- Download source & dependencies
# Make a folder
mkdir ~/blender-git
cd ~/blender-git
# Clone the Blender repo
git clone https://git.blender.org/blender.git
# Clone the dependencies
mkdir ~/blender-git/lib
cd ~/blender-git/lib
# Make a folder
mkdir ~/blender-git
cd ~/blender-git
# Clone the Blender repo
git clone https://git.blender.org/blender.git
# Clone the dependencies
mkdir ~/blender-git/lib
cd ~/blender-git/lib
#!/bin/bash | |
# https://github.com/neuronsimulator/nrn/issues/409#issuecomment-576953060 | |
# | |
# If first arg is "clean" then remove the neuron module | |
# from site-packages and exit. | |
# | |
# If first arg is "test" then run "python -c 'import neuron; neuron.test()'" | |
# | |
# If first arg is "install" then build and install with support for all | |
# subsequent pyenv version names. |
import arbor, dbbs_models | |
from patch import p | |
# cell = arbor.cable_cell(morph.morphology, labels, decor) | |
model = dbbs_models.StellateCell | |
cell = model.cable_cell() | |
neuron_cell = model() | |
print(neuron_cell.soma) | |
neuron_cell.record_soma() | |
neuron_time = p.time | |
p.celsius = 32 |
class NrnCell: | |
def __init__(self): | |
self.all = [] | |
def _dims(segments): | |
# Get the (prox - dist) ^ 2 along a certain axis | |
d = lambda seg, axis: (getattr(seg.prox, axis) - getattr(seg.dist, axis)) ** 2 | |
# Sum and sqrt the distances along the x, y, z axes for eucl. dist | |
eucl = [sum(d(s, axis) for axis in ("x", "y", "z")) ** (1/2) for s in segments] |
class DeepQuery { | |
constructor(public query: any) { | |
} | |
private isObj(obj: any): boolean { | |
return ( | |
typeof obj === 'object' && | |
obj !== null | |
) |
As a user of scientific computing software packages, Python packages always trips over binary extensions that require cooperation with binaries on the target system. Packaging things in wheels becomes impossible, because there is currently no way for a user to specify that they want a wheel, but specifically the wheel that is compatible with their local library.
Take mpi4py
, the most popular parallelization scheme in my field. It requires to know which MPI
implementation is used: MPICH
,
OpenMPI
, ...? What mpi4py
does is provide a source distribution that detects the local library at install time, and errors out if it can't. So the user is
tasked with installing the binary dependencies of a Python package, before they can install the Python package. Python users have by design 0 knowledge of building binary software, we pip install
or riot ┬─┬ノ(ಠ_ಠノ).