Merge branch 'bugfix/fix-cli' into develop

develop
Chris Leaman 6 years ago
commit c4d9e02821

@ -48,36 +48,43 @@ impacts: ./data/interim/impacts_forecasted_foreshore_slope_sto06.csv ./data/inte
./data/raw/processed_shorelines/orientations.mat: ./data/raw/processed_shorelines/profiles.mat ./data/raw/processed_shorelines/orientations.mat: ./data/raw/processed_shorelines/profiles.mat
$(MATLAB_PATH) -nosplash -r "cd $(CURRENT_DIR); run('./src/data/beach_orientations.m'); quit" $(MATLAB_PATH) -nosplash -r "cd $(CURRENT_DIR); run('./src/data/beach_orientations.m'); quit"
# # Produces a .csv of sites where our beach cross-sections are located
# ./data/interim/sites.csv ./data/interim/profiles.csv: ./data/raw/processed_shorelines/profiles.mat
# activate ./.venv && python ./src/data/parse_mat.py create-sites-and-profiles-csv \
# --profiles-mat "./data/raw/processed_shorelines/profiles.mat" \
# --profiles-output-file "./data/interim/profiles.csv" \
# --sites-output-file "./data/interim/sites.csv"
# Produces a .csv of sites where our beach cross-sections are located # Produces a .csv of sites where our beach cross-sections are located
./data/interim/sites.csv ./data/interim/profiles.csv: ./data/raw/processed_shorelines/profiles.mat ./data/interim/sites.csv ./data/interim/profiles.csv: ./data/raw/processed_shorelines/profiles.mat
activate ./.venv && python ./src/data/parse_mat.py create-sites-and-profiles-csv \ activate ./.venv && python ./src/cli.py create-sites-and-profiles-csv \
--profiles-mat "./data/raw/processed_shorelines/profiles.mat" \ --profiles-mat "./data/raw/processed_shorelines/profiles.mat" \
--profiles-output-file "./data/interim/profiles.csv" \ --profiles-output-file "./data/interim/profiles.csv" \
--sites-output-file "./data/interim/sites.csv" --sites-output-file "./data/interim/sites.csv"
# Produces a .csv of waves for each site # Produces a .csv of waves for each site
./data/interim/waves.csv: ./data/interim/sites.csv ./data/raw/processed_shorelines/waves.mat ./data/interim/waves.csv: ./data/interim/sites.csv ./data/raw/processed_shorelines/waves.mat
activate ./.venv && python ./src/data/parse_mat.py create-waves-csv \ activate ./.venv && python ./src/cli.py create-waves-csv \
--waves-mat "./data/raw/processed_shorelines/waves.mat" \ --waves-mat "./data/raw/processed_shorelines/waves.mat" \
--sites-csv "./data/interim/sites.csv" \ --sites-csv "./data/interim/sites.csv" \
--output-file "./data/interim/waves.csv" --output-file "./data/interim/waves.csv"
# Produces a .csv of tides for each site # Produces a .csv of tides for each site
./data/interim/tides.csv: ./data/interim/sites.csv ./data/raw/processed_shorelines/tides.mat ./data/interim/tides.csv: ./data/interim/sites.csv ./data/raw/processed_shorelines/tides.mat
activate ./.venv && python ./src/data/parse_mat.py create-tides-csv \ activate ./.venv && python ./src/cli.py create-tides-csv \
--tides-mat "./data/raw/processed_shorelines/tides.mat" \ --tides-mat "./data/raw/processed_shorelines/tides.mat" \
--sites-csv "./data/interim/sites.csv" \ --sites-csv "./data/interim/sites.csv" \
--output-file "./data/interim/tides.csv" --output-file "./data/interim/tides.csv"
# Creates a .shp of our sites to load into QGis # Creates a .shp of our sites to load into QGis
./data/interim/sites.shp: ./data/interim/sites.csv ./data/interim/sites.shp: ./data/interim/sites.csv
activate ./.venv && python ./src/data/csv_to_shp.py sites-csv-to-shp \ activate ./.venv && python ./src/cli.py sites-csv-to-shp \
--input-csv "./data/interim/sites.csv" \ --input-csv "./data/interim/sites.csv" \
--output-shp "./data/interim/sites.shp" --output-shp "./data/interim/sites.shp"
# Creates a .csv of our dune toe and crest profile features # Creates a .csv of our dune toe and crest profile features
./data/interim/profile_features.csv: ./data/raw/profile_features/dune_crests.shp ./data/raw/profile_features/dune_toes.shp ./data/interim/sites.csv ./data/interim/profiles.csv ./data/interim/profile_features.csv: ./data/raw/profile_features/dune_crests.shp ./data/raw/profile_features/dune_toes.shp ./data/interim/sites.csv ./data/interim/profiles.csv
activate ./.venv && python ./src/data/profile_features.py create-profile-features \ activate ./.venv && python ./src/cli.py create-profile-features \
--dune-crest-shp "./data/raw/profile_features/dune_crests.shp" \ --dune-crest-shp "./data/raw/profile_features/dune_crests.shp" \
--dune-toe-shp "./data/raw/profile_features/dune_toes.shp" \ --dune-toe-shp "./data/raw/profile_features/dune_toes.shp" \
--sites-csv "./data/interim/sites.csv" \ --sites-csv "./data/interim/sites.csv" \
@ -86,7 +93,7 @@ impacts: ./data/interim/impacts_forecasted_foreshore_slope_sto06.csv ./data/inte
# Creates a forecast of twl using sto06 and prestorm time varying prestorm foreshore slope # Creates a forecast of twl using sto06 and prestorm time varying prestorm foreshore slope
./data/interim/twl_foreshore_slope_sto06.csv: ./data/interim/waves.csv ./data/interim/tides.csv ./data/interim/profiles.csv ./data/interim/sites.csv ./data/interim/profile_features.csv ./data/interim/twl_foreshore_slope_sto06.csv: ./data/interim/waves.csv ./data/interim/tides.csv ./data/interim/profiles.csv ./data/interim/sites.csv ./data/interim/profile_features.csv
activate ./.venv && python ./src/analysis/forecast_twl.py create-twl-forecast \ activate ./.venv && python ./src/cli.py create-twl-forecast \
--waves-csv "./data/interim/waves.csv" \ --waves-csv "./data/interim/waves.csv" \
--tides-csv "./data/interim/tides.csv" \ --tides-csv "./data/interim/tides.csv" \
--profiles-csv "./data/interim/profiles.csv" \ --profiles-csv "./data/interim/profiles.csv" \
@ -96,7 +103,7 @@ impacts: ./data/interim/impacts_forecasted_foreshore_slope_sto06.csv ./data/inte
--output-file "./data/interim/twl_foreshore_slope_sto06.csv" --output-file "./data/interim/twl_foreshore_slope_sto06.csv"
./data/interim/twl_mean_slope_sto06.csv: ./data/interim/waves.csv ./data/interim/tides.csv ./data/interim/profiles.csv ./data/interim/sites.csv ./data/interim/profile_features.csv ./data/interim/twl_mean_slope_sto06.csv: ./data/interim/waves.csv ./data/interim/tides.csv ./data/interim/profiles.csv ./data/interim/sites.csv ./data/interim/profile_features.csv
activate ./.venv && python ./src/analysis/forecast_twl.py create-twl-forecast \ activate ./.venv && python ./src/cli.py create-twl-forecast \
--waves-csv "./data/interim/waves.csv" \ --waves-csv "./data/interim/waves.csv" \
--tides-csv "./data/interim/tides.csv" \ --tides-csv "./data/interim/tides.csv" \
--profiles-csv "./data/interim/profiles.csv" \ --profiles-csv "./data/interim/profiles.csv" \
@ -106,19 +113,19 @@ impacts: ./data/interim/impacts_forecasted_foreshore_slope_sto06.csv ./data/inte
--output-file "./data/interim/twl_mean_slope_sto06.csv" --output-file "./data/interim/twl_mean_slope_sto06.csv"
./data/interim/impacts_observed.csv: ./data/interim/profiles.csv ./data/interim/profile_features.csv ./data/interim/impacts_observed.csv: ./data/interim/profiles.csv ./data/interim/profile_features.csv
activate ./.venv && python ./src/analysis/observed_storm_impacts.py create-observed-impacts \ activate ./.venv && python ./src/cli.py create-observed-impacts \
--profiles-csv "./data/interim/profiles.csv" \ --profiles-csv "./data/interim/profiles.csv" \
--profile-features-csv "./data/interim/profile_features.csv" \ --profile-features-csv "./data/interim/profile_features.csv" \
--output-file "./data/interim/impacts_observed.csv" --output-file "./data/interim/impacts_observed.csv"
./data/interim/impacts_forecasted_mean_slope_sto06.csv: ./data/interim/profile_features.csv ./data/interim/twl_mean_slope_sto06.csv ./data/interim/impacts_forecasted_mean_slope_sto06.csv: ./data/interim/profile_features.csv ./data/interim/twl_mean_slope_sto06.csv
activate ./.venv && python ./src/analysis/forecasted_storm_impacts.py create-forecasted-impacts \ activate ./.venv && python ./src/cli.py create-forecasted-impacts \
--profile-features-csv "./data/interim/profile_features.csv" \ --profile-features-csv "./data/interim/profile_features.csv" \
--forecasted-twl-csv "./data/interim/twl_mean_slope_sto06.csv" \ --forecasted-twl-csv "./data/interim/twl_mean_slope_sto06.csv" \
--output-file "./data/interim/impacts_forecasted_mean_slope_sto06.csv" --output-file "./data/interim/impacts_forecasted_mean_slope_sto06.csv"
./data/interim/impacts_forecasted_foreshore_slope_sto06.csv: ./data/interim/profile_features.csv ./data/interim/twl_foreshore_slope_sto06.csv ./data/interim/impacts_forecasted_foreshore_slope_sto06.csv: ./data/interim/profile_features.csv ./data/interim/twl_foreshore_slope_sto06.csv
activate ./.venv && python ./src/analysis/forecasted_storm_impacts.py create-forecasted-impacts \ activate ./.venv && python ./src/cli.py create-forecasted-impacts \
--profile-features-csv "./data/interim/profile_features.csv" \ --profile-features-csv "./data/interim/profile_features.csv" \
--forecasted-twl-csv "./data/interim/twl_foreshore_slope_sto06.csv" \ --forecasted-twl-csv "./data/interim/twl_foreshore_slope_sto06.csv" \
--output-file "./data/interim/impacts_forecasted_foreshore_slope_sto06.csv" --output-file "./data/interim/impacts_forecasted_foreshore_slope_sto06.csv"

@ -74,3 +74,4 @@ been corrected for systematic errors, so actual elevations should be taken from
- [ ] Implement data/interim/*.csv file checking using py.test. Check for correct columns, number of nans etc. Testing of code is probably a lower priority than just checking the interim data files at the moment. - [ ] Implement data/interim/*.csv file checking using py.test. Check for correct columns, number of nans etc. Testing of code is probably a lower priority than just checking the interim data files at the moment.
- [ ] Investigate using [modin](https://github.com/modin-project/modin) to help speed up analysis. - [ ] Investigate using [modin](https://github.com/modin-project/modin) to help speed up analysis.
- [ ] Need to think about how relative imports are handled, see [here](https://chrisyeh96.github.io/2017/08/08/definitive-guide-python-imports.html). Maybe the click CLI interface should be moved to the `./src/` folder and it can import all the other packages? - [ ] Need to think about how relative imports are handled, see [here](https://chrisyeh96.github.io/2017/08/08/definitive-guide-python-imports.html). Maybe the click CLI interface should be moved to the `./src/` folder and it can import all the other packages?
- [ ] Simplify runup_models in Stockdon06 - we should really only have one function for each runup model. Need to make it work with individual values or entire dataframe. Use (np.maskedarray)[https://docs.scipy.org/doc/numpy-1.15.0/reference/maskedarray.generic.html]

@ -1,15 +0,0 @@
import pandas as pd
import os
def main():
data_folder = "./data/interim"
df_waves = pd.read_csv(os.path.join(data_folder, "waves.csv"), index_col=[0, 1])
df_tides = pd.read_csv(os.path.join(data_folder, "tides.csv"), index_col=[0, 1])
df_profiles = pd.read_csv(os.path.join(data_folder, "profiles.csv"), index_col=[0, 1, 2])
df_sites = pd.read_csv(os.path.join(data_folder, "sites.csv"), index_col=[0])
if __name__ == "__main__":
main()

@ -2,13 +2,13 @@
Compares forecasted and observed impacts, putting them into one data frame and exporting the results. Compares forecasted and observed impacts, putting them into one data frame and exporting the results.
""" """
import logging.config
import os import os
import pandas as pd import pandas as pd
logging.config.fileConfig("./src/logging.conf", disable_existing_loggers=False) from utils import setup_logging
logger = logging.getLogger(__name__)
logger = setup_logging()
def compare_impacts(df_forecasted, df_observed): def compare_impacts(df_forecasted, df_observed):

@ -1,16 +1,16 @@
import logging.config
import os import os
from multiprocessing import Pool from multiprocessing import Pool
import click import click
import numpy as np import numpy as np
import numpy.ma as ma import numpy.ma as ma
import pandas as pd import pandas as pd
from scipy import stats from scipy import stats
import runup_models from analysis import runup_models
from utils import setup_logging
logging.config.fileConfig("./src/logging.conf", disable_existing_loggers=False) logger = setup_logging()
logger = logging.getLogger(__name__)
MULTIPROCESS_THREADS = int(os.environ.get("MULTIPROCESS_THREADS", 4)) MULTIPROCESS_THREADS = int(os.environ.get("MULTIPROCESS_THREADS", 4))
@ -301,13 +301,3 @@ def create_twl_forecast(waves_csv, tides_csv, profiles_csv, profile_features_csv
df_twl_foreshore_slope_sto06.to_csv(output_file) df_twl_foreshore_slope_sto06.to_csv(output_file)
logger.info("Saved to %s", output_file) logger.info("Saved to %s", output_file)
logger.info("Done!") logger.info("Done!")
@click.group()
def cli():
pass
if __name__ == "__main__":
cli.add_command(create_twl_forecast)
cli()

@ -2,13 +2,12 @@
Estimates the forecasted storm impacts based on the forecasted water level and dune crest/toe. Estimates the forecasted storm impacts based on the forecasted water level and dune crest/toe.
""" """
import logging.config
import os
import click import click
import pandas as pd import pandas as pd
logging.config.fileConfig("./src/logging.conf", disable_existing_loggers=False) from utils import setup_logging
logger = logging.getLogger(__name__)
logger = setup_logging()
def forecasted_impacts(df_profile_features, df_forecasted_twl): def forecasted_impacts(df_profile_features, df_forecasted_twl):
@ -72,7 +71,6 @@ def storm_regime(df_forecasted_impacts):
@click.option("--forecasted-twl-csv", required=True, help="") @click.option("--forecasted-twl-csv", required=True, help="")
@click.option("--output-file", required=True, help="") @click.option("--output-file", required=True, help="")
def create_forecasted_impacts(profile_features_csv, forecasted_twl_csv, output_file): def create_forecasted_impacts(profile_features_csv, forecasted_twl_csv, output_file):
logger.info("Creating observed wave impacts") logger.info("Creating observed wave impacts")
logger.info("Importing existing data") logger.info("Importing existing data")
df_profile_features = pd.read_csv(profile_features_csv, index_col=[0]) df_profile_features = pd.read_csv(profile_features_csv, index_col=[0])
@ -82,13 +80,3 @@ def create_forecasted_impacts(profile_features_csv, forecasted_twl_csv, output_f
df_forecasted_impacts.to_csv(output_file) df_forecasted_impacts.to_csv(output_file)
logger.info("Saved to %s", output_file) logger.info("Saved to %s", output_file)
logger.info("Done!") logger.info("Done!")
@click.group()
def cli():
pass
if __name__ == "__main__":
cli.add_command(create_forecasted_impacts)
cli()

@ -1,12 +1,11 @@
import logging.config
import os
import click import click
import numpy as np import numpy as np
import pandas as pd import pandas as pd
from scipy.integrate import simps from scipy.integrate import simps
logging.config.fileConfig("./src/logging.conf", disable_existing_loggers=False) from utils import setup_logging
logger = logging.getLogger(__name__)
logger = setup_logging()
def return_first_or_nan(l): def return_first_or_nan(l):
@ -49,8 +48,8 @@ def volume_change(df_profiles, df_profile_features, zone):
prestorm_dune_toe_x = prestorm_dune_crest_x prestorm_dune_toe_x = prestorm_dune_crest_x
# If no prestorm and poststorm profiles, skip site and continue # If no prestorm and poststorm profiles, skip site and continue
profile_lengths = [len(df_site.query("profile_type == '{}'".format(x))) for x in ['prestorm', 'poststorm']] profile_lengths = [len(df_site.query("profile_type == '{}'".format(x))) for x in ["prestorm", "poststorm"]]
if any([length ==0 for length in profile_lengths]): if any([length == 0 for length in profile_lengths]):
continue continue
# Find last x coordinate where we have both prestorm and poststorm measurements. If we don't do this, # Find last x coordinate where we have both prestorm and poststorm measurements. If we don't do this,
@ -182,13 +181,3 @@ def create_observed_impacts(profiles_csv, profile_features_csv, output_file):
logger.info("Saved to %s", output_file) logger.info("Saved to %s", output_file)
logger.info("Done!") logger.info("Done!")
@click.group()
def cli():
pass
if __name__ == "__main__":
cli.add_command(create_observed_impacts)
cli()

@ -0,0 +1,29 @@
"""
Entry point to run data processing and analysis commands.
"""
import click
import data.parse_mat as parse_mat
import data.profile_features as profile_features
import data.csv_to_shp as csv_to_shp
import analysis.forecast_twl as forecast_twl
import analysis.forecasted_storm_impacts as forecasted_storm_impacts
import analysis.observed_storm_impacts as observed_storm_impacts
@click.group()
def cli():
pass
if __name__ == "__main__":
cli.add_command(parse_mat.create_waves_csv)
cli.add_command(parse_mat.create_sites_and_profiles_csv)
cli.add_command(parse_mat.create_tides_csv)
cli.add_command(profile_features.create_profile_features)
cli.add_command(csv_to_shp.sites_csv_to_shp)
cli.add_command(forecast_twl.create_twl_forecast)
cli.add_command(forecasted_storm_impacts.create_forecasted_impacts)
cli.add_command(observed_storm_impacts.create_observed_impacts)
cli()

@ -1,12 +1,6 @@
""" """
Converts .csv files to .shape files Converts .csv files to .shape files
""" """
import os
import sys
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import click import click
import fiona import fiona
import pandas as pd import pandas as pd
@ -38,13 +32,3 @@ def sites_csv_to_shp(input_csv, output_shp):
prop = {"beach": row["beach"], "site_id": index} prop = {"beach": row["beach"], "site_id": index}
output.write({"geometry": mapping(point), "properties": prop}) output.write({"geometry": mapping(point), "properties": prop})
logger.info("Done!") logger.info("Done!")
@click.group()
def cli():
pass
if __name__ == "__main__":
cli.add_command(sites_csv_to_shp)
cli()

@ -2,14 +2,8 @@
Converts raw .mat files into a flattened .csv structure which can be imported into python pandas. Converts raw .mat files into a flattened .csv structure which can be imported into python pandas.
""" """
import os
import sys
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from datetime import datetime, timedelta
import math import math
from datetime import datetime, timedelta
import click import click
import numpy as np import numpy as np
@ -17,7 +11,7 @@ import pandas as pd
from mat4py import loadmat from mat4py import loadmat
from shapely.geometry import Point from shapely.geometry import Point
from profile_features import convert_coord_systems from data.profile_features import convert_coord_systems
from utils import setup_logging from utils import setup_logging
logger = setup_logging() logger = setup_logging()

@ -1,5 +1,5 @@
import os
from functools import partial from functools import partial
import click import click
import fiona import fiona
import numpy as np import numpy as np
@ -8,11 +8,10 @@ import pyproj
from shapely.geometry import LineString, Point from shapely.geometry import LineString, Point
from shapely.geometry import shape from shapely.geometry import shape
from shapely.ops import transform from shapely.ops import transform
import logging.config
from utils import setup_logging
logging.config.fileConfig("./src/logging.conf", disable_existing_loggers=False) logger = setup_logging()
logger = logging.getLogger(__name__)
def convert_coord_systems(g1, in_coord_system="EPSG:4326", out_coord_system="EPSG:28356"): def convert_coord_systems(g1, in_coord_system="EPSG:4326", out_coord_system="EPSG:28356"):
@ -160,13 +159,3 @@ def create_profile_features(dune_crest_shp, dune_toe_shp, sites_csv, profiles_cs
df_profile_features = parse_profile_features(df_sites, df_profiles, dune_crest_shp, dune_toe_shp) df_profile_features = parse_profile_features(df_sites, df_profiles, dune_crest_shp, dune_toe_shp)
df_profile_features.to_csv(output_csv) df_profile_features.to_csv(output_csv)
logger.info("Done!") logger.info("Done!")
@click.group()
def cli():
pass
if __name__ == "__main__":
cli.add_command(create_profile_features)
cli()

@ -1,32 +0,0 @@
[loggers]
keys=root, matplotlib, fiona
[handlers]
keys=consoleHandler
[formatters]
keys=simpleFormatter
[logger_root]
level=DEBUG
handlers=consoleHandler
[logger_matplotlib]
level=WARNING
handlers=consoleHandler
qualname=matplotlib
[logger_fiona]
level=WARNING
handlers=consoleHandler
qualname=fiona
[handler_consoleHandler]
class=StreamHandler
level=INFO
formatter=simpleFormatter
args=(sys.stdout,)
[formatter_simpleFormatter]
format=%(asctime)s %(name)-17s %(levelname)-8s %(message)s
datefmt=%a, %d %b %Y %H:%M:%S
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