def test_data_velib_simulation(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__",
LogFile="temp_hal_log2.txt")
fold = os.path.abspath(os.path.split(__file__)[0])
data = os.path.join(fold, "data")
for speed in (10, 15):
for bike in (1, 2, 3, 5, 10):
df = DataVelibCollect.to_df(data)
dfp, dfs = DataVelibCollect.simulate(
df, bike, speed, fLOG=fLOG)
dfp.to_csv(
"out_simul_bike_nb{0}_sp{1}_path.txt".format(
bike,
speed),
sep="\t",
index=False)
dfs.to_csv(
"out_simul_bike_nb{0}_sp{1}_data.txt".format(
bike,
speed),
sep="\t",
index=False)
if __name__ != "__main__":
return
def test_data_velib_animation(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__",
LogFile="temp_hal_log2.txt")
fold = os.path.abspath(os.path.split(__file__)[0])
data = os.path.join(fold, "data")
if "travis" in sys.executable:
return
try:
from JSAnimation import IPython_display
except ImportError:
import pymyinstall
pymyinstall.ModuleInstall(
"JSAnimation",
"github",
"jakevdp").install(
temp_folder="c:\\temp")
df = DataVelibCollect.to_df(data)
anime = DataVelibCollect.js_animation(df)
from JSAnimation import HTMLWriter
wr = HTMLWriter(embed_frames=False)
anime.save(os.path.join(fold, "out_animation.html"), writer=wr)
def test_data_velib_simulation(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__",
LogFile="temp_hal_log2.txt")
fold = os.path.abspath(os.path.split(__file__)[0])
data = os.path.join(fold, "data")
for speed in (10, 15):
for bike in (1, 2, 3, 5, 10):
df = DataVelibCollect.to_df(data)
dfp, dfs = DataVelibCollect.simulate(df,
bike,
speed,
fLOG=fLOG)
dfp.to_csv("out_simul_bike_nb{0}_sp{1}_path.txt".format(
bike, speed),
sep="\t",
index=False)
dfs.to_csv("out_simul_bike_nb{0}_sp{1}_data.txt".format(
bike, speed),
sep="\t",
index=False)
if __name__ != "__main__":
return
def test_data_velib_json(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__",
LogFile="temp_hal_log2.txt")
tempfold = get_temp_folder(__file__, "temp_data_i")
temp_file = os.path.join(tempfold, "data_velib.txt")
if os.path.exists(temp_file):
os.remove(temp_file)
assert not os.path.exists(temp_file)
key = self.get_private_key()
if key is None:
return
velib = DataVelibCollect(key)
js = velib.get_json("Paris")
assert isinstance(js, list)
fLOG(type(js))
nb = 0
for o in js:
fLOG(o)
nb += 1
if nb > 10:
break
assert nb > 0
assert len(js) > 0
tbl = pandas.DataFrame(js)
tbl.to_csv(temp_file, sep="\t")
assert os.path.exists(temp_file)
fLOG(tbl[:10])
def test_data_velib_json_collect_func_besancon(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__",
LogFile="temp_hal_log2.txt")
tempfold = get_temp_folder(__file__, "temp_data_func_bes")
temp_file = os.path.join(tempfold, "data_velib.txt")
delay = datetime.timedelta(seconds=5)
dt = datetime.datetime.now() + delay
key = self.get_private_key()
if key is None:
return
DataVelibCollect.run_collection(key, contract="Besancon", delayms=1000,
folder_file=temp_file, single_file=True,
stop_datetime=dt, log_every=1, fLOG=fLOG)
if not os.path.exists(temp_file):
raise FileNotFoundError(temp_file)
with open(temp_file, "r", encoding="utf8") as f:
lines = f.readlines()
if len(lines) < 1:
raise Exception(
"len(lines)<1: %d\n%s" %
(len(lines), "\n".join(lines)))
assert len(lines) < 10
assert "\t" in lines[0]
def test_data_velib_contract(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__",
LogFile="temp_hal_log2.txt")
key = self.get_private_key()
if key is None:
return
velib = DataVelibCollect(key)
cont = velib.get_contracts()
fLOG("**", cont)
assert len(cont) > 0
def test_data_velib_json_collect(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__",
LogFile="temp_hal_log2.txt")
fold = os.path.abspath(os.path.split(__file__)[0])
tempfold = os.path.join(fold, "temp_data_i2")
if not os.path.exists(tempfold):
os.mkdir(tempfold)
for _ in os.listdir(tempfold):
os.remove(os.path.join(tempfold, _))
temp_file = os.path.join(tempfold, "data_velib.txt")
delay = datetime.datetime.fromtimestamp(
5.0) - datetime.datetime.fromtimestamp(0.)
dt = datetime.datetime.now() + delay
key = self.get_private_key()
if key is None:
return
velib = DataVelibCollect(key)
velib.collecting_data(
"Paris",
1000,
temp_file,
stop_datetime=dt,
log_every=1,
fLOG=fLOG)
assert os.path.exists(temp_file)
with open(temp_file, "r", encoding="utf8") as f:
lines = f.readlines()
if len(lines) < 1:
raise Exception(
"len(lines)<1: %d\n%s" %
(len(lines), "\n".join(lines)))
assert len(lines) < 10
assert "\t" in lines[0]
dt = datetime.datetime.now() + delay
velib.collecting_data("Paris", 1000, temp_file, stop_datetime=dt,
single_file=False, log_every=1, fLOG=fLOG)
res = os.listdir(tempfold)
if len(res) <= 2:
raise Exception(str(res))
def test_data_velib_contract(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__",
LogFile="temp_hal_log2.txt")
key = self.get_private_key()
if key is None:
return
velib = DataVelibCollect(key)
cont = velib.get_contracts()
fLOG("**", cont)
assert len(cont) > 0
def test_data_velib_animation(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__",
LogFile="temp_hal_log2.txt")
fold = os.path.abspath(os.path.split(__file__)[0])
data = os.path.join(fold, "data")
if "travis" in sys.executable:
return
from pymyinstall.installhelper.install_cmd_helper import is_conda_distribution
if is_conda_distribution():
# not tested on anaconda
return
df = DataVelibCollect.to_df(data)
DataVelibCollect.js_animation(df)
def test_data_velib_animation(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__",
LogFile="temp_hal_log2.txt")
fold = os.path.abspath(os.path.split(__file__)[0])
data = os.path.join(fold, "data")
if "travis" in sys.executable:
return
from pymyinstall.installhelper.install_cmd_helper import is_conda_distribution
if is_conda_distribution():
# not tested on anaconda
return
df = DataVelibCollect.to_df(data)
DataVelibCollect.js_animation(df)
def test_data_velib_json_collect_func_besancon(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__",
LogFile="temp_hal_log2.txt")
fold = os.path.abspath(os.path.split(__file__)[0])
tempfold = os.path.join(fold, "temp_data_func_bes")
if not os.path.exists(tempfold):
os.mkdir(tempfold)
for _ in os.listdir(tempfold):
os.remove(os.path.join(tempfold, _))
temp_file = os.path.join(tempfold, "data_velib.txt")
delay = datetime.datetime.fromtimestamp(
5.0) - datetime.datetime.fromtimestamp(0.)
dt = datetime.datetime.now() + delay
key = self.get_private_key()
if key is None:
return
DataVelibCollect.run_collection(key,
contract="Besancon",
delayms=1000,
folder_file=temp_file,
single_file=True,
stop_datetime=dt,
log_every=1,
fLOG=fLOG)
assert os.path.exists(temp_file)
with open(temp_file, "r", encoding="utf8") as f:
lines = f.readlines()
if len(lines) < 1:
raise Exception("len(lines)<1: %d\n%s" %
(len(lines), "\n".join(lines)))
assert len(lines) < 10
assert "\t" in lines[0]
def test_data_velib_contract(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__",
LogFile="temp_hal_log2.txt")
fold = os.path.abspath(os.path.split(__file__)[0])
data = os.path.join(fold, "data")
df = DataVelibCollect.to_df(data)
# fLOG(df.head())
assert len(df) > 0
stations = df[["name", "lat", "lng"]]
gr = stations.groupby(["name", "lat", "lng"], as_index=False).sum()
# fLOG(gr.head())
assert len(gr) >= 30
df.to_csv(os.path.join(fold, "out_data.txt"), sep="\t", index=False)
dt = datetime.datetime(2014, 5, 22, 11, 49, 27, 523164)
sub = df[df["collect_date"] == dt]
fig, ax, plt = DataVelibCollect.draw(sub)
def test_data_velib_contract(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__",
LogFile="temp_hal_log2.txt")
fold = os.path.abspath(os.path.split(__file__)[0])
data = os.path.join(fold, "data")
df = DataVelibCollect.to_df(data)
# fLOG(df.head())
assert len(df) > 0
stations = df[["name", "lat", "lng"]]
gr = stations.groupby(["name", "lat", "lng"], as_index=False).sum()
# fLOG(gr.head())
assert len(gr) >= 30
df.to_csv(os.path.join(fold, "out_data.txt"), sep="\t", index=False)
dt = datetime.datetime(2014, 5, 22, 11, 49, 27, 523164)
sub = df[df["collect_date"] == dt]
fig, ax, plt = DataVelibCollect.draw(sub)
def test_data_velib_json_collect(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__",
LogFile="temp_hal_log2.txt")
tempfold = get_temp_folder(__file__, "temp_data_i2")
temp_file = os.path.join(tempfold, "data_velib.txt")
delay = datetime.timedelta(seconds=5)
dt = datetime.datetime.now() + delay
key = self.get_private_key()
if key is None:
return
velib = DataVelibCollect(key)
velib.collecting_data("Paris", 1000, temp_file, stop_datetime=dt,
log_every=1, fLOG=fLOG)
if not os.path.exists(temp_file):
raise FileNotFoundError(temp_file)
with open(temp_file, "r", encoding="utf8") as f:
lines = f.readlines()
if len(lines) < 1:
raise Exception(
"len(lines)<1: %d\n%s" %
(len(lines), "\n".join(lines)))
assert len(lines) < 10
assert "\t" in lines[0]
dt = datetime.datetime.now() + delay
velib.collecting_data("Paris", 1000, temp_file, stop_datetime=dt,
single_file=False, log_every=1, fLOG=fLOG)
res = os.listdir(tempfold)
if len(res) <= 2:
raise Exception(str(res))
