Skip subsitution step with forallpeople integration

[cslotboom]

Hey, I'd like to skip unit substitution when there is a lone unit with forallpeople.
Right now handcalcs will write out all the calculations steps if you write something like 200*si.mm. This is especially noticeable for unit-less equations.

It would look much cleaner if something like 200*si.mm is rendered as 200 mm, without the distribution, similar to how unitless quantities are just rendered.

An alternatively, if there was a way to flag lines to be skipped so they don't render, that would also be great! If I could declare blim but not render it, that would also be a solution to clean up these equations.

See examples below.

@handcalc('long', precision = 1)
def summarizeMoment(F_b, b, d, L, k_net, k_L = 1):
    phi = 0.9
    
    S_eff = b*d**2 / 6
    blim = 130*si.mm
    k_Zbg = min((((130*si.mm)/b)**0.1)*((610/d)**0.1)*((9100/L)**0.1), 1.3)
    k_eff = min(k_Zbg, k_L)
    
    Mr = (phi*F_b*S_eff*k_eff*k_net).to('Nm')

[connorferster]

Heyo!

Put any calculation in parentheses to prevent the substitution step from rendering.

[cslotboom]

Hey, okay perfect! Good to note and it did help my use case.
Do you think it is feasible to have a tag that will suppress certain lines, or would that be quite tricky? Even with the substitution suppressed, there is a lot of real estate being taken up by extra definitions. I often find myself doing gymnastics (like defining variables in other places) to save room and have cleaner substitutions.

That or the ability to suppress the substitution for definitions in multi-line expressions, such as below where 130*si.mm is used. This seems like a much harder task however.

It might seem like a small thing, but the extra substitution step might be confusing for a layperson who is trying to read a calculation.

@handcalc('long', precision = 2)
def summarizeMoment(F_b, b, d, L, k_net, k_L = 1):
    phi = 0.9
    d_lim = (610*si.mm)
    L_lim = (9100*si.mm)
    
    S_eff = b*d**2 / 6
    k_Zbg = min(((((130*si.mm)/b)*(d_lim/d)*(L_lim/L))**0.1), 1.3)
    k_eff = min(k_Zbg, k_L)
    
    M_r = (phi*F_b*S_eff*k_eff*k_net).to('Nm')