicalnotation=true):

>	g_[arbitrary]:

$`Default differentiation variables for d_, D_ and dAlembertian are:`*{X = (x1, x2, x3, x4)}$

(2)

>	LG :=(g_[~mu,~nu]Ricci[mu,nu])sqrt(-%g_[determinant]);

(3)

>	SG:=Intc(LG,X)

Int(Int(Int(Int(Physics:-g_[`~mu`, `~nu`]*Physics:-Ricci[mu, nu]*(-%g_[determinant])^(1/2), x1 = -infinity .. infinity), x2 = -infinity .. infinity), x3 = -infinity .. infinity), x4 = -infinity .. infinity)

(4)

>	EQ:=Fundiff(SG,%g_[~delta,~gamma])/sqrt(-%g_[determinant])

-(1/2)*%g_[delta, gamma]*Physics:-g_[`~mu`, `~nu`]*Physics:-Ricci[mu, nu]

(5)

>	Simplify(subs(%g_=g_,EQ))

-(1/2)*Physics:-g_[delta, gamma]*Physics:-Ricci[nu, `~nu`]

(6)

>

Strange right? I bring this up because it makes me wonder about potential errors in other computations...

The answer - equation 6 - in 1410 is the correct answer. This is simply a derivation of the Einstein Tensor.

Exploring the SIR Model with Vaccination

by: Paras31 245 Product: Maple 2024

May 07 2024

0 3

In our recent project, we're diving deep into understanding the SIR model—a fundamental framework in epidemiology that helps us analyze how diseases spread through populations. The SIR model categorizes individuals into three groups: Susceptible (S), Infected (I), and Recovered (R). By tracking how people move through these categories, we can predict disease dynamics and evaluate interventions.

Key Points of the SIR Model:

Susceptible (S): Individuals who can catch the disease.
Infected (I): Those currently infected and capable of spreading the disease.
Recovered (R): Individuals who have recovered and developed immunity.

Vaccination Impact: One of the critical interventions in disease control is vaccination, which moves individuals directly from the susceptible to the recovered group. This simple action reduces the number of people at risk, thereby lowering the overall spread of the disease.

We're experimenting with a simple model to understand how different vaccination rates can significantly alter the dynamics of an outbreak. By simulating scenarios with varying vaccination coverage, students can observe how herd immunity plays a crucial role in controlling diseases. Our goal is to make these abstract concepts clear and relatable through practical modeling exercises.

In this exercise, we are going back to the simple SIR model, without births or deaths, to look at the effect of vaccination. The aim of this activity is to represent vaccination in a very simple way - we are assuming it already happened before we run our model! By changing the initial conditions, we can prepare the population so that it has received a certain coverage of vaccination.

We are starting with the transmission and recovery parameters and . To incorporate immunity from vaccination in the model, we assume that a proportion p of the total population starts in the recovered compartment, representing the vaccine coverage and assuming the vaccine is perfectly effective. Again, we assume the epidemic starts with a single infected case introduced into the population.
We are going to model this scenario for a duration of 2 years, assuming that the vaccine coverage is 50%, and plot the prevalence in each compartment over time.

deS := diff(S(t), t) = -b*S(t)*I0(t); deI := diff(I0(t), t) = b*S(t)*I0(t)-c*I0(t); deR := diff(R(t), t) = c*I0(t)

(1)

F := dsolve([deS, deI, deR, S(0) = 1-p, I0(0) = 1/n, R(0) = p], [S(t), I0(t), R(t)], numeric, method = rkf45, maxfun = 100000)

$odeplot(F, [[t, S(t)], [t, I0(t)], [t, R(t)]], t = 0 .. 730, colour = [blue, red, green], legend = ["S(t)", "I0(t)", "R(t)"], labels = ["Time (days)", " Proportion\nof Population "], title = "SIR Model with vaccine coverage 50 %", size = [500, 300])$

(2)

(3)

(4)

Increasing the vaccine coverage to 75%

deS := diff(S(t), t) = -b*S(t)*I0(t); deI := diff(I0(t), t) = b*S(t)*I0(t)-c*I0(t); deR := diff(R(t), t) = c*I0(t)

(5)

F1 := dsolve([deS, deI, deR, S(0) = 1-p, I0(0) = 1/n, R(0) = p], [S(t), I0(t), R(t)], numeric, method = rkf45, maxfun = 100000)

$odeplot(F1, [[t, S(t)], [t, I0(t)], [t, R(t)]], t = 0 .. 730, colour = [blue, red, green], legend = ["S(t)", "I0(t)", "R(t)"], labels = ["Time (days)", " Proportion\nof Population "], title = "SIR Model with vaccine coverage 75%", size = [500, 300])$

(6)

(7)

Does everyone in the population need to be vaccinated in order to prevent an epidemic?What do you observe if you model the infection dynamics with different values for p?

No, not everyone in the population needs to be vaccinated in order to prevent an epidemic . In this scenario, if p equals 0.75 or higher, no epidemic occurs - 75 % is the critical vaccination/herd immunity threshold . Remember,, herd immunity describes the phenomenon in which there is sufficient immunity in a population to interrupt transmission . Because of this, not everyone needs to be vaccinated to prevent an outbreak .

What proportion of the population needs to be vaccinated in order to prevent an epidemic if and ? What if and

In the context of the SIR model, the critical proportion of the population that needs to be vaccinated in order to prevent an epidemic is often referred to as the "herd immunity threshold" or "critical vaccination coverage."

•	Scenario 1: and

deS := diff(S(t), t) = -b*S(t)*I0(t); deI := diff(I0(t), t) = b*S(t)*I0(t)-c*I0(t); deR := diff(R(t), t) = c*I0(t)

(8)

F1 := dsolve([deS, deI, deR, S(0) = 1-p, I0(0) = 1/n, R(0) = p], [S(t), I0(t), R(t)], numeric, method = rkf45, maxfun = 100000)

$odeplot(F1, [[t, S(t)], [t, I0(t)], [t, R(t)]], t = 0 .. 730, colour = [blue, red, green], legend = ["S(t)", "I0(t)", "R(t)"], labels = ["Time (days)", " Proportion\nof Population "], title = "SIR Model with vaccine coverage 50 %", size = [500, 300])$

The required vaccination coverage is around 50% .

•	Scenario 1: and

deS := diff(S(t), t) = -b*S(t)*I0(t); deI := diff(I0(t), t) = b*S(t)*I0(t)-c*I0(t); deR := diff(R(t), t) = c*I0(t)

(9)

F1 := dsolve([deS, deI, deR, S(0) = 1-p, I0(0) = 1/n, R(0) = p], [S(t), I0(t), R(t)], numeric, method = rkf45, maxfun = 100000)

$odeplot(F1, [[t, S(t)], [t, I0(t)], [t, R(t)]], t = 0 .. 730, colour = [blue, red, green], legend = ["S(t)", "I0(t)", "R(t)"], labels = ["Time (days)", " Proportion\nof Population "], title = "SIR Model with vaccine coverage 83% ", size = [500, 300])$

Download SIR_simple_vaccination_example.mw

Union and indexed sets...

Asked by: Johan Bertilsdotter 15

May 06 2024

1 1

Or some other type of calculation in indexed set. I tried the maple android app with no luck. How is done in maple?

Dynamic Systems/System of ODEs error...

Asked by: jackyleerush 10

May 06 2024

2 6

Hey there guys, was wondering if I could get some help with this - I'm pretty new to maple.

I'm trying to take a collection of coupled ODEs I have and get maple put them in state-space form for me. I've tried a few different approaches and messed around with a few different commands but havent managed to quite make it work. At the moment I'm trying to make a DiffEquation object and then use StateSpace to get the state space representation, but I keep getting this "diff-eq is not a polynomial" line as a warning when I run the DiffEquation command and as an error when I try to conver to state space.

Could anyone tell me why I'm getting this and what the best/correct way to go about this is?

Cheers

Download 403TripleCart.mw

why do i have a problem?...

Asked by: miguelbravo 70

May 06 2024

0 0

I`m trying execute the example of Deeplearnig:

with(DeepLearning);
v1 := Vector(8, i -> i, datatype = float[8]);
v2 := Vector(8, [-1.0, 1.0, 5.0, 11.0, 19.0, 29.0, 41.0, 55.0], datatype = float[8]);
model := Sequential([DenseLayer(1, inputshape = [1])]);
model := Vector(2, {(1) = Typesetting:-mi("`DeepLearning

Model`"), (2) = Typesetting:-mi("`<keras.engine.sequential.Se\

quential object at 0x000001C5B6520700>`")})

model:-Compile(optimizer = "sgd", loss = "mean_squared_error");
model:-Fit(v1, v2, epochs = 500);
"<Python object: <keras.callbacks.History object at 0x000001C5CC\

EE9DE0>>"

convert("<Python object: <keras.callbacks.History object at 0x000001C5CCEE9DE0>>", 'symbol');
<Python object: <keras.callbacks.History object at 0x000001C5CCE\

E9DE0>>

model:-Predict([10]);

But, finally, there is this error:

Error, (in Predict) AttributeError: 'CatchOutErr' object has no attribute 'flush'

['Traceback (most recent call last):\n', ' File "C:\\Program Files\\Maple 2023\\Python.X86_64_WINDOWS\\lib\\site-packages\\keras\\utils\\traceback_utils.py", line 70, in error_handler\n raise e.with_traceback(filtered_tb) from None\n', ' File "C:\\Program Files\\Maple 2023\\Python.X86_64_WINDOWS\\lib\\site-packages\\keras\\utils\\io_utils.py", line 80, in print_msg\n sys.stdout.flush()\n', "AttributeError: 'CatchOutErr' object has no attribute 'flush'\n"]

What`s is happening?

Thanks!

Signs of first and second derivatives of bivariate...

Asked by: MaPal93 175

May 06 2024

1 3

I have a complicated bivariate function f(Gamma,rho) that is a RootOf of a quartic. I know that it is strictly positive (one of the four roots at least) for Gamma=0..10 and rho in (-1,+1), with bounds excluded.

I need to find the signs of its first and second derivatives (wrt to Gamma and wrt to rho: 4 derivatives in total).

I encounter numerical issues when I plot3d the derivatives using D[]() vs. fdiff() (numerical function evaluations of the RootOf). I was hoping for the two commands to produce the same output, but they don't it seems. What's going on?

Script:

>	restart; _quartic := RootOf(-8(rho + 1)^4_Z^4 + 12(rho + 1)^3Gamma(rho - 1)_Z^3 - 5(rho + 1)^2(-4/5 + Gamma^2rho^2 + 2(-2/5 - Gamma^2)rho + Gamma^2)_Z^2 - 4(rho + 1)Gamma(rho^2 - 1)_Z + Gamma^2(rho + 1)(rho - 1)^2); convert(_quartic,radical): f(Gamma,rho) := simplify(%):

RootOf((8*rho^3+24*rho^2+24*rho+8)*_Z^4+(-12*Gamma*rho^3-12*Gamma*rho^2+12*Gamma*rho+12*Gamma)*_Z^3+(5*Gamma^2*rho^3-5*Gamma^2*rho^2-5*Gamma^2*rho+5*Gamma^2-4*rho^2-8*rho-4)*_Z^2+(4*Gamma*rho^2-4*Gamma)*_Z-Gamma^2*rho^2+2*rho*Gamma^2-Gamma^2)

(1)

Synthetic representation of derivatives

>

der1_Gamma := diff(_quartic, Gamma):
der1_rho := diff(_quartic, rho):

Diff('f(Gamma,rho)', Gamma) = collect~(normal(eval(der1_Gamma, _quartic = 'f(Gamma,rho)')), 'f(Gamma,rho)');
Diff('f(Gamma,rho)', rho) = collect~(normal(eval(der1_rho, _quartic = 'f(Gamma,rho)')), 'f(Gamma,rho)');

der2_Gamma := diff(der1_Gamma, Gamma):
der2_rho := diff(der1_rho, rho):

Diff('f(Gamma,rho)', Gamma$2) = collect~(normal(eval(der2_Gamma, _quartic = 'f(Gamma,rho)')), 'f(Gamma,rho)');
Diff('f(Gamma,rho)', rho$2) = collect~(normal(eval(der2_rho, _quartic = 'f(Gamma,rho)')), 'f(Gamma,rho)');

(2)

Signs of derivatives: fdiff (numerical function evaluations of the RootOf) vs. D[]()

>	restart; with(plots):

>	_quartic := RootOf(-8(rho + 1)^4_Z^4 + 12(rho + 1)^3Gamma(rho - 1)_Z^3 - 5(rho + 1)^2(-4/5 + Gamma^2rho^2 + 2(-2/5 - Gamma^2)rho + Gamma^2)_Z^2 - 4(rho + 1)Gamma(rho^2 - 1)_Z + Gamma^2(rho + 1)(rho - 1)^2):

>	plot3d(_quartic, Gamma=0..10, rho=-1..+1, labels=[Gamma,rho,Lambda(Gamma,rho)],axesfont=["helvetica","roman",20],labelfont=["helvetica","roman",30]);

Define it as a f and test it for Gamma=1 and rho=0.5

>	f := (Gamma,rho) -> RootOf(-8(rho + 1)^4_Z^4 + 12(rho + 1)^3Gamma(rho - 1)_Z^3 - 5(rho + 1)^2(-4/5 + Gamma^2rho^2 + 2(-2/5 - Gamma^2)rho + Gamma^2)_Z^2 - 4(rho + 1)Gamma(rho^2 - 1)_Z + Gamma^2(rho + 1)(rho - 1)^2): evalf(f(1.0,0.5));

(3)

Value at zero:

>	f(0,0): allvalues(%): fl := select(is, [allvalues(f(0,0))], positive)[];evalf(%);

(4)

Value at infinity (commented out because too slow)

>	#limit(f(x,y), {x = infinity, y = 0}): #fh := select(is, [allvalues(%)], positive)[];evalf(%);

Derivative at zero:

>	allvalues([D[1](f)(0,0)]): Dfl := %[1][];

(5)

Derivative at a point, evaluated, vs numerical derivative at a point:

>	D[1](f)(1,0.5): evalf(%); fdiff(f(x,y), x, {x = 1.0, y = 0.5}); fdiff(f, [1], [1.0,0.5]); D[2](f)(1,0.5): evalf(%); fdiff(f(x,y), y, {x = 1.0, y = 0.5}); fdiff(f, [2], [1.0,0.5]);

(6)

Can make a function out of fdiff

>	fDfG := (Gamma,rho) -> fdiff(f, [1], [Gamma,rho]); fDfr := (Gamma,rho) -> fdiff(f, [2], [Gamma,rho]);

(7)

Check for numerical values close to thresholds:

>

Digits := 15:
evalf('D[1]'(f)(0.1e-8,0.5));fdiff(f, [1], [0.1e-8,0.5]);
evalf('D[1]'(f)(0.1e-7,0.5));fdiff(f, [1], [0.1e-7,0.5]);
evalf('D[1]'(f)(0.1e-5,0.5));fdiff(f, [1], [0.1e-5,0.5]);
evalf('D[1]'(f)(0.00001,0.5));fdiff(f, [1], [0.00001,0.5]);
evalf('D[1]'(f)(0.001,0.5));fdiff(f, [1], [0.001,0.5]);

evalf('D[2]'(f)(1,-0.99));fdiff(f, [2], [1,-0.99]);
evalf('D[2]'(f)(1,-0.97));fdiff(f, [2], [1,-0.97]);
evalf('D[2]'(f)(1,-0.1));fdiff(f, [2], [1,-0.1]);
evalf('D[2]'(f)(1,0.98));fdiff(f, [2], [1,0.98]);
evalf('D[2]'(f)(1,-0.99));fdiff(f, [2], [1,-0.99]);

(8)

Compare with D (vertical range here to prevent effect of large values from fdiff near zero):

>	d1G := plot3d([D[1](f), fDfG], 0..10, -0.95..+0.95, view=-0.3..0, color = [red, blue]); d1r := plot3d([D[2](f), fDfr], 0..10, -0.95..+0.95, color = [red, blue]);

Second derivatives:

>	evalf('D[1,1]'(f)(1.0,0.5)); fdiff(f, [1, 1], [1.0,0.5]); evalf('D[2,2]'(f)(1.0,0.5)); fdiff(f, [2, 2], [1.0,0.5]); fD2fG := (Gamma,rho) -> fdiff(f, [1, 1], [Gamma]); fD2fr := (Gamma,rho) -> fdiff(f, [2, 2], [Gamma]);

(9)

>	d2G:= plot3d([D[1,1](f), fD2fG], 0..10, -0.9..+0.9, color = [red, blue]); d2r:= plot3d([D[2,2](f), fD2fr], 0..10, -0.9..+0.9, color = [red, blue]);

Warning, unable to evaluate the function to numeric values in the region; see the plotting command's help page to ensure the calling sequence is correct

>	d1d2G := plot3d([fDfG, fD2fG], 0.1e-6 .. 10, -0.98 .. +0.98, axesfont=["helvetica","roman",20],labelfont=["helvetica","roman",30], size=[1000,1000]); d1d2r := plot3d([fDfr, fD2fr], 0.1e-6 .. 10, -0.98 .. +0.98, axesfont=["helvetica","roman",20],labelfont=["helvetica","roman",30], size=[1000,1000]);

Warning, unable to evaluate the function to numeric values in the region; see the plotting command's help page to ensure the calling sequence is correct

Download signs_derivatves_bivariate.mw

Why does no substitution work on some functions ?...

Asked by: WA573 80

May 06 2024

0 4

Why does no substitution work on functions with s(n+1,t) (see eqns (2-8))? Also (&PartialD;)/(&PartialD; (sigma2*t))=1/(sigma2)(&PartialD;)/(&PartialD; t), how can I do it on Maple?shift.mw

Third party package...

Asked by: mz6687 40

May 06 2024

0 3

I am trying to load the third-party package 'CPC Program Library (qub.ac.uk)' by following the instructions as in 'how to install wkptest? - MaplePrimes'. But encounter with Errors: '

Error, `:` unexpected
with(wkptest);
Error, invalid input: with expects its 1st argument, pname, to be of type {`module`, package}, but received wkptest

>

restart:

>

sourcefolder:=cat(kernelopts('C:\Users\ahmed\Downloads\adty_v1_0'),"/wkptest");
installfolder:=cat(kernelopts('homedir'),"/maple/toolbox/wkptest/lib");
FileTools:-MakeDirectory(installfolder, 'recurse'=true);
libraryfile:=cat(installfolder,"/wkptest.mla");
try
FileTools:-Remove(libraryfile);
catch:
end try:
LibraryTools:-Create(libraryfile);
libname:=libraryfile,libname;
read cat(sourcefolder,"/wkptest_cpc");

Error, `:` unexpected

>	with(wkptest);

Error, invalid input: with expects its 1st argument, pname, to be of type {`module`, package}, but received wkptest

Download exam_wkptest1.mws

How can I calculate the actual number of months be...

Asked by: ragush 15

May 05 2024

3 3

When I calculate the difference between two dates with the same day using the DateDifference Calendar function, I don't get an integer number of months, but results with extra days, hours, minutes, seconds and milliseconds. How can I calulate the actual number of months?

I appreciate any help.