Grammostola pulchripes

One of the larger species of tarantula, the Chaco golden knee (Grammostola pulchripes), formerly known by Grammostola aureostriata,[1] can be expected to reach between 20–22 cm (8.5 in).

Chaco golden knee
Scientific classification
Kingdom: Animalia
Phylum: Arthropoda
Subphylum: Chelicerata
Class: Arachnida
Order: Araneae
Infraorder: Mygalomorphae
Family: Theraphosidae
Genus: Grammostola
Species:
G. pulchripes
Binomial name
Grammostola pulchripes
(Simon, 1892)
Synonyms

Grammostola aureostriata Schmidt & Bulmer, 2001
Grammostola aureostriata

Name

The former (and very commonly used) species name, aureostriata, is derived from Latin aureus "golden" and striatus "striped". The currently used species name, "pulchripes," is derived from Latin "pulchra", meaning "beautiful", and "pes", meaning "foot".

Description and behavior

The Chaco golden knee is a large tarantula, being able to reach between 7 and 8 inches in legspan (17.8-20.3 cm). Being a terrestrial tarantula, it has a heavy body. Mature males have longer legs and smaller bodies than females, and they possess tibial hooks or apophyses to hold back a female's fangs during mating. Males also possess modified pedipalps to insert sperm into the female's genital operculum. It exhibits a multitude of colors, with bright yellowish leg stripes, dark black "femurs", and pink hairs all over its body. As with the rest of the genus Grammostola, the Chaco golden knee has very large fangs, and the carapace (the top of the prosoma) is raised to make room for the large chelicerae. It has rudimentary eyesight, and senses its environment with the setae all over its body, feeling vibrations through the ground and air, and picking up chemical signatures, similar to a sense of smell.

Natural habitat

The Chaco golden knee tarantulas are known to inhabit the grasslands of Argentina and Paraguay.[2] As such, they are adapted to generally warm climate, with alternating dry and rainy seasons.

As a pet
  • G. pulchripes in captivity

The Chaco golden knee is a very calm and docile tarantula, which, along with its striking appearance and large size, makes it an attractive pet, especially for beginners. It frequently sits in plain view in captivity, and likes to shove substrate around, especially at young ages. Females can live for well over twenty years, while males only live for about five or six years. The tarantula must periodically molt its exoskeleton to grow larger, and it is vulnerable during this time. This can happen every few weeks for newborn spiderlings or every few years for large adults.

The Chaco golden knee tends to be one of the more docile and calm species of tarantula and therefore makes an attractive first pet. The Chaco is an opportunistic burrowing terrestrial tarantula: they tend to burrow while younger and adopt a pre-existing hide as its home when it begins to mature. It is quite flashy in appearance, bearing long light-colored hairs all over its body and gold stripes on its legs, particularly at the "knees". This is a good display species as it often sits in plain view. When it was first imported into the pet trade, it was thought to be a variant of the Pink zebra beauty species, but it is significantly larger and can easily be distinguished by the size difference, with the most notable comparative feature being the leg-span, though an experienced owner could distinguish the colouring.

  • Spiderling feeding on Blaptica dubia
  • Mature male Chaco
  • Juvenile female in captivity
  • Young female G. pulchripes
gollark: It uses the function, yes.
gollark: So, I finished that to highly dubious demand. I'd like to know how #11 and such work.
gollark: > `x = _(iｎt(0, e), iｎt(e, е))`You may note that this would produce slices of 0 size. However, one of the `e`s is a homoglyph; it contains `2 * e`.`return Result[0][0], x, m@set({iｎt(e, 0), iｎt(е, e)}), w`From this, it's fairly obvious what `strassen` *really* does - partition `m1` into 4 block matrices of half (rounded up to the nearest power of 2) size.> `E = typing(lookup[2])`I forgot what this is meant to contain. It probably isn't important.> `def exponentiate(m1, m2):`This is the actual multiplication bit.> `if m1.n == 1: return Mаtrix([[m1.bigData[0] * m2.bigData[0]]])`Recursion base case. 1-sized matrices are merely multiplied scalarly.> `aa, ab, ac, ad = strassen(m1)`> `аa, аb, аc, аd = strassen(m2)`More use of homoglyph confusion here. The matrices are quartered.> `m = m1.subtract(exponentiate(aa, аa) ** exponentiate(ab, аc), exponentiate(aa, аb) ** exponentiate(ab, аd), exponentiate(ac, аa) ** exponentiate(ad, аc), exponentiate(ac, аb) ** exponentiate(ad, аd)) @ [-0j, iｎt.abs(m2.n * 3, m1.n)]`This does matrix multiplication in an inefficient *recursive* way; the Strassen algorithm could save one of eight multiplications here, which is more efficient (on big matrices). It also removes the zero padding.> `m = exponentiate(Mаtrix(m1), Mаtrix(m2)) @ (0j * math.sin(math.asin(math.sin(math.asin(math.sin(math.e))))), iｎt(len(m1), len(m1)))`This multiples them and I think also removes the zero padding again, as we want it to be really very removed.> `i += 1`This was added as a counter used to ensure that it was usably performant during development.> `math.factorial = math.sinh`Unfortunately, Python's factorial function has really rather restrictive size limits.> `for row in range(m.n):`This converts back into the 2D array format.> `for performance in sorted(dir(gc)): getattr(gc, performance)()`Do random fun things to the GC.
gollark: > `globals()[Row + Row] = random.randint(*sys.version_info[:2])`Never actually got used anywhere.> `ε = sys.float_info.epsilon`Also not used. I just like epsilons.> `def __exit__(self, _, _________, _______):`This is also empty, because cleaning up the `_` global would be silly. It'll be overwritten anyway. This does serve a purpose, however, and not just in making it usable as a context manager. This actually swallows all errors, which is used in some places.> `def __pow__(self, m2):`As ever, this is not actual exponentiation. `for i, (ι, 𐌉) in enumerate(zip(self.bigData, m2.bigData)): e.bigData[i] = ι + 𐌉` is in fact just plain and simple addition of two matrices.> `def subtract(forth, 𝕒, polynomial, c, vector_space):`This just merges 4 submatrices back into one matrix.> `with out as out, out, forth:`Apart from capturing the exceptions, this doesn't really do much either. The `_` provided by the context manager is not used.> `_(0j, iｎt(0, 𝕒.n))`Yes, it's used in this line. However, this doesn't actually have any effect whatsoever on the execution of this. So I ignore it. It was merely a distraction.> `with Mаtrix(ℤ(ℤ(4))):`It is used again to swallow exceptions. After this is just some fluff again.> `def strassen(m, x= 3.1415935258989):`This is an interesting part. Despite being called `strassen`, it does not actually implement the Strassen algorithm, which is a somewhat more efficient way to multiply matrices than the naive way used in - as far as I can tell - every entry.> `e = 2 ** (math.ceil(math.log2(m.n)) - 1)`This gets the next power of two in a fairly obvious way. It is used to pad out the matrix to the next power of 2 size.> `with m:`The context manager is used again for nicer lookups.> `Result[0] += [_(0j, iｎt(e, e))]`Weird pythonoquirkiness again. You can append to lists in tuples with `+=`, but it throws an exception as they're sort of immutable.> `typing(lookup[4])(input())`It's entirely possible that this does things.
gollark: > `def __eq__(self, xy): return self.bigData[math.floor(xy.real * self.n + xy.imag)]`This actually gets indices into the matrix. I named it badly for accursedness. It uses complex number coordinates.> `def __matmul__(self, ǫ):`*This* function gets a 2D "slice" of the matrix between the specified coordinates. > `for (fοr, k), (b, р), (whіle, namedtuple) in itertools.product(I(*iｎt.ℝ(start, end)), enumerate(range(ℤ(start.imag), math.floor(end.imag))), (ǫ, ǫ)):`This is really just bizarre obfuscation for the basic "go through every X/Y in the slice" thing.> `out[b * 1j + fοr] = 0`In case the matrix is too big, just pad it with zeros.> `except ZeroDivisionError:`In case of zero divisions, which cannot actually *happen*, we replace 0 with 1 except this doesn't actually work.> `import hashlib`As ever, we need hashlib.> `memmove(id(0), id(1), 27)`It *particularly* doesn't work because we never imported this name.> `def __setitem__(octonion, self, v):`This sets either slices or single items of the matrix. I would have made it use a cool™️ operator, but this has three parameters, unlike the other ones. It's possible that I could have created a temporary "thing setting handle" or something like that and used two operators, but I didn't.> `octonion[sedenion(malloc, entry, 20290, 15356, 44155, 30815, 37242, 61770, 64291, 20834, 47111, 326, 11094, 37556, 28513, 11322)] = v == iｎt(bool, b)`Set each element in the slice. The sharp-eyed may wonder where `sedenion` comes from.> `"""`> `for testing`> `def __repr__(m):`This was genuinely for testing, although the implementation here was more advanced.> `def __enter__(The_Matrix: 2):`This allows use of `Matrix` objects as context managers.> `globals()[f"""_"""] = lambda h, Ĥ: The_Matrix@(h,Ĥ)`This puts the matrix slicing thing into a convenient function accessible globally (as long as the context manager is running). This is used a bit below.

References
  1. http://www.thebts.co.uk/forums/showthread.php?t=5079
  2. "The Needs & Habitat of the Chaco Golden Knee Tarantula". Retrieved 2016-10-02.
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