def test_histogram2d(self):
s = self.scheduler()
csv = CSVLoader(get_dataset('bigfile'),
index_col=False,
header=None,
scheduler=s)
min_ = Min(scheduler=s)
min_.input.table = csv.output.table
max_ = Max(scheduler=s)
max_.input.table = csv.output.table
histogram2d = Histogram2D(1, 2, xbins=100, ybins=100,
scheduler=s) # columns are called 1..30
histogram2d.input.table = csv.output.table
histogram2d.input.min = min_.output.table
histogram2d.input.max = max_.output.table
heatmap = Heatmap(filename='histo_%03d.png', scheduler=s)
heatmap.input.array = histogram2d.output.table
#pr = Print(scheduler=s)
pr = Every(proc=self.terse, scheduler=s)
#pr.input.df = heatmap.output.heatmap
#pr.input.df = histogram2d.output.df
pr.input.df = csv.output.table
csv.scheduler().start()
s.join()
#self.scheduler.thread.join()
s = histogram2d.trace_stats()
def t_histogram2d_impl(self, **kw: Any) -> None:
s = self.scheduler()
random = RandomTable(3, rows=100000, scheduler=s)
stirrer = Stirrer(update_column="_2", fixed_step_size=1000, scheduler=s, **kw)
stirrer.input[0] = random.output.result
min_ = Min(scheduler=s)
min_.input[0] = stirrer.output.result
max_ = Max(scheduler=s)
max_.input[0] = stirrer.output.result
histogram2d = Histogram2D(
0, 1, xbins=100, ybins=100, scheduler=s
) # columns are called 1..30
histogram2d.input[0] = stirrer.output.result
histogram2d.input.min = min_.output.result
histogram2d.input.max = max_.output.result
heatmap = Heatmap(filename="histo_%03d.png", scheduler=s)
heatmap.input.array = histogram2d.output.result
pr = Every(proc=self.terse, scheduler=s)
pr.input[0] = heatmap.output.result
aio.run(s.start())
last = notNone(histogram2d.table.last()).to_dict()
h1 = last["array"]
bounds = [[last["ymin"], last["ymax"]], [last["xmin"], last["xmax"]]]
t = stirrer.table.loc[:, ["_1", "_2"]]
assert t is not None
v = t.to_array()
bins = [histogram2d.params.ybins, histogram2d.params.xbins]
h2 = fh.histogram2d(v[:, 1], v[:, 0], bins=bins, range=bounds)
h2 = np.flip(h2, axis=0) # type: ignore
self.assertEqual(np.sum(h1), np.sum(h2))
self.assertListEqual(h1.reshape(-1).tolist(), h2.reshape(-1).tolist())
def test_histogram2d1(self) -> None:
s = self.scheduler()
csv = CSVLoader(
get_dataset("bigfile"), index_col=False, header=None, scheduler=s
)
min_ = Min(scheduler=s)
min_.input[0] = csv.output.result
max_ = Max(scheduler=s)
max_.input[0] = csv.output.result
histogram2d = Histogram2D(
1, 2, xbins=100, ybins=100, scheduler=s
) # columns are called 1..30
histogram2d.input[0] = csv.output.result
histogram2d.input.min = min_.output.result
histogram2d.input.max = max_.output.result
heatmap = Heatmap(filename="histo_%03d.png", scheduler=s)
heatmap.input.array = histogram2d.output.result
pr = Every(proc=self.terse, scheduler=s)
pr.input[0] = heatmap.output.result
aio.run(csv.scheduler().start())
last = notNone(histogram2d.table.last()).to_dict()
h1 = last["array"]
bounds = [[last["ymin"], last["ymax"]], [last["xmin"], last["xmax"]]]
df = pd.read_csv(
get_dataset("bigfile"), header=None, usecols=[1, 2] # type: ignore
)
v = df.to_numpy() # .reshape(-1, 2)
bins = [histogram2d.params.ybins, histogram2d.params.xbins]
h2 = fh.histogram2d(v[:, 1], v[:, 0], bins=bins, range=bounds)
h2 = np.flip(h2, axis=0) # type: ignore
self.assertTrue(np.allclose(h1, h2))
def refresh_info_h2d(hout: WidgetType, h2d_mod: Histogram2D, name: str,
tab: "TreeTab") -> None:
if not tab.is_visible(name) and h2d_mod.updated_once: # type: ignore
return
if not h2d_mod.table:
return
last = h2d_mod.table.last()
assert last
res = last.to_dict()
hist = res["array"]
hout.update("data", insert=hist, remove="true")
h2d_mod.updated_once = True # type: ignore
def test_histogram2d(self) -> None:
s = self.scheduler()
csv = CSVLoader(
get_dataset("bigfile"), index_col=False, header=None, scheduler=s
)
min_ = Min(scheduler=s)
min_.input[0] = csv.output.result
max_ = Max(scheduler=s)
max_.input[0] = csv.output.result
histogram2d = Histogram2D(
1, 2, xbins=100, ybins=100, scheduler=s
) # columns are called 1..30
histogram2d.input[0] = csv.output.result
histogram2d.input.min = min_.output.result
histogram2d.input.max = max_.output.result
heatmap = Heatmap(filename="histo_%03d.png", scheduler=s)
heatmap.input.array = histogram2d.output.result
pr = Every(proc=self.terse, scheduler=s)
pr.input[0] = heatmap.output.result
aio.run(csv.scheduler().start())
_ = histogram2d.trace_stats()
#SUFFIX= ''
PREFIX= '../nyc-taxi/'
SUFFIX= '.bz2'
URLS = [
PREFIX+'yellow_tripdata_2015-01.csv'+SUFFIX,
PREFIX+'yellow_tripdata_2015-02.csv'+SUFFIX,
PREFIX+'yellow_tripdata_2015-03.csv'+SUFFIX,
PREFIX+'yellow_tripdata_2015-04.csv'+SUFFIX,
PREFIX+'yellow_tripdata_2015-05.csv'+SUFFIX,
PREFIX+'yellow_tripdata_2015-06.csv'+SUFFIX,
]
filenames = pd.DataFrame({'filename': URLS})
cst = Constant(Table('filenames', data=filenames), scheduler=s)
csv = CSVLoader(index_col=False,skipinitialspace=True,usecols=['dropoff_longitude', 'dropoff_latitude'], filter_=filter_, scheduler=s)
csv.input.filenames = cst.output.table
min = Min(scheduler=s)
min.input.table = csv.output.table
max = Max(scheduler=s)
max.input.table = csv.output.table
histogram2d = Histogram2D('dropoff_longitude', 'dropoff_latitude', xbins=RESOLUTION, ybins=RESOLUTION, scheduler=s)
histogram2d.input.table = csv.output.table
histogram2d.input.min = min.output.table
histogram2d.input.max = max.output.table
heatmap = Heatmap(filename='nyc_dropoff_yellow%d.png', history=5, scheduler=s)
heatmap.input.array = histogram2d.output.table
if __name__=='__main__':
s.start()
#SUFFIX= ''
PREFIX= '../nyc-taxi/'
SUFFIX= '.bz2'
URLS = [
PREFIX+'green_tripdata_2015-01.csv'+SUFFIX,
PREFIX+'green_tripdata_2015-02.csv'+SUFFIX,
PREFIX+'green_tripdata_2015-03.csv'+SUFFIX,
PREFIX+'green_tripdata_2015-04.csv'+SUFFIX,
PREFIX+'green_tripdata_2015-05.csv'+SUFFIX,
PREFIX+'green_tripdata_2015-06.csv'+SUFFIX,
]
filenames = pd.DataFrame({'filename': URLS})
cst = Constant(Table('filenames', data=filenames), scheduler=s)
csv = CSVLoader(index_col=False,skipinitialspace=True,usecols=['Pickup_longitude', 'Pickup_latitude'], filter_=filter_, scheduler=s)
csv.input.filenames = cst.output.table
min = Min(scheduler=s)
min.input.table = csv.output.table
max = Max(scheduler=s)
max.input.table = csv.output.table
histogram2d = Histogram2D('Pickup_longitude', 'Pickup_latitude', xbins=RESOLUTION, ybins=RESOLUTION, scheduler=s)
histogram2d.input.table = csv.output.table
histogram2d.input.min = min.output.table
histogram2d.input.max = max.output.table
heatmap = Heatmap(filename='nyc_pickup_green%d.png', history=5, scheduler=s)
heatmap.input.array = histogram2d.output.table
if __name__=='__main__':
s.start()
PREFIX + 'uber-raw-data-jun14.csv' + SUFFIX,
PREFIX + 'uber-raw-data-jul14.csv' + SUFFIX,
PREFIX + 'uber-raw-data-sep14.csv' + SUFFIX,
]
filenames = pd.DataFrame({'filename': URLS})
cst = Constant(table=Table('filenames', data=filenames), scheduler=s)
csv = CSVLoader(index_col=False,
skipinitialspace=True,
usecols=['Lon', 'Lat'],
filter_=filter_,
scheduler=s)
csv.input.filenames = cst.output.table
min = Min(scheduler=s)
min.input.table = csv.output.table
max = Max(scheduler=s)
max.input.table = csv.output.table
histogram2d = Histogram2D('Lon',
'Lat',
xbins=RESOLUTION,
ybins=RESOLUTION,
scheduler=s)
histogram2d.input.table = csv.output.table
histogram2d.input.min = min.output.table
histogram2d.input.max = max.output.table
heatmap = Heatmap(filename='nyc_pickup_uber%d.png', history=5, scheduler=s)
heatmap.input.array = histogram2d.output.table
if __name__ == '__main__':
s.start()
from progressivis.io import CSVLoader
from progressivis.stats import Histogram2D, Min, Max
from progressivis.datasets import get_dataset
from progressivis.vis import Heatmap
print("Loading test_histogram2d")
print("Type of default_scheduler is %s" % type(Scheduler.default))
csv = CSVLoader(get_dataset('bigfile'),
index_col=False,
header=None,
engine='c')
pr = Every()
pr.input.df = csv.output.table
min_ = Min()
min_.input.table = csv.output.table
max_ = Max()
max_.input.table = csv.output.table
histogram2d = Histogram2D('_1', '_2', xbins=128, ybins=128)
histogram2d.input.table = csv.output.table
histogram2d.input.min = min_.output.table
histogram2d.input.max = max_.output.table
# heatmap
heatmap = Heatmap(filename='histo_%03d.png')
heatmap.input.array = histogram2d.output.table
pr = Print(name='print')
pr.input.df = csv.output.table
if __name__ == '__main__':
csv.start()