Commit 38a2a42f authored by Paulo Medeiros's avatar Paulo Medeiros
Browse files

More linting fixes

parent 2efc8e58
......@@ -210,7 +210,9 @@ def generate_control_card():
value=5,
step=1,
required=True,
style=dict(display="table-cell",),
style=dict(
display="table-cell",
),
),
],
style=dict(display="table-cell"),
......@@ -233,7 +235,9 @@ def generate_control_card():
min=2,
value=5,
step=1,
style=dict(display="table-cell",),
style=dict(
display="table-cell",
),
),
],
style=dict(display="table-cell"),
......@@ -250,7 +254,9 @@ def generate_control_card():
inputMode="numeric",
min=0.0,
value=10.0,
style=dict(display="table-cell",),
style=dict(
display="table-cell",
),
),
],
style=dict(display="table-cell"),
......@@ -391,8 +397,14 @@ def indicator(text, id_value):
children=[
html.Div(
children=[
html.P(id=id_value, className="indicator_value",),
html.P(text, className="indicator_text",),
html.P(
id=id_value,
className="indicator_value",
),
html.P(
text,
className="indicator_text",
),
],
),
],
......@@ -423,7 +435,11 @@ def generate_right_column_elements():
children = [
html.Div(
id="clustering_plot_div",
children=[dcc.Graph(id="clustering_plot",)],
children=[
dcc.Graph(
id="clustering_plot",
)
],
),
html.Div(
id="clustered_data_table_card",
......@@ -438,7 +454,9 @@ def generate_right_column_elements():
sort_action="native",
filter_action="native",
# Styling
style_cell=dict(padding="10px",),
style_cell=dict(
padding="10px",
),
style_header=dict(
backgroundColor="rgb(2,21,70)",
color="white",
......@@ -486,7 +504,10 @@ app.layout = html.Div(
children=[
generate_indicators(),
html.B("Visualisation of Clusters"),
html.Div(id="calculated_dist", children=[],),
html.Div(
id="calculated_dist",
children=[],
),
html.Hr(),
dcc.Loading(
# Embed the the right-hand side column inside a dcc.Loading
......@@ -674,7 +695,9 @@ def run_clustering_and_make_plot(
time_start_clustering = time.time()
logger.info("Running %s...", method)
df = cluster_netatmo_obs(
df=df, config=clustering_config, calc_silhouette_samples=True,
df=df,
config=clustering_config,
calc_silhouette_samples=True,
)
df = sort_df_by_cluster_size(df)
time_end_clustering = time.time()
......
......@@ -47,7 +47,10 @@ def description_card():
children=[
html.H5("NetAtmo Data Explorer"),
html.H3("NetAtmo Data Explorer Dashboard"),
html.Div(id="intro", children="An aid to explore NetAtmo data",),
html.Div(
id="intro",
children="An aid to explore NetAtmo data",
),
],
style={"text-align": "center"},
)
......
......@@ -307,7 +307,9 @@ def run_clustering_on_df(
metric="precomputed",
).fit(distance_matrix)
logger.debug(
" * Done with %s. Elapsed: %.2fs", method, time.time() - tstart,
" * Done with %s. Elapsed: %.2fs",
method,
time.time() - tstart,
)
# Update df with cluster label info. It is important that this is done
# right before calling filter_outliers, as the filter_outliers function
......
......@@ -357,7 +357,9 @@ def parsed_path(path):
with config_section("general") as section:
# in/our dirs
config_metadata.register(
"data_rootdir", default=".", astype=parsed_path,
"data_rootdir",
default=".",
astype=parsed_path,
)
config_metadata.register(
"outdir",
......
......@@ -420,7 +420,10 @@ class Domain:
)
# (d) Set _grid attr
return DomainGrid(
xaxis=grid_xaxis, yaxis=grid_yaxis, proj=proj, tstep=tstep,
xaxis=grid_xaxis,
yaxis=grid_yaxis,
proj=proj,
tstep=tstep,
)
self._grid = init_grid(ngrid_lonlat, grid_spacing, ezone_ngrid)
......
......@@ -588,7 +588,9 @@ class HollowSymmetricMatrix(np.lib.mixins.NDArrayOperatorsMixin):
new_data = self[indices[:, np.newaxis], indices]
return self.__class__(
new_data, dtype=self.dtype, optimize_mode=self.optimize_mode,
new_data,
dtype=self.dtype,
optimize_mode=self.optimize_mode,
)
def convert_to_dense_storage(self):
......
......@@ -354,7 +354,11 @@ def rm_overlapping_stations(df):
overlapping_stations = (
df[["id", "lat", "lon"]]
.round(6)
.groupby(["lat", "lon"], as_index=False, sort=False,)
.groupby(
["lat", "lon"],
as_index=False,
sort=False,
)
.filter(lambda grp: len(grp["id"].unique()) != 1)["id"]
.unique()
)
......@@ -397,7 +401,11 @@ def remove_duplicates_within_cycle(df, dtg):
msg += "Keeping only the one closest to the DTG: "
msg += "%s obs now became %s"
logger.debug(
msg, n_stations_with_duplicates, dtg, orig_nobs, new_nobs,
msg,
n_stations_with_duplicates,
dtg,
orig_nobs,
new_nobs,
)
return df
......
......@@ -182,7 +182,10 @@ def _filter_outliers_iterative(
# We use "-2" as a "removed by refining methods" flag
n_removed_old = np.count_nonzero(df[:, -1] == -2)
df = _filter_outliers_iterative_one_iter(
df, max_n_stdev_around_mean, truncate=trunc_perc, weights=weights,
df,
max_n_stdev_around_mean,
truncate=trunc_perc,
weights=weights,
)
n_removed_new = np.count_nonzero(df[:, -1] == -2)
n_removed_this_iter = n_removed_new - n_removed_old
......
......@@ -238,8 +238,16 @@ def get_domain_fig(
traceorder="reversed",
),
geo=dict(
lataxis=dict(range=latrange, showgrid=True, dtick=10,),
lonaxis=dict(range=lonrange, showgrid=True, dtick=15,),
lataxis=dict(
range=latrange,
showgrid=True,
dtick=10,
),
lonaxis=dict(
range=lonrange,
showgrid=True,
dtick=15,
),
),
)
......@@ -436,7 +444,10 @@ def make_clustering_fig(df, domain, **kwargs):
trace_visible = True
trace = get_obs_scattergeo_trace(
cluster_df, trace_name=label, marker=marker, visible=trace_visible,
cluster_df,
trace_name=label,
marker=marker,
visible=trace_visible,
)
fig.add_trace(trace)
......@@ -526,7 +537,9 @@ def generate_single_frame(df, dataset_var, frame_duration, frame=None):
opacity=0.5,
line=dict(color="black", width=0.25),
colorbar=dict(
titleside="right", ticks="outside", showticksuffix="last",
titleside="right",
ticks="outside",
showticksuffix="last",
),
)
trace = get_obs_scattergeo_trace(df, marker=marker)
......@@ -581,7 +594,10 @@ def init_fig_dict(domain, dataset_var, frame_duration):
args=[
None,
dict(
frame=dict(duration=frame_duration, redraw=True,),
frame=dict(
duration=frame_duration,
redraw=True,
),
fromcurrent=True,
transition=dict(
duration=frame_duration / 2,
......@@ -615,9 +631,15 @@ def init_fig_dict(domain, dataset_var, frame_duration):
y=0,
pad=dict(b=10, t=50),
currentvalue=dict(
font=dict(size=20), prefix="DTG: ", visible=True, xanchor="right",
font=dict(size=20),
prefix="DTG: ",
visible=True,
xanchor="right",
),
transition=dict(
duration=frame_duration / 2,
easing="cubic-in-out",
),
transition=dict(duration=frame_duration / 2, easing="cubic-in-out",),
steps=[],
)
......
......@@ -284,7 +284,10 @@ def _input2output_single_dtg(
logger = get_logger(__name__, loglevel)
logger.debug(
"Reading data for %sDTG=%s%s...", logcolor.cyan, dtg, logcolor.reset,
"Reading data for %sDTG=%s%s...",
logcolor.cyan,
dtg,
logcolor.reset,
)
try:
# read_netatmo_data_for_dtg will raise DataNotFoundError if
......@@ -385,7 +388,9 @@ def netatmoqc_input2output(
outdir = Path()
logger.info(
"%sSaving selected observations...%s", logcolor.cyan, logcolor.reset,
"%sSaving selected observations...%s",
logcolor.cyan,
logcolor.reset,
)
outdir_csv = None
......@@ -393,7 +398,10 @@ def netatmoqc_input2output(
if save_csv:
outdir_csv = Path(outdir) / "csv_files"
logger.info(
"%s> CSV outdir:%s %s", logcolor.cyan, logcolor.reset, outdir_csv,
"%s> CSV outdir:%s %s",
logcolor.cyan,
logcolor.reset,
outdir_csv,
)
if save_obsoul:
outdir_obsoul = Path(outdir) / "obsoul_files"
......
Supports Markdown
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment