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Author SHA1 Message Date
83c2a6d3b0 chore(deps): update dependency mypy to v1
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2024-04-25 01:30:56 +00:00
7aa5ad2eb9
chore(release): 0.7.9
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2024-04-21 11:23:42 -05:00
fe331bb544
Merge branch 'filter_compose'
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2024-04-21 11:21:36 -05:00
03ac85a967
chore: performance enhancement for fmt in justfile
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2024-04-21 11:21:11 -05:00
96589ff659
adds a filter for future dmc use 2024-04-21 10:55:44 -05:00
e5b5809764
build: delete do.sh
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2024-03-20 11:28:04 -05:00
1407418c60 Merge pull request 'custom_dmc' (#37) from custom_dmc into master
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Reviewed-on: #37
2024-03-20 16:27:19 +00:00
383b51c35d
Merge branch 'master' into custom_dmc
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2024-03-20 11:23:39 -05:00
5b9123d128 Merge pull request 'flakeupdate' (#36) from flakeupdate into master
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Reviewed-on: #36
2024-03-20 16:21:41 +00:00
2b1a1c21e4
Merge branch 'master' into flakeupdate
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2024-03-20 11:18:16 -05:00
ea080ca1c7
feat: adds ability to write custom dmc filters
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2024-03-20 10:56:54 -05:00
028fe58561
build: fixes issue brekaing build with unused variable
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2024-03-19 15:46:00 -05:00
b6a41872d5
just: fmt before test, better comments
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2024-03-19 15:45:15 -05:00
731dabd74d
nix: adds just as dependency, and fixes tests by installing deepdog app locally 2024-03-19 15:42:43 -05:00
7950f19c2d
build: adds justfile to replace do
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2024-03-19 15:42:18 -05:00
b27e504bbd
lint: unneeded variable definition
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2024-03-17 18:40:46 -05:00
33106ba772
nix: updates nix things to work, rewrites flake
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2024-03-17 15:18:52 -05:00
3ae0783d00
feat: adds tarucha phase calculation, using spin qubit precession rate noise
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2024-03-17 14:11:22 -05:00
11 changed files with 1098 additions and 303 deletions

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@ -2,6 +2,14 @@
All notable changes to this project will be documented in this file. See [standard-version](https://github.com/conventional-changelog/standard-version) for commit guidelines.
### [0.7.9](https://gitea.deepak.science:2222/physics/deepdog/compare/0.7.8...0.7.9) (2024-04-21)
### Features
* adds ability to write custom dmc filters ([ea080ca](https://gitea.deepak.science:2222/physics/deepdog/commit/ea080ca1c7068042ce1e0a222d317f785a6b05f4))
* adds tarucha phase calculation, using spin qubit precession rate noise ([3ae0783](https://gitea.deepak.science:2222/physics/deepdog/commit/3ae0783d00cbe6a76439c1d671f2cff621d8d0a8))
### [0.7.8](https://gitea.deepak.science:2222/physics/deepdog/compare/0.7.7...0.7.8) (2024-02-29)

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@ -0,0 +1,14 @@
from typing import Sequence
from deepdog.direct_monte_carlo.direct_mc import DirectMonteCarloFilter
import numpy
class ComposedDMCFilter(DirectMonteCarloFilter):
def __init__(self, filters: Sequence[DirectMonteCarloFilter]):
self.filters = filters
def filter_samples(self, samples: numpy.ndarray) -> numpy.ndarray:
current_sample = samples
for filter in self.filters:
current_sample = filter.filter_samples(current_sample)
return current_sample

View File

@ -2,7 +2,7 @@ import pdme.model
import pdme.measurement
import pdme.measurement.input_types
import pdme.subspace_simulation
from typing import Tuple, Sequence
from typing import Tuple, Dict, NewType, Any
from dataclasses import dataclass
import logging
import numpy
@ -30,6 +30,20 @@ class DirectMonteCarloConfig:
tag: str = ""
# Aliasing dict as a generic data container
DirectMonteCarloData = NewType("DirectMonteCarloData", Dict[str, Any])
class DirectMonteCarloFilter:
"""
Abstract class for filtering out samples matching some criteria. Initialise with data as needed,
then filter out samples as needed.
"""
def filter_samples(self, samples: numpy.ndarray) -> numpy.ndarray:
raise NotImplementedError
class DirectMonteCarloRun:
"""
A single model Direct Monte Carlo run, currently implemented only using single threading.
@ -65,25 +79,26 @@ class DirectMonteCarloRun:
def __init__(
self,
model_name_pair: Tuple[str, pdme.model.DipoleModel],
measurements: Sequence[pdme.measurement.DotRangeMeasurement],
filter: DirectMonteCarloFilter,
config: DirectMonteCarloConfig,
):
self.model_name, self.model = model_name_pair
self.measurements = measurements
self.dot_inputs = [(measure.r, measure.f) for measure in self.measurements]
# self.measurements = measurements
# self.dot_inputs = [(measure.r, measure.f) for measure in self.measurements]
self.dot_inputs_array = pdme.measurement.input_types.dot_inputs_to_array(
self.dot_inputs
)
# self.dot_inputs_array = pdme.measurement.input_types.dot_inputs_to_array(
# self.dot_inputs
# )
self.config = config
(
self.lows,
self.highs,
) = pdme.measurement.input_types.dot_range_measurements_low_high_arrays(
self.measurements
)
self.filter = filter
# (
# self.lows,
# self.highs,
# ) = pdme.measurement.input_types.dot_range_measurements_low_high_arrays(
# self.measurements
# )
def _single_run(self, seed) -> numpy.ndarray:
rng = numpy.random.default_rng(seed)
@ -93,18 +108,20 @@ class DirectMonteCarloRun:
)
current_sample = sample_dipoles
for di, low, high in zip(self.dot_inputs_array, self.lows, self.highs):
if len(current_sample) < 1:
break
vals = pdme.util.fast_v_calc.fast_vs_for_dipoleses(
numpy.array([di]), current_sample
)
return self.filter.filter_samples(current_sample)
# for di, low, high in zip(self.dot_inputs_array, self.lows, self.highs):
current_sample = current_sample[
numpy.all((vals > low) & (vals < high), axis=1)
]
return current_sample
# if len(current_sample) < 1:
# break
# vals = pdme.util.fast_v_calc.fast_vs_for_dipoleses(
# numpy.array([di]), current_sample
# )
# current_sample = current_sample[
# numpy.all((vals > low) & (vals < high), axis=1)
# ]
# return current_sample
def execute(self) -> DirectMonteCarloResult:
step_count = 0

View File

@ -0,0 +1,143 @@
from numpy import ndarray
from deepdog.direct_monte_carlo.direct_mc import DirectMonteCarloFilter
from typing import Sequence
import pdme.measurement
import pdme.measurement.input_types
import pdme.util.fast_nonlocal_spectrum
import pdme.util.fast_v_calc
import numpy
class SingleDotPotentialFilter(DirectMonteCarloFilter):
def __init__(self, measurements: Sequence[pdme.measurement.DotRangeMeasurement]):
self.measurements = measurements
self.dot_inputs = [(measure.r, measure.f) for measure in self.measurements]
self.dot_inputs_array = pdme.measurement.input_types.dot_inputs_to_array(
self.dot_inputs
)
(
self.lows,
self.highs,
) = pdme.measurement.input_types.dot_range_measurements_low_high_arrays(
self.measurements
)
def filter_samples(self, samples: ndarray) -> ndarray:
current_sample = samples
for di, low, high in zip(self.dot_inputs_array, self.lows, self.highs):
if len(current_sample) < 1:
break
vals = pdme.util.fast_v_calc.fast_vs_for_dipoleses(
numpy.array([di]), current_sample
)
current_sample = current_sample[
numpy.all((vals > low) & (vals < high), axis=1)
]
return current_sample
class DoubleDotSpinQubitFrequencyFilter(DirectMonteCarloFilter):
def __init__(
self,
pair_phase_measurements: Sequence[pdme.measurement.DotPairRangeMeasurement],
):
self.pair_phase_measurements = pair_phase_measurements
self.dot_pair_inputs = [
(measure.r1, measure.r2, measure.f)
for measure in self.pair_phase_measurements
]
self.dot_pair_inputs_array = (
pdme.measurement.input_types.dot_pair_inputs_to_array(self.dot_pair_inputs)
)
(
self.pair_phase_lows,
self.pair_phase_highs,
) = pdme.measurement.input_types.dot_range_measurements_low_high_arrays(
self.pair_phase_measurements
)
def fast_s_spin_qubit_tarucha_nonlocal_dipoleses(
self, dot_pair_inputs: numpy.ndarray, dipoleses: numpy.ndarray
) -> numpy.ndarray:
"""
No error correction here baby.
"""
ps = dipoleses[:, :, 0:3]
ss = dipoleses[:, :, 3:6]
ws = dipoleses[:, :, 6]
r1s = dot_pair_inputs[:, 0, 0:3]
r2s = dot_pair_inputs[:, 1, 0:3]
f1s = dot_pair_inputs[:, 0, 3]
# Don't actually need this
# f2s = dot_pair_inputs[:, 1, 3]
diffses1 = r1s[:, None] - ss[:, None, :]
diffses2 = r2s[:, None] - ss[:, None, :]
norms1 = numpy.linalg.norm(diffses1, axis=3)
norms2 = numpy.linalg.norm(diffses2, axis=3)
alphses1 = (
(
3
* numpy.transpose(
numpy.transpose(
numpy.einsum("abcd,acd->abc", diffses1, ps) / (norms1**2)
)
* numpy.transpose(diffses1)
)[:, :, :, 0]
)
- ps[:, :, 0, numpy.newaxis]
) / (norms1**3)
alphses2 = (
(
3
* numpy.transpose(
numpy.transpose(
numpy.einsum("abcd,acd->abc", diffses2, ps) / (norms2**2)
)
* numpy.transpose(diffses2)
)[:, :, :, 0]
)
- ps[:, :, 0, numpy.newaxis]
) / (norms2**3)
bses = (1 / numpy.pi) * (
ws[:, None, :] / (f1s[:, None] ** 2 + ws[:, None, :] ** 2)
)
return numpy.einsum("...j->...", alphses1 * alphses2 * bses)
def filter_samples(self, samples: ndarray) -> ndarray:
current_sample = samples
for pi, plow, phigh in zip(
self.dot_pair_inputs_array, self.pair_phase_lows, self.pair_phase_highs
):
if len(current_sample) < 1:
break
###
# This should be abstracted out, but we're going to dump it here for time pressure's sake
###
# vals = pdme.util.fast_nonlocal_spectrum.signarg(
# pdme.util.fast_nonlocal_spectrum.fast_s_nonlocal_dipoleses(
# numpy.array([pi]), current_sample
# )
#
vals = pdme.util.fast_nonlocal_spectrum.signarg(
self.fast_s_spin_qubit_tarucha_nonlocal_dipoleses(
numpy.array([pi]), current_sample
)
)
current_sample = current_sample[
numpy.all(
((vals > plow) & (vals < phigh)) | ((vals < plow) & (vals > phigh)),
axis=1,
)
]
return current_sample

View File

@ -66,7 +66,7 @@ def get_a_result_fast_filter_pairs(input) -> int:
return len(current_sample)
def get_a_result_fast_filter_pair_phase_only(input) -> int:
def get_a_result_fast_filter_potential_pair_phase_only(input) -> int:
(
model,
pair_inputs,
@ -102,6 +102,103 @@ def get_a_result_fast_filter_pair_phase_only(input) -> int:
return len(current_sample)
def get_a_result_fast_filter_tarucha_spin_qubit_pair_phase_only(input) -> int:
(
model,
pair_inputs,
pair_phase_lows,
pair_phase_highs,
monte_carlo_count,
seed,
) = input
def fast_s_spin_qubit_tarucha_nonlocal_dipoleses(
dot_pair_inputs: numpy.ndarray, dipoleses: numpy.ndarray
) -> numpy.ndarray:
"""
No error correction here baby.
"""
ps = dipoleses[:, :, 0:3]
ss = dipoleses[:, :, 3:6]
ws = dipoleses[:, :, 6]
r1s = dot_pair_inputs[:, 0, 0:3]
r2s = dot_pair_inputs[:, 1, 0:3]
f1s = dot_pair_inputs[:, 0, 3]
# don't actually need, because we're assuming they're the same frequencies across the pair
# f2s = dot_pair_inputs[:, 1, 3]
diffses1 = r1s[:, None] - ss[:, None, :]
diffses2 = r2s[:, None] - ss[:, None, :]
norms1 = numpy.linalg.norm(diffses1, axis=3)
norms2 = numpy.linalg.norm(diffses2, axis=3)
alphses1 = (
(
3
* numpy.transpose(
numpy.transpose(
numpy.einsum("abcd,acd->abc", diffses1, ps) / (norms1**2)
)
* numpy.transpose(diffses1)
)[:, :, :, 0]
)
- ps[:, :, 0, numpy.newaxis]
) / (norms1**3)
alphses2 = (
(
3
* numpy.transpose(
numpy.transpose(
numpy.einsum("abcd,acd->abc", diffses2, ps) / (norms2**2)
)
* numpy.transpose(diffses2)
)[:, :, :, 0]
)
- ps[:, :, 0, numpy.newaxis]
) / (norms2**3)
bses = (1 / numpy.pi) * (
ws[:, None, :] / (f1s[:, None] ** 2 + ws[:, None, :] ** 2)
)
return numpy.einsum("...j->...", alphses1 * alphses2 * bses)
rng = numpy.random.default_rng(seed)
# TODO: A long term refactor is to pull the frequency stuff out from here. The None stands for max_frequency, which is unneeded in the actually useful models.
sample_dipoles = model.get_monte_carlo_dipole_inputs(
monte_carlo_count, None, rng_to_use=rng
)
current_sample = sample_dipoles
for pi, plow, phigh in zip(pair_inputs, pair_phase_lows, pair_phase_highs):
if len(current_sample) < 1:
break
###
# This should be abstracted out, but we're going to dump it here for time pressure's sake
###
# vals = pdme.util.fast_nonlocal_spectrum.signarg(
# pdme.util.fast_nonlocal_spectrum.fast_s_nonlocal_dipoleses(
# numpy.array([pi]), current_sample
# )
#
vals = pdme.util.fast_nonlocal_spectrum.signarg(
fast_s_spin_qubit_tarucha_nonlocal_dipoleses(
numpy.array([pi]), current_sample
)
)
current_sample = current_sample[
numpy.all(
((vals > plow) & (vals < phigh)) | ((vals < plow) & (vals > phigh)),
axis=1,
)
]
return len(current_sample)
def get_a_result_fast_filter(input) -> int:
model, dot_inputs, lows, highs, monte_carlo_count, seed = input
@ -299,6 +396,7 @@ class RealSpectrumRun:
seeds = seed_sequence.spawn(self.monte_carlo_cycles)
if self.use_pair_measurements:
_logger.debug("using pair measurements")
current_success = sum(
pool.imap_unordered(
get_a_result_fast_filter_pairs,
@ -320,9 +418,11 @@ class RealSpectrumRun:
)
)
elif self.use_pair_phase_measurements:
_logger.debug("using pair phase measurements")
_logger.debug("specifically using tarucha")
current_success = sum(
pool.imap_unordered(
get_a_result_fast_filter_pairs,
get_a_result_fast_filter_tarucha_spin_qubit_pair_phase_only,
[
(
model,

38
do.sh
View File

@ -1,38 +0,0 @@
#!/usr/bin/env bash
# Do - The Simplest Build Tool on Earth.
# Documentation and examples see https://github.com/8gears/do
set -Eeuo pipefail # -e "Automatic exit from bash shell script on error" -u "Treat unset variables and parameters as errors"
build() {
echo "I am ${FUNCNAME[0]}ing"
poetry build
}
test() {
echo "I am ${FUNCNAME[0]}ing"
poetry run flake8 deepdog tests
poetry run mypy deepdog
poetry run pytest
}
fmt() {
poetry run black .
find . -not \( -path "./.*" -type d -prune \) -type f -name "*.py" -exec sed -i -e 's/ /\t/g' {} \;
}
release() {
./scripts/release.sh
}
htmlcov() {
poetry run pytest --cov-report=html
}
all() {
build && test
}
"$@" # <- execute the task
[ "$#" -gt 0 ] || printf "Usage:\n\t./do.sh %s\n" "($(compgen -A function | grep '^[^_]' | paste -sd '|' -))"

145
flake.lock generated
View File

@ -1,28 +1,33 @@
{
"nodes": {
"flake-utils": {
"inputs": {
"systems": "systems"
},
"locked": {
"lastModified": 1648297722,
"narHash": "sha256-W+qlPsiZd8F3XkzXOzAoR+mpFqzm3ekQkJNa+PIh1BQ=",
"lastModified": 1710146030,
"narHash": "sha256-SZ5L6eA7HJ/nmkzGG7/ISclqe6oZdOZTNoesiInkXPQ=",
"owner": "numtide",
"repo": "flake-utils",
"rev": "0f8662f1319ad6abf89b3380dd2722369fc51ade",
"rev": "b1d9ab70662946ef0850d488da1c9019f3a9752a",
"type": "github"
},
"original": {
"owner": "numtide",
"repo": "flake-utils",
"rev": "0f8662f1319ad6abf89b3380dd2722369fc51ade",
"type": "github"
}
},
"flake-utils_2": {
"inputs": {
"systems": "systems_2"
},
"locked": {
"lastModified": 1653893745,
"narHash": "sha256-0jntwV3Z8//YwuOjzhV2sgJJPt+HY6KhU7VZUL0fKZQ=",
"lastModified": 1705309234,
"narHash": "sha256-uNRRNRKmJyCRC/8y1RqBkqWBLM034y4qN7EprSdmgyA=",
"owner": "numtide",
"repo": "flake-utils",
"rev": "1ed9fb1935d260de5fe1c2f7ee0ebaae17ed2fa1",
"rev": "1ef2e671c3b0c19053962c07dbda38332dcebf26",
"type": "github"
},
"original": {
@ -31,29 +36,34 @@
"type": "github"
}
},
"nix-github-actions": {
"inputs": {
"nixpkgs": [
"poetry2nixSrc",
"nixpkgs"
]
},
"locked": {
"lastModified": 1703863825,
"narHash": "sha256-rXwqjtwiGKJheXB43ybM8NwWB8rO2dSRrEqes0S7F5Y=",
"owner": "nix-community",
"repo": "nix-github-actions",
"rev": "5163432afc817cf8bd1f031418d1869e4c9d5547",
"type": "github"
},
"original": {
"owner": "nix-community",
"repo": "nix-github-actions",
"type": "github"
}
},
"nixpkgs": {
"locked": {
"lastModified": 1655087213,
"narHash": "sha256-4R5oQ+OwGAAcXWYrxC4gFMTUSstGxaN8kN7e8hkum/8=",
"lastModified": 1710703777,
"narHash": "sha256-M4CNAgjrtvrxIWIAc98RTYcVFoAgwUhrYekeiMScj18=",
"owner": "NixOS",
"repo": "nixpkgs",
"rev": "37b6b161e536fddca54424cf80662bce735bdd1e",
"type": "github"
},
"original": {
"owner": "NixOS",
"repo": "nixpkgs",
"rev": "37b6b161e536fddca54424cf80662bce735bdd1e",
"type": "github"
}
},
"nixpkgs_2": {
"locked": {
"lastModified": 1655046959,
"narHash": "sha256-gxqHZKq1ReLDe6ZMJSbmSZlLY95DsVq5o6jQihhzvmw=",
"owner": "NixOS",
"repo": "nixpkgs",
"rev": "07bf3d25ce1da3bee6703657e6a787a4c6cdcea9",
"rev": "fc7885fbcea4b782142e06ce2d4d08cf92862004",
"type": "github"
},
"original": {
@ -62,23 +72,27 @@
"type": "github"
}
},
"poetry2nix": {
"poetry2nixSrc": {
"inputs": {
"flake-utils": "flake-utils_2",
"nixpkgs": "nixpkgs_2"
"nix-github-actions": "nix-github-actions",
"nixpkgs": [
"nixpkgs"
],
"systems": "systems_3",
"treefmt-nix": "treefmt-nix"
},
"locked": {
"lastModified": 1654921554,
"narHash": "sha256-hkfMdQAHSwLWlg0sBVvgrQdIiBP45U1/ktmFpY4g2Mo=",
"lastModified": 1708589824,
"narHash": "sha256-2GOiFTkvs5MtVF65sC78KNVxQSmsxtk0WmV1wJ9V2ck=",
"owner": "nix-community",
"repo": "poetry2nix",
"rev": "7b71679fa7df00e1678fc3f1d1d4f5f372341b63",
"rev": "3c92540611f42d3fb2d0d084a6c694cd6544b609",
"type": "github"
},
"original": {
"owner": "nix-community",
"repo": "poetry2nix",
"rev": "7b71679fa7df00e1678fc3f1d1d4f5f372341b63",
"type": "github"
}
},
@ -86,7 +100,72 @@
"inputs": {
"flake-utils": "flake-utils",
"nixpkgs": "nixpkgs",
"poetry2nix": "poetry2nix"
"poetry2nixSrc": "poetry2nixSrc"
}
},
"systems": {
"locked": {
"lastModified": 1681028828,
"narHash": "sha256-Vy1rq5AaRuLzOxct8nz4T6wlgyUR7zLU309k9mBC768=",
"owner": "nix-systems",
"repo": "default",
"rev": "da67096a3b9bf56a91d16901293e51ba5b49a27e",
"type": "github"
},
"original": {
"owner": "nix-systems",
"repo": "default",
"type": "github"
}
},
"systems_2": {
"locked": {
"lastModified": 1681028828,
"narHash": "sha256-Vy1rq5AaRuLzOxct8nz4T6wlgyUR7zLU309k9mBC768=",
"owner": "nix-systems",
"repo": "default",
"rev": "da67096a3b9bf56a91d16901293e51ba5b49a27e",
"type": "github"
},
"original": {
"owner": "nix-systems",
"repo": "default",
"type": "github"
}
},
"systems_3": {
"locked": {
"lastModified": 1681028828,
"narHash": "sha256-Vy1rq5AaRuLzOxct8nz4T6wlgyUR7zLU309k9mBC768=",
"owner": "nix-systems",
"repo": "default",
"rev": "da67096a3b9bf56a91d16901293e51ba5b49a27e",
"type": "github"
},
"original": {
"id": "systems",
"type": "indirect"
}
},
"treefmt-nix": {
"inputs": {
"nixpkgs": [
"poetry2nixSrc",
"nixpkgs"
]
},
"locked": {
"lastModified": 1708335038,
"narHash": "sha256-ETLZNFBVCabo7lJrpjD6cAbnE11eDOjaQnznmg/6hAE=",
"owner": "numtide",
"repo": "treefmt-nix",
"rev": "e504621290a1fd896631ddbc5e9c16f4366c9f65",
"type": "github"
},
"original": {
"owner": "numtide",
"repo": "treefmt-nix",
"type": "github"
}
}
},

View File

@ -1,63 +1,46 @@
{
description = "Application packaged using poetry2nix";
inputs.flake-utils.url = "github:numtide/flake-utils?rev=0f8662f1319ad6abf89b3380dd2722369fc51ade";
inputs.nixpkgs.url = "github:NixOS/nixpkgs?rev=37b6b161e536fddca54424cf80662bce735bdd1e";
inputs.poetry2nix.url = "github:nix-community/poetry2nix?rev=7b71679fa7df00e1678fc3f1d1d4f5f372341b63";
inputs.flake-utils.url = "github:numtide/flake-utils";
inputs.nixpkgs.url = "github:NixOS/nixpkgs";
inputs.poetry2nixSrc = {
url = "github:nix-community/poetry2nix";
inputs.nixpkgs.follows = "nixpkgs";
};
outputs = { self, nixpkgs, flake-utils, poetry2nix }:
{
# Nixpkgs overlay providing the application
overlay = nixpkgs.lib.composeManyExtensions [
poetry2nix.overlay
(final: prev: {
# The application
deepdog = prev.poetry2nix.mkPoetryApplication {
overrides = final.poetry2nix.overrides.withDefaults (self: super: {
# …
# workaround https://github.com/nix-community/poetry2nix/issues/568
pdme = super.pdme.overridePythonAttrs (old: {
buildInputs = old.buildInputs or [ ] ++ [ final.python39.pkgs.poetry-core ];
});
});
projectDir = ./.;
};
deepdogEnv = prev.poetry2nix.mkPoetryEnv {
overrides = final.poetry2nix.overrides.withDefaults (self: super: {
# …
# workaround https://github.com/nix-community/poetry2nix/issues/568
pdme = super.pdme.overridePythonAttrs (old: {
buildInputs = old.buildInputs or [ ] ++ [ final.python39.pkgs.poetry-core ];
});
});
projectDir = ./.;
};
})
];
} // (flake-utils.lib.eachDefaultSystem (system:
outputs = { self, nixpkgs, flake-utils, poetry2nixSrc }:
flake-utils.lib.eachDefaultSystem (system:
let
pkgs = import nixpkgs {
inherit system;
overlays = [ self.overlay ];
};
in
{
apps = {
deepdog = pkgs.deepdog;
};
defaultApp = pkgs.deepdog;
devShell = pkgs.mkShell {
buildInputs = [
pkgs.poetry
pkgs.deepdogEnv
pkgs.deepdog
];
shellHook = ''
export DO_NIX_CUSTOM=1
'';
packages = [ pkgs.nodejs-16_x ];
};
}));
pkgs = nixpkgs.legacyPackages.${system};
poetry2nix = poetry2nixSrc.lib.mkPoetry2Nix { inherit pkgs; };
in {
packages = {
deepdogApp = poetry2nix.mkPoetryApplication {
projectDir = self;
python = pkgs.python39;
preferWheels = true;
};
deepdogEnv = poetry2nix.mkPoetryEnv {
projectDir = self;
python = pkgs.python39;
preferWheels = true;
overrides = poetry2nix.overrides.withDefaults (self: super: {
});
};
default = self.packages.${system}.deepdogEnv;
};
devShells.default = pkgs.mkShell {
inputsFrom = [ self.packages.${system}.deepdogEnv ];
buildInputs = [
pkgs.poetry
self.packages.${system}.deepdogEnv
self.packages.${system}.deepdogApp
pkgs.just
];
shellHook = ''
export DO_NIX_CUSTOM=1
'';
};
}
);
}

54
justfile Normal file
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@ -0,0 +1,54 @@
# execute default build
default: build
# builds the python module using poetry
build:
echo "building..."
poetry build
# print a message displaying whether nix is being used
checknix:
#!/usr/bin/env bash
set -euxo pipefail
if [[ "${DO_NIX_CUSTOM:=0}" -eq 1 ]]; then
echo "In an interactive nix env."
else
echo "Using poetry as runner, no nix detected."
fi
# run all tests
test: fmt
#!/usr/bin/env bash
set -euxo pipefail
if [[ "${DO_NIX_CUSTOM:=0}" -eq 1 ]]; then
echo "testing, using nix..."
flake8 deepdog tests
mypy deepdog
pytest
else
echo "testing..."
poetry run flake8 deepdog tests
poetry run mypy deepdog
poetry run pytest
fi
# format code
fmt:
#!/usr/bin/env bash
set -euxo pipefail
if [[ "${DO_NIX_CUSTOM:=0}" -eq 1 ]]; then
black .
else
poetry run black .
fi
find deepdog -type f -name "*.py" -exec sed -i -e 's/ /\t/g' {} \;
find tests -type f -name "*.py" -exec sed -i -e 's/ /\t/g' {} \;
# release the app, checking that our working tree is clean and ready for release
release:
./scripts/release.sh
htmlcov:
poetry run pytest --cov-report=html

731
poetry.lock generated

File diff suppressed because it is too large Load Diff

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@ -1,6 +1,6 @@
[tool.poetry]
name = "deepdog"
version = "0.7.8"
version = "0.7.9"
description = ""
authors = ["Deepak Mallubhotla <dmallubhotla+github@gmail.com>"]
@ -14,7 +14,7 @@ scipy = "1.10"
pytest = ">=6"
flake8 = "^4.0.1"
pytest-cov = "^4.1.0"
mypy = "^0.971"
mypy = "^1.10"
python-semantic-release = "^7.24.0"
black = "^22.3.0"
syrupy = "^4.0.8"