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someone did a reformatting
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@frl000
frl000 committed Nov 30, 2023
1 parent 4ef6315 commit 20b1c1f
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Showing 2 changed files with 48 additions and 36 deletions.
16 changes: 8 additions & 8 deletions src/ospx/watch/cli/watchCosim.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -70,7 +70,7 @@ def _argparser() -> argparse.ArgumentParser:
help=("console output will be quiet."),
default=False,
)

_ = console_verbosity.add_argument(
"-t",
"--timeline",
Expand Down Expand Up @@ -171,13 +171,13 @@ def main():
# Dispatch to _main(), which takes care of processing the arguments and invoking the API.
_main(
watch_dict_file_name=watch_dict_file_name,
converge = converge,
plot = plot,
dump = dump,
skip_values = skip,
latest_values = latest,
scale_factor = scale_factor,
timeline_data = timeline_data,
converge=converge,
plot=plot,
dump=dump,
skip_values=skip,
latest_values=latest,
scale_factor=scale_factor,
timeline_data=timeline_data,
)


Expand Down
68 changes: 40 additions & 28 deletions src/ospx/watch/watchCosim.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -120,23 +120,25 @@ def plot(self, converge: bool = False):

while True: # do as long as not interrupted
df = self._read_csv_files_into_dataframe()

# cumulate counter for termination if no changes
if df_row_size == len(df):
terminate_loops += 1
else:
terminate_loops = 0

df_row_size = len(df)
df_col_size = len(list(df)) - 1 # reduced by one because 1st col is time column, frl: check multiple datasources

df_col_size = (
len(list(df)) - 1
) # reduced by one because 1st col is time column, frl: check multiple datasources

# axs = [None for x in range(df_col_size)]
axs: MutableSequence[Axes] = []
plot: Axes
time_key = list(df)[0]
for index in range(df_col_size):
current_key = list(df)[index + 1] # 0 is time column and thus removed, frl: check multiple dataframes

plot = self.figure.add_subplot(self.max_row, self.number_of_columns, index + 1)

try:
Expand All @@ -151,7 +153,7 @@ def plot(self, converge: bool = False):
pass
except Exception as e:
logger.exception(e)

# subplot.set_title(currentKey, fontsize=10)
_ = plot.grid(color="#66aa88", linestyle="--")
_ = plot.xaxis.set_tick_params(labelsize=8)
Expand Down Expand Up @@ -217,8 +219,8 @@ def dump(self):
"max": _max,
}
if self.timeline_data:
result_dict[header].update({'values':values})
result_dict[header].update({"values": values})

# debug
# result_dict.update({'_datasources':self.data_sources})
result_dict_name = "-".join([self.title, "resultDict"])
Expand All @@ -239,8 +241,10 @@ def _define_data_source_properties_for_plotting(self):
- column names (= variable names)
"""

#pattern = re.compile(r"(^#|\s+\[.*?\]$)")
pattern = re.compile(r"(^#{0,2}\s*|\s+\[.*?\]$)") # frl 2023-11-07 remove all leading #'s and spaces and all trailing [.*]'s
# pattern = re.compile(r"(^#|\s+\[.*?\]$)")
pattern = re.compile(
r"(^#{0,2}\s*|\s+\[.*?\]$)"
) # frl 2023-11-07 remove all leading #'s and spaces and all trailing [.*]'s

for (
data_source_name,
Expand All @@ -256,50 +260,52 @@ def _define_data_source_properties_for_plotting(self):
data_header = f.readline().strip().split(self.delimiter)
if not data_header:
continue
time_column: int = 0 #frl 2023-11-07 default first column

time_column: int = 0 # frl 2023-11-07 default first column
if "timeColumn" in data_source_properties and isinstance(data_source_properties["timeColumn"], int):
time_column = data_source_properties["timeColumn"]

_time_name: str = data_header[time_column]
data_source_properties.update({"timeName": _time_name})
_display_time_name: str = pattern.sub("", _time_name)
data_source_properties.update({"displayTimeName": _display_time_name})

data_columns: List[int] = []
#read_only_shortlisted_columns: bool = False #flr 2023-11-07 greedy approach needs to be updated on demand
read_only_shortlisted_columns = True if 'dataColumns' in data_source_properties else False
# read_only_shortlisted_columns: bool = False #flr 2023-11-07 greedy approach needs to be updated on demand

read_only_shortlisted_columns = True if "dataColumns" in data_source_properties else False
if read_only_shortlisted_columns:
# if columns were explicitely specified (shortlisted) in watch dict:
# Read only shortlisted columns.
if "dataColumns" in data_source_properties and isinstance(data_source_properties["dataColumns"], List):
if "dataColumns" in data_source_properties and isinstance(
data_source_properties["dataColumns"], List
):
data_columns = [int(col) for col in data_source_properties["dataColumns"]]
#else: frl 2023-11-07 simx heritage?
# else: frl 2023-11-07 simx heritage?
# # if columns were not explicitely specified in watch dict:
# # Read all columns except settings.
# columns.extend(
# index
# for index, col_name in enumerate(data_header)
# if not re.match(r"^(settings)", col_name)
# )

_column_names: List[str] = [data_header[column] for column in data_columns]
data_source_properties.update({"colNames": _column_names})
_display_column_names: List[str] = [
pattern.sub("", col_name) for col_name in data_source_properties["colNames"] # type: ignore
]
#_display_column_names = ["Time", "StepCount"] + [
# _display_column_names = ["Time", "StepCount"] + [
_display_column_names = [
data_source_name + "|" + col_name
for col_name in _display_column_names
# if col_name not in ["Time", "StepCount"] frl 2023-11-07
]

data_source_properties.update({"displayColNames": _display_column_names})
data_source_properties.update({"xColumn": time_column})
data_source_properties.update({"yColumns": data_columns})

return

def _initialize_plot(self):
Expand All @@ -319,9 +325,13 @@ def _initialize_plot(self):
)
self.terminate = False

df = self._read_csv_files_into_dataframe() # do it once to find the number of respective columns of all datasources
self.number_of_subplots = len(list(df)) - 1 # one of the columns is the abscissa, frl: check if this works for multiple datasources and merged time columns

df = (
self._read_csv_files_into_dataframe()
) # do it once to find the number of respective columns of all datasources
self.number_of_subplots = (
len(list(df)) - 1
) # one of the columns is the abscissa, frl: check if this works for multiple datasources and merged time columns

self.number_of_columns = int(sqrt(self.number_of_subplots - 1)) + 1
self.max_row = int(self.number_of_subplots / self.number_of_columns - 0.1) + 1
return
Expand Down Expand Up @@ -349,13 +359,13 @@ def _read_csv_files_into_dataframe(self) -> DataFrame:
[data_source_properties["displayTimeName"]] + data_source_properties["displayColNames"], # type: ignore
)
)

_column_names: List[str] = []
if "colNames" in data_source_properties and isinstance(data_source_properties["colNames"], List):
_column_names = [str(col_name) for col_name in data_source_properties["colNames"]]
if "timeName" in data_source_properties and isinstance(data_source_properties["timeName"], str):
_column_names = [data_source_properties["timeName"]] + _column_names

if "csvFile" in data_source_properties and isinstance(data_source_properties["csvFile"], str):
df_single_data_source: DataFrame
df_single_data_source = pd.read_csv(
Expand All @@ -377,7 +387,9 @@ def _read_csv_files_into_dataframe(self) -> DataFrame:
# df_all_data_sources = pd.concat([df_all_data_sources, df_single_data_source], axis=1)

# df_all_data_sources = pd.concat([df_all_data_sources, df_single_data_source], ignore_index=True)
df_all_data_sources = pd.concat([df_all_data_sources, df_single_data_source]) #frl check for duplicated timeName columns for multiple datasources
df_all_data_sources = pd.concat(
[df_all_data_sources, df_single_data_source]
) # frl check for duplicated timeName columns for multiple datasources

# potential solution
# interpolating non-matching time data
Expand Down

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