def test_seriescolumn():
dm1 = DataMatrix(length=2)
dm1.col1 = SeriesColumn(2)
dm1.col1 = 1, 2
dm1.col_shared = SeriesColumn(2)
dm1.col_shared = 3, 4
dm2 = DataMatrix(length=2)
dm2.col2 = SeriesColumn(2)
dm2.col2 = 5, 6
dm2.col_shared = SeriesColumn(2)
dm2.col_shared = 7, 8
dm3 = dm1 << dm2
check_series(dm3.col1,
[[1, 1], [2, 2], [np.nan, np.nan], [np.nan, np.nan]])
check_series(dm3.col_shared, [[3, 3], [4, 4], [7, 7], [8, 8]])
check_series(dm3.col2,
[[np.nan, np.nan], [np.nan, np.nan], [5, 5], [6, 6]])
dm3.i = [4, 0, 2, 1]
dm4 = dm3.i <= 2
dm5 = (dm3.i <= 2) | (dm3.i >= 3)
check_integrity(dm1)
check_integrity(dm2)
check_integrity(dm3)
check_integrity(dm4)
check_integrity(dm5)
def check_shuffle(col_type):
dm = DataMatrix(length=3, default_col_type=col_type)
dm.col1 = 11, 12, 13
dm.col2 = 1, 2, 3
dm = operations.shuffle(dm)
for row in dm:
ok_(row.col1 == row.col2 + 10)
dm.col1 = operations.shuffle(dm.col1)
dm.col2 = operations.shuffle(dm.col2)
check_integrity(dm)
def check_shuffle(col_type): dm = DataMatrix(length=3, default_col_type=col_type) dm.col1 = 11,12,13 dm.col2 = 1,2,3 dm = operations.shuffle(dm) for row in dm: ok_(row.col1 == row.col2+10) dm.col1 = operations.shuffle(dm.col1) dm.col2 = operations.shuffle(dm.col2) check_integrity(dm)
def check_iteration(col_type):
dm = DataMatrix(length=2, default_col_type=col_type)
dm.col1 = 1, 2
dm.col2 = 3, 4
# Row iteration
ref = [
[('col1', 1), ('col2', 3)],
[('col1', 2), ('col2', 4)]
]
for row, rowref in zip(dm, ref):
assert(list(row) == rowref)
# Column iteration
ref = [
('col1', [1,2]),
('col2', [3,4])
]
for (name, col), (ref_name, ref_col) in zip(dm.columns, ref):
assert(name == ref_name)
assert(list(col) == ref_col)
# Cells within column iteration
ref = [1,2]
for val, ref_val in zip(dm.col1, ref):
assert(val == ref_val)
# Cells within row iteration
ref = [
('col1', 1),
('col2', 3)
]
for (name, val), (ref_name, ref_val) in zip(dm[0], ref):
assert(val == ref_val)
assert(name == ref_name)
def check_nan_sort(): dm = DataMatrix(length=3, default_col_type=FloatColumn) dm.col1 = 2,np.nan,1 dm.col2 = 1,2,np.nan dm = operations.sort(dm, by=dm.col1) check_col(dm.col1, [1, 2, np.nan]) check_col(dm.col2, [np.nan, 1, 2]) dm = operations.sort(dm, by=dm.col2) check_col(dm.col1, [2, np.nan, 1]) check_col(dm.col2, [1, 2, np.nan]) dm.col1 = operations.sort(dm.col1) dm.col2 = operations.sort(dm.col2) check_col(dm.col1, [1, 2, np.nan]) check_col(dm.col2, [1, 2, np.nan]) check_integrity(dm)
def check_nan_sort():
dm = DataMatrix(length=3, default_col_type=FloatColumn)
dm.col1 = 2, np.nan, 1
dm.col2 = 1, 2, np.nan
dm = operations.sort(dm, by=dm.col1)
check_col(dm.col1, [1, 2, np.nan])
check_col(dm.col2, [np.nan, 1, 2])
dm = operations.sort(dm, by=dm.col2)
check_col(dm.col1, [2, np.nan, 1])
check_col(dm.col2, [1, 2, np.nan])
dm.col1 = operations.sort(dm.col1)
dm.col2 = operations.sort(dm.col2)
check_col(dm.col1, [1, 2, np.nan])
check_col(dm.col2, [1, 2, np.nan])
check_integrity(dm)
def check_sort(col_type): dm = DataMatrix(length=3, default_col_type=col_type) dm.col1 = 3,2,1 dm.col2 = 1,2,3 dm = operations.sort(dm, by=dm.col1) check_col(dm.col1, [1, 2, 3]) check_col(dm.col2, [3, 2, 1]) dm = operations.sort(dm, by=dm.col2) check_col(dm.col1, [3, 2, 1]) check_col(dm.col2, [1, 2, 3]) dm.col2 = operations.sort(dm.col2, by=dm.col1) check_col(dm.col2, [3, 2, 1]) dm.col1 = operations.sort(dm.col1) dm.col2 = operations.sort(dm.col2) check_col(dm.col1, [1, 2, 3]) check_col(dm.col2, [1, 2, 3]) check_integrity(dm)
def check_sort(col_type):
dm = DataMatrix(length=3, default_col_type=col_type)
dm.col1 = 3, 2, 1
dm.col2 = 1, 2, 3
dm = operations.sort(dm, by=dm.col1)
check_col(dm.col1, [1, 2, 3])
check_col(dm.col2, [3, 2, 1])
dm = operations.sort(dm, by=dm.col2)
check_col(dm.col1, [3, 2, 1])
check_col(dm.col2, [1, 2, 3])
dm.col2 = operations.sort(dm.col2, by=dm.col1)
check_col(dm.col2, [3, 2, 1])
dm.col1 = operations.sort(dm.col1)
dm.col2 = operations.sort(dm.col2)
check_col(dm.col1, [1, 2, 3])
check_col(dm.col2, [1, 2, 3])
check_integrity(dm)
def check_concat(col_type, invalid):
dm1 = DataMatrix(length=2, default_col_type=col_type)
dm1.col1 = 1, 2
dm1.col_shared = 3, 4
dm2 = DataMatrix(length=2, default_col_type=col_type)
dm2.col2 = 5, 6
dm2.col_shared = 7, 8
dm3 = dm1 << dm2
check_col(dm3.col1, [1, 2, invalid, invalid])
check_col(dm3.col_shared, [3, 4, 7, 8])
check_col(dm3.col2, [invalid, invalid, 5, 6])
def check_concat(col_type, invalid): dm1 = DataMatrix(length=2, default_col_type=col_type) dm1.col1 = 1, 2 dm1.col_shared = 3, 4 dm2 = DataMatrix(length=2, default_col_type=col_type) dm2.col2 = 5, 6 dm2.col_shared = 7, 8 dm3 = dm1 << dm2 check_col(dm3.col1, [1,2,invalid,invalid]) check_col(dm3.col_shared, [3,4,7,8]) check_col(dm3.col2, [invalid,invalid,5,6])
def test_seriescolumn(): dm1 = DataMatrix(length=2) dm1.col1 = SeriesColumn(2) dm1.col1 = 1, 2 dm1.col_shared = SeriesColumn(2) dm1.col_shared = 3, 4 dm2 = DataMatrix(length=2) dm2.col2 = SeriesColumn(2) dm2.col2 = 5, 6 dm2.col_shared = SeriesColumn(2) dm2.col_shared = 7, 8 dm3 = dm1 << dm2 check_series(dm3.col1, [[1,1],[2,2],[0,0],[0,0]]) check_series(dm3.col_shared, [[3,3],[4,4],[7,7],[8,8]]) check_series(dm3.col2, [[0,0],[0,0],[5,5],[6,6]]) dm3.i = [4,0,2,1] dm4 = dm3.i <= 2 dm5 = (dm3.i <= 2) | (dm3.i >= 3) check_integrity(dm1) check_integrity(dm2) check_integrity(dm3) check_integrity(dm4) check_integrity(dm5)
def check_iteration(col_type):
dm = DataMatrix(length=2, default_col_type=col_type)
dm.col1 = 1, 2
dm.col2 = 3, 4
# Row iteration
ref = [[('col1', 1), ('col2', 3)], [('col1', 2), ('col2', 4)]]
for row, rowref in zip(dm, ref):
assert (list(row) == rowref)
# Column iteration
ref = [('col1', [1, 2]), ('col2', [3, 4])]
for (name, col), (ref_name, ref_col) in zip(dm.columns, ref):
assert (name == ref_name)
assert (list(col) == ref_col)
# Cells within column iteration
ref = [1, 2]
for val, ref_val in zip(dm.col1, ref):
assert (val == ref_val)
# Cells within row iteration
ref = [('col1', 1), ('col2', 3)]
for (name, val), (ref_name, ref_val) in zip(dm[0], ref):
assert (val == ref_val)
assert (name == ref_name)
it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. qdatamatatrix is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with qdatamatatrix. If not, see <http://www.gnu.org/licenses/>. """ from datamatrix import DataMatrix from qdatamatrix import QDataMatrix import sys from qtpy import QtWidgets import qtpy dm = DataMatrix(length=3) dm.col1 = 1, 2, 3 dm.col2 = 'a', 'b', 'c' print(dm) app = QtWidgets.QApplication(sys.argv) qdm = QDataMatrix(dm) qdm.resize(600,400) # qdm.refresh() qdm.show() sys.exit(app.exec_())
it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. qdatamatatrix is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with qdatamatatrix. If not, see <http://www.gnu.org/licenses/>. """ from datamatrix import DataMatrix from qdatamatrix import QDataMatrix import sys from qtpy import QtWidgets import qtpy dm = DataMatrix(length=3) dm.col1 = 1, 2, 3 dm.col2 = 'a', 'b', 'c' print(dm) app = QtWidgets.QApplication(sys.argv) qdm = QDataMatrix(dm) qdm.resize(600, 400) # qdm.refresh() qdm.show() sys.exit(app.exec_())
You should have received a copy of the GNU General Public License
along with qdatamatatrix. If not, see <http://www.gnu.org/licenses/>.
"""
from datamatrix import DataMatrix
from qdatamatrix import QDataMatrix
import sys
from qtpy import QtWidgets
import qtpy
def show():
print(qdm._dm)
for n, c in qdm._dm.columns:
print(n, repr(c._rowid))
dm = DataMatrix(length=4)
dm.sorted = False
dm.col1 = range(4)
dm.col3 = ['a', 'b', 'c', 'd']
dm.col2 = ['e', 'f', 'g', 'h']
print(dm)
app = QtWidgets.QApplication(sys.argv)
qdm = QDataMatrix(dm, read_only=False)
qdm.resize(600, 400)
qdm.changed.connect(show)
qdm.show()
sys.exit(app.exec_())
