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Add numpy rules to ruff #2800

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May 15, 2024
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Add numpy rules to ruff #2800

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f176ec3
Add numpy rules to ruff
mraspaud May 13, 2024
f33c3e4
Update np.random usages
mraspaud May 15, 2024
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2 changes: 1 addition & 1 deletion pyproject.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -132,7 +132,7 @@ line-length = 120
[tool.ruff.lint]
# See https://docs.astral.sh/ruff/rules/
# In the future, add "B", "S", "N"
select = ["A", "D", "E", "W", "F", "I", "PT", "TID", "C90", "Q", "T10", "T20"]
select = ["A", "D", "E", "W", "F", "I", "PT", "TID", "C90", "Q", "T10", "T20", "NPY"]

[tool.ruff.lint.per-file-ignores]
"satpy/tests/*" = ["S101"] # assert allowed in tests
Expand Down
29 changes: 15 additions & 14 deletions satpy/tests/reader_tests/_li_test_utils.py
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Expand Up @@ -20,6 +20,7 @@
import xarray as xr

from satpy.tests.reader_tests.test_netcdf_utils import FakeNetCDF4FileHandler
from satpy.tests.utils import RANDOM_GEN

# mapping of netcdf type code to numpy data type:
TYPE_MAP = {
Expand All @@ -44,7 +45,7 @@ def l2_le_schema(settings=None):
nfilters = settings.get("num_filters", 2)

def rand_u16(num):
return np.random.randint(low=0, high=np.iinfo(np.uint16).max - 1, size=num, dtype=np.uint16)
return RANDOM_GEN.integers(low=0, high=np.iinfo(np.uint16).max - 1, size=num, dtype=np.uint16)

return {
"providers": settings.get("providers", {}),
Expand Down Expand Up @@ -100,7 +101,7 @@ def rand_u16(num):
"scale_factor": 0.004,
"add_offset": 0.0,
"long_name": "L2 filter results",
"default_data": lambda: np.random.randint(low=0, high=255, size=(nobs, nfilters), dtype=np.uint8)
"default_data": lambda: RANDOM_GEN.integers(low=0, high=255, size=(nobs, nfilters), dtype=np.uint8)
},
"epoch_time": {
"format": "f8",
Expand Down Expand Up @@ -212,13 +213,13 @@ def l2_lef_schema(settings=None):
"long_name": "Radiance of Flash",
"standard_name": "radiance",
"units": "mW.m-2.sr-1",
"default_data": lambda: np.clip(np.round(np.random.normal(500, 100, nobs)), 1, 2 ** 16 - 1)
"default_data": lambda: np.clip(np.round(RANDOM_GEN.normal(500, 100, nobs)), 1, 2 ** 16 - 1)
},
"event_filter_qa": {
"format": "u1",
"shape": ("events",),
"long_name": "L2 event pre-filtering quality assurance value",
"default_data": lambda: np.random.randint(1, 2 ** 8 - 1, nobs)
"default_data": lambda: RANDOM_GEN.integers(1, 2 ** 8 - 1, nobs)
},
"epoch_time": {
"format": "f8",
Expand All @@ -232,21 +233,21 @@ def l2_lef_schema(settings=None):
"shape": ("events",),
"long_name": "Time offset from epoch time",
"units": "seconds",
"default_data": lambda: np.random.uniform(1, 2 ** 31 - 1, nobs)
"default_data": lambda: RANDOM_GEN.uniform(1, 2 ** 31 - 1, nobs)
},
"detector_row": {
"format": "u2",
"shape": ("events",),
"long_name": "Detector row position of event pixel",
"units": "1",
"default_data": lambda: np.random.randint(1, 1000, nobs)
"default_data": lambda: RANDOM_GEN.integers(1, 1000, nobs)
},
"detector_column": {
"format": "u2",
"shape": ("events",),
"long_name": "Detector column position of event pixel",
"units": "1",
"default_data": lambda: np.random.randint(1, 1000, nobs)
"default_data": lambda: RANDOM_GEN.integers(1, 1000, nobs)
},
}
}
Expand Down Expand Up @@ -328,7 +329,7 @@ def l2_lfl_schema(settings=None):
"long_name": "Radiance of Flash",
"standard_name": "radiance",
"units": "mW.m-2.sr-1",
"default_data": lambda: np.round(np.random.normal(500, 100, nobs))
"default_data": lambda: np.round(RANDOM_GEN.normal(500, 100, nobs))
},
"flash_duration": {
"format": "u2",
Expand All @@ -343,15 +344,15 @@ def l2_lfl_schema(settings=None):
"shape": ("flashes",),
"long_name": "L2 filtered flash confidence",
"standard_name": "flash_filter_confidence",
"default_data": lambda: np.clip(np.round(np.random.normal(20, 10, nobs)), 1, 2 ** 7 - 1)
"default_data": lambda: np.clip(np.round(RANDOM_GEN.normal(20, 10, nobs)), 1, 2 ** 7 - 1)
},
"flash_footprint": {
"format": "u2",
"shape": ("flashes",),
"long_name": "Flash footprint size",
"standard_name": "flash_footprint",
"units": "L1 grid pixels",
"default_data": lambda: np.maximum(1, np.round(np.random.normal(5, 3, nobs)))
"default_data": lambda: np.maximum(1, np.round(RANDOM_GEN.normal(5, 3, nobs)))
},
"flash_id": {
"format": "u4",
Expand All @@ -367,7 +368,7 @@ def l2_lfl_schema(settings=None):
"units": "seconds since 2000-01-01 00:00:00.0",
"standard_name": "time",
"precision": "1 millisecond",
"default_data": lambda: np.random.uniform(stime, etime, nobs)
"default_data": lambda: RANDOM_GEN.uniform(stime, etime, nobs)
},
"l1b_geolocation_warning": {
"format": "i1",
Expand Down Expand Up @@ -437,7 +438,7 @@ def l2_af_schema(settings=None):
"flash_accumulation": {
"format": "u2",
"shape": ("pixels",),
"default_data": lambda: np.clip(np.round(np.random.normal(1, 2, nobs)), 1, 2 ** 16 - 1)
"default_data": lambda: np.clip(np.round(RANDOM_GEN.normal(1, 2, nobs)), 1, 2 ** 16 - 1)
},
"mtg_geos_projection": mtg_geos_projection(),
"x": fci_grid_definition("X", nobs),
Expand Down Expand Up @@ -495,7 +496,7 @@ def l2_afr_schema(settings=None):
"long_name": "Area averaged flash radiance accumulation",
"grid_mapping": "mtg_geos_projection",
"coordinate": "sparse: x y",
"default_data": lambda: np.random.randint(low=1, high=6548, size=(120), dtype=np.int16)
"default_data": lambda: RANDOM_GEN.integers(low=1, high=6548, size=(120), dtype=np.int16)
},
"accumulation_start_times": {
"format": "f4",
Expand Down Expand Up @@ -538,7 +539,7 @@ def fci_grid_definition(axis, nobs):
"standard_name": standard_name,
"units": "radian",
"valid_range": np.asarray([1, 5568]),
"default_data": lambda: np.clip(np.round(np.random.normal(2000, 500, nobs)), 1, 2 ** 16 - 1)
"default_data": lambda: np.clip(np.round(RANDOM_GEN.normal(2000, 500, nobs)), 1, 2 ** 16 - 1)
}


Expand Down
17 changes: 9 additions & 8 deletions satpy/tests/reader_tests/test_epic_l1b_h5.py
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Expand Up @@ -25,14 +25,15 @@
import pytest

from satpy.readers.epic_l1b_h5 import CALIB_COEFS

b317_data = np.random.uniform(low=0, high=5200, size=(100, 100))
b688_data = np.random.uniform(low=0, high=5200, size=(100, 100))
sza_data = np.random.uniform(low=0, high=100, size=(100, 100))
vaa_data = np.random.uniform(low=-180, high=180, size=(100, 100))
lon_data = np.random.uniform(low=-90, high=90, size=(100, 100))
lat_data = np.random.uniform(low=-180, high=180, size=(100, 100))
mas_data = np.random.choice([0, 1], size=(100, 100))
from satpy.tests.utils import RANDOM_GEN

b317_data = RANDOM_GEN.uniform(low=0, high=5200, size=(100, 100))
b688_data = RANDOM_GEN.uniform(low=0, high=5200, size=(100, 100))
sza_data = RANDOM_GEN.uniform(low=0, high=100, size=(100, 100))
vaa_data = RANDOM_GEN.uniform(low=-180, high=180, size=(100, 100))
lon_data = RANDOM_GEN.uniform(low=-90, high=90, size=(100, 100))
lat_data = RANDOM_GEN.uniform(low=-180, high=180, size=(100, 100))
mas_data = RANDOM_GEN.choice([0, 1], size=(100, 100))


@pytest.fixture()
Expand Down
4 changes: 2 additions & 2 deletions satpy/tests/reader_tests/test_generic_image.py
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Expand Up @@ -24,7 +24,7 @@
import pytest
import xarray as xr

from satpy.tests.utils import make_dataid
from satpy.tests.utils import RANDOM_GEN, make_dataid


class TestGenericImage(unittest.TestCase):
Expand Down Expand Up @@ -62,7 +62,7 @@ def setUp(self):
a__[:10, :10] = 0
a__ = da.from_array(a__, chunks=(50, 50))

r_nan__ = np.random.uniform(0., 1., size=(self.y_size, self.x_size))
r_nan__ = RANDOM_GEN.uniform(0., 1., size=(self.y_size, self.x_size))
r_nan__[:10, :10] = np.nan
r_nan__ = da.from_array(r_nan__, chunks=(50, 50))

Expand Down
9 changes: 5 additions & 4 deletions satpy/tests/reader_tests/test_goci2_l2_nc.py
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Expand Up @@ -24,6 +24,7 @@
from pytest_lazyfixture import lazy_fixture

from satpy import Scene
from satpy.tests.utils import RANDOM_GEN

# NOTE:
# The following fixtures are not defined in this file, but are used and injected by Pytest:
Expand Down Expand Up @@ -78,7 +79,7 @@ def _create_bad_lon_lat():
@pytest.fixture(scope="session")
def ac_file(tmp_path_factory):
"""Create a fake atmospheric correction product."""
data = np.random.random((10, 10))
data = RANDOM_GEN.random((10, 10))
RhoC = xr.Dataset(
{"RhoC_555": (["number_of_lines", "pixels_per_line"], data)},
coords={"number_of_lines": np.arange(10), "pixels_per_line": np.arange(10)},
Expand All @@ -102,7 +103,7 @@ def ac_file(tmp_path_factory):
@pytest.fixture(scope="module")
def iop_file(tmp_path_factory):
"""Create a fake IOP product."""
data = np.random.random((10, 10))
data = RANDOM_GEN.random((10, 10))
a = xr.Dataset(
{"a_total_555": (["number_of_lines", "pixels_per_line"], data)},
coords={"number_of_lines": np.arange(10), "pixels_per_line": np.arange(10)},
Expand All @@ -124,7 +125,7 @@ def iop_file(tmp_path_factory):
@pytest.fixture(scope="module")
def generic_file(tmp_path_factory):
"""Create a fake ouput product like Chl, Zsd etc."""
data = np.random.random((10, 10))
data = RANDOM_GEN.random((10, 10))
geophysical_data = xr.Dataset(
{"Chl": (["number_of_lines", "pixels_per_line"], data)},
coords={"number_of_lines": np.arange(10), "pixels_per_line": np.arange(10)},
Expand All @@ -141,7 +142,7 @@ def generic_file(tmp_path_factory):
@pytest.fixture(scope="module")
def generic_bad_file(tmp_path_factory):
"""Create a PP product with lon/lat base name missing."""
data = np.random.random((10, 10))
data = RANDOM_GEN.random((10, 10))
geophysical_data = xr.Dataset(
{"PP": (["number_of_lines", "pixels_per_line"], data)},
coords={"number_of_lines": np.arange(10), "pixels_per_line": np.arange(10)},
Expand Down
7 changes: 4 additions & 3 deletions satpy/tests/reader_tests/test_hrit_base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -30,6 +30,7 @@

from satpy.readers import FSFile
from satpy.readers.hrit_base import HRITFileHandler, decompress, get_xritdecompress_cmd, get_xritdecompress_outfile
from satpy.tests.utils import RANDOM_GEN

# NOTE:
# The following fixtures are not defined in this file, but are used and injected by Pytest:
Expand Down Expand Up @@ -145,9 +146,9 @@ def create_stub_hrit(filename, open_fun=open, meta=mda):
lines = meta["number_of_lines"]
cols = meta["number_of_columns"]
total_bits = lines * cols * nbits
arr = np.random.randint(0, 256,
size=int(total_bits / 8),
dtype=np.uint8)
arr = RANDOM_GEN.integers(0, 256,
size=int(total_bits / 8),
dtype=np.uint8)
with open_fun(filename, mode="wb") as fd:
fd.write(b" " * meta["total_header_length"])
bytes_data = arr.tobytes()
Expand Down
8 changes: 4 additions & 4 deletions satpy/tests/reader_tests/test_insat3d_img_l1b_h5.py
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Expand Up @@ -16,7 +16,7 @@
open_dataset,
open_datatree,
)
from satpy.tests.utils import make_dataid
from satpy.tests.utils import RANDOM_GEN, make_dataid

# NOTE:
# The following fixtures are not defined in this file, but are used and injected by Pytest:
Expand All @@ -30,10 +30,10 @@
alb_units = "%"
temp_units = "K"
chunks_1km = (1, 46, 1126)
values_1km = np.random.randint(0, 1000, shape_1km, dtype=np.uint16)
values_1km = RANDOM_GEN.integers(0, 1000, shape_1km, dtype=np.uint16)
values_1km[0, 0, 0] = 0
values_4km = np.random.randint(0, 1000, shape_4km, dtype=np.uint16)
values_8km = np.random.randint(0, 1000, shape_8km, dtype=np.uint16)
values_4km = RANDOM_GEN.integers(0, 1000, shape_4km, dtype=np.uint16)
values_8km = RANDOM_GEN.integers(0, 1000, shape_8km, dtype=np.uint16)

values_by_resolution = {1000: values_1km,
4000: values_4km,
Expand Down
13 changes: 7 additions & 6 deletions satpy/tests/reader_tests/test_mirs.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,6 +31,7 @@
from satpy.dataset import DataID
from satpy.readers import load_reader
from satpy.readers.yaml_reader import FileYAMLReader
from satpy.tests.utils import RANDOM_GEN

METOP_FILE = "IMG_SX.M2.D17037.S1601.E1607.B0000001.WE.HR.ORB.nc"
NPP_MIRS_L2_SWATH = "NPR-MIRS-IMG_v11r6_npp_s201702061601000_e201702061607000_c202012201658410.nc"
Expand Down Expand Up @@ -77,7 +78,7 @@

def fake_coeff_from_fn(fn):
"""Create Fake Coefficients."""
ameans = np.random.uniform(261, 267, N_CHANNEL)
ameans = RANDOM_GEN.uniform(261, 267, N_CHANNEL)
locations = [
[1, 2],
[1, 2],
Expand Down Expand Up @@ -117,7 +118,7 @@ def fake_coeff_from_fn(fn):
str_coeff = " ".join([str(x) for x in random_coeff])
random_means = np.zeros(all_nchx[nx])
str_means = " ".join([str(x) for x in random_means])
error_val = np.random.uniform(0, 4)
error_val = RANDOM_GEN.uniform(0, 4)
coeffs_line = " {:>2} {:>2} {} {} {}\n".format(idx, fov,
str_coeff,
str_means,
Expand All @@ -138,15 +139,15 @@ def _get_datasets_with_attributes(**kwargs):
"_FillValue": -999,
"valid_range": [0, 50000]},
dims=("Scanline", "Field_of_view", "Channel"))
rr = xr.DataArray(np.random.randint(100, 500, size=(N_SCANLINE, N_FOV), dtype=np.int16),
rr = xr.DataArray(RANDOM_GEN.integers(100, 500, size=(N_SCANLINE, N_FOV), dtype=np.int16),
attrs={"long_name": "Rain Rate (mm/hr)",
"units": "mm/hr",
"coordinates": "Longitude Latitude",
"scale_factor": 0.1,
"_FillValue": -999,
"valid_range": [0, 1000]},
dims=("Scanline", "Field_of_view"))
sfc_type = xr.DataArray(np.random.randint(0, 4, size=(N_SCANLINE, N_FOV), dtype=np.int16),
sfc_type = xr.DataArray(RANDOM_GEN.integers(0, 4, size=(N_SCANLINE, N_FOV), dtype=np.int16),
attrs={"description": "type of surface:0-ocean," +
"1-sea ice,2-land,3-snow",
"units": "1",
Expand Down Expand Up @@ -187,12 +188,12 @@ def _get_datasets_with_less_attributes():
attrs={"long_name": "Channel Temperature (K)",
"scale_factor": 0.01},
dims=("Scanline", "Field_of_view", "Channel"))
rr = xr.DataArray(np.random.randint(100, 500, size=(N_SCANLINE, N_FOV), dtype=np.int16),
rr = xr.DataArray(RANDOM_GEN.integers(100, 500, size=(N_SCANLINE, N_FOV), dtype=np.int16),
attrs={"long_name": "Rain Rate (mm/hr)",
"scale_factor": 0.1},
dims=("Scanline", "Field_of_view"))

sfc_type = xr.DataArray(np.random.randint(0, 4, size=(N_SCANLINE, N_FOV), dtype=np.int16),
sfc_type = xr.DataArray(RANDOM_GEN.integers(0, 4, size=(N_SCANLINE, N_FOV), dtype=np.int16),
attrs={"description": "type of surface:0-ocean," +
"1-sea ice,2-land,3-snow"},
dims=("Scanline", "Field_of_view"))
Expand Down
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