def setDataFrame(self, dataFrame):
self.df = dataFrame
dataModel = DataFrameModel()
dataModel.setDataFrame(self.df)
self.dataModel = dataModel
self.dataListView.setModel(dataModel)
self.dataTableView.setViewModel(dataModel)
self.dataComboBox.setModel(dataModel)
# self.dataTableView.resizeColumnsToContents()
# create a simple item model for our choosing combobox
columnModel = QtGui.QStandardItemModel()
for column in self.df.columns:
columnModel.appendRow(QtGui.QStandardItem(column))
self.chooseColumnComboBox.setModel(columnModel)
self.tableViewColumnDtypes.setModel(dataModel.columnDtypeModel())
self.tableViewColumnDtypes.horizontalHeader().setDefaultSectionSize(
200)
self.tableViewColumnDtypes.setItemDelegateForColumn(
1, DtypeComboDelegate(self.tableViewColumnDtypes))
dataModel.changingDtypeFailed.connect(self.changeColumnValue)
def test_copyDataFrame(copy, operator):
dataFrame = pandas.DataFrame([0], columns=["A"])
model = DataFrameModel(dataFrame, copyDataFrame=copy)
assert operator(id(model.dataFrame()), id(dataFrame))
model.setDataFrame(dataFrame, copyDataFrame=copy)
assert operator(id(model.dataFrame()), id(dataFrame))
def test_copyDataFrame(copy, operator):
dataFrame = pandas.DataFrame([0], columns=['A'])
model = DataFrameModel(dataFrame, copyDataFrame=copy)
assert operator(id(model.dataFrame()), id(dataFrame))
model.setDataFrame(dataFrame, copyDataFrame=copy)
assert operator(id(model.dataFrame()), id(dataFrame))
def setDataFrame(self, dataFrame):
self.df = dataFrame
dataModel = DataFrameModel()
dataModel.setDataFrame(self.df)
self.dataListView.setModel(dataModel)
self.dataTableView.setViewModel(dataModel)
self.dataComboBox.setModel(dataModel)
for index, column in enumerate(dataModel.dataFrame().columns):
dtype = dataModel.dataFrame()[column].dtype
self.updateDelegates(index, dtype)
#self.updateDelegates()
# self.dataTableView.resizeColumnsToContents()
# create a simple item model for our choosing combobox
columnModel = QtGui.QStandardItemModel()
for column in self.df.columns:
columnModel.appendRow(QtGui.QStandardItem(column))
self.chooseColumnComboBox.setModel(columnModel)
self.tableViewColumnDtypes.setModel(dataModel.columnDtypeModel())
self.tableViewColumnDtypes.horizontalHeader().setDefaultSectionSize(200)
self.tableViewColumnDtypes.setItemDelegateForColumn(1, DtypeComboDelegate(self.tableViewColumnDtypes))
dataModel.dtypeChanged.connect(self.updateDelegates)
dataModel.changingDtypeFailed.connect(self.changeColumnValue)
def test_setDataFrame():
dataFrame = pandas.DataFrame([0], columns=["A"])
model = DataFrameModel()
model.setDataFrame(dataFrame)
assert not model.dataFrame().empty
assert model.dataFrame() is dataFrame
with pytest.raises(TypeError) as excinfo:
model.setDataFrame(None)
assert "pandas.core.frame.DataFrame" in unicode(excinfo.value)
def test_setDataFrame():
dataFrame = pandas.DataFrame([0], columns=['A'])
model = DataFrameModel()
model.setDataFrame(dataFrame)
assert not model.dataFrame().empty
assert model.dataFrame() is dataFrame
with pytest.raises(TypeError) as excinfo:
model.setDataFrame(None)
assert "pandas.core.frame.DataFrame" in unicode(excinfo.value)
def test_flags():
model = DataFrameModel(pandas.DataFrame([0], columns=["A"]))
index = model.index(0, 0)
assert index.isValid()
assert model.flags(index) == Qt.ItemIsSelectable | Qt.ItemIsEnabled
model.enableEditing(True)
assert model.flags(index) == Qt.ItemIsSelectable | Qt.ItemIsEnabled | Qt.ItemIsEditable
model.setDataFrame(pandas.DataFrame([True], columns=["A"]))
index = model.index(0, 0)
model.enableEditing(True)
assert model.flags(index) != Qt.ItemIsSelectable | Qt.ItemIsEnabled | Qt.ItemIsEditable
assert model.flags(index) == Qt.ItemIsSelectable | Qt.ItemIsEnabled | Qt.ItemIsUserCheckable
def display_query(selcols):
## setup a new empty model
model1 = DataFrameModel()
## setup an application and create a table view widget
app = QtGui.QApplication([])
widget1 = DataTableWidget()
widget1.resize(1600, 800)
widget1.show()
## asign the created model
widget1.setViewModel(model1)
## fill the model with data
model1.setDataFrame(selcols)
## start the app"""
app.exec_()
return
def test_flags():
model = DataFrameModel(pandas.DataFrame([0], columns=['A']))
index = model.index(0, 0)
assert index.isValid()
assert model.flags(index) == Qt.ItemIsSelectable | Qt.ItemIsEnabled
model.enableEditing(True)
assert model.flags(
index) == Qt.ItemIsSelectable | Qt.ItemIsEnabled | Qt.ItemIsEditable
model.setDataFrame(pandas.DataFrame([True], columns=['A']))
index = model.index(0, 0)
model.enableEditing(True)
assert model.flags(
index) != Qt.ItemIsSelectable | Qt.ItemIsEnabled | Qt.ItemIsEditable
assert model.flags(
index
) == Qt.ItemIsSelectable | Qt.ItemIsEnabled | Qt.ItemIsUserCheckable
# use QtGui from the compat module to take care if correct sip version, etc.
from pandasqt.compat import QtGui
from pandasqt.models.DataFrameModel import DataFrameModel
from pandasqt.views.DataTableView import DataTableWidget
from pandasqt.views._ui import icons_rc
"""setup a new empty model"""
model = DataFrameModel()
"""setup an application and create a table view widget"""
app = QtGui.QApplication([])
widget = DataTableWidget()
widget.resize(800, 600)
widget.show()
"""asign the created model"""
widget.setViewModel(model)
"""create some test data"""
data = {
'A': [10, 11, 12],
'B': [20, 21, 22],
'C': ['Peter Pan', 'Cpt. Hook', 'Tinkerbell']
}
df = pandas.DataFrame(data)
"""convert the column to the numpy.int8 datatype to test the delegates in the table
int8 is limited to -128-127
"""
df['A'] = df['A'].astype(numpy.int8)
df['B'] = df['B'].astype(numpy.float16)
"""fill the model with data"""
model.setDataFrame(df)
"""start the app"""
app.exec_()
from pandasqt.views._ui import icons_rc
"""setup a new empty model"""
model = DataFrameModel()
"""setup an application and create a table view widget"""
app = QtGui.QApplication([])
widget = DataTableWidget()
widget.resize(800, 600)
widget.show()
"""asign the created model"""
widget.setViewModel(model)
"""create some test data"""
data = {
'A': [10, 11, 12],
'B': [20, 21, 22],
'C': ['Peter Pan', 'Cpt. Hook', 'Tinkerbell']
}
df = pandas.DataFrame(data)
"""convert the column to the numpy.int8 datatype to test the delegates in the table
int8 is limited to -128-127
"""
df['A'] = df['A'].astype(numpy.int8)
df['B'] = df['B'].astype(numpy.float16)
"""fill the model with data"""
model.setDataFrame(df)
"""start the app"""
app.exec_()
class TracksterGUI(Ui_MainWindow):
# -----
# Setup
# -----
# PyQt signals to be emitted when the underlying database is change
# Lets components that hold views on that data to update themselves
wl_data_changed = Signal() # Workout log changed
bw_data_changed = Signal() # Body weight log changed
lt_data_changed = Signal() # Lift types database changed
build_data_changed = Signal() # The workout being built in the Build tab was changed
log_data_changed = Signal()
analysis_data_changed = Signal()
def __init__(self):
# super().__init__()
self.db = Backend(filename)
self._wl_model = DataFrameModel(self.db.workout_log, copyDataFrame=False, show_index=True)
self._bw_model = DataFrameModel(self.db.weight_log, copyDataFrame=False, show_index=True)
self._lt_model = DataFrameModel(self.db.lift_types, copyDataFrame=False, show_index=False)
def setupUi(self, main_window):
super().setupUi(main_window)
self.setup_global()
self.__setup_dashboard_tab()
self.__setup_body_weight_tab()
self.__setup_log_tab()
self.__setup_build_tab()
self.__setup_analysis_tab()
self.__connect_update_slots_and_signals()
def setup_global(self):
self._wl_model.timestampFormat = "yyyy-MM-dd"
self._bw_model.timestampFormat = "yyyy-MM-dd"
self._lt_model.timestampFormat = "yyyy-MM-dd"
self.actionSave.triggered.connect(self.save_logs)
self.actionRevert.triggered.connect(self.revert_from_temp)
self.tabs.tabBarClicked.connect(self.switching_main_tabs_event)
def __setup_dashboard_tab(self):
pass
def __setup_body_weight_tab(self):
self.bw_table.setModel(self._bw_model)
self._bw_model.enableEditing(True)
self._bw_model.set_cell_colors(Theme.bw_color_cols, Theme.red_brush, Theme.green_brush)
self.bw_table.tableView.setSortingEnabled(False)
self.bw_table.tableView.scrollToBottom()
self.bw_table.enableEditing(True)
self.bw_date.setDate(QDate.currentDate())
self.bw_plot_data()
self.bw_update_stats()
self.bw_add.clicked.connect(self.bw_add_entry)
self.bw_save.clicked.connect(self.db.save_bw_temp)
self.bw_delete.clicked.connect(self.bw_delete_row)
def __setup_log_tab(self):
self._log_table_view = pd.DataFrame()
self._log_table_model = DataFrameModel(self._log_table_view, copyDataFrame=False, show_index=False)
self._log_table_model.enableEditing(True)
self._log_table_model.dataChanged.connect(self.log_values_changed)
self.log_table.setModel(self._log_table_model)
self.log_table.horizontalHeader().setStretchLastSection(True)
self._log_date = pd.Timestamp.today()
self._log_lift = ''
self._log_unsynced_changes = False
self._log_unsaved_changes = False
self.log_date.setDate(QDate.currentDate())
self.log_cal.setSelectedDate(QDate.currentDate())
self.log_date_changed(pd.Timestamp.today())
self.log_populate_lifts_box()
self.log_populate_table()
self.log_date.dateChanged.connect(self.log_date_selection_changed)
self.log_cal.selectionChanged.connect(self.log_cal_selection_changed)
self.log_add.clicked.connect(self.log_add_entry)
self.log_save.clicked.connect(self.log_sync_changes)
self.log_delete.clicked.connect(self.log_del_row)
def __setup_build_tab(self):
self._build_cur_workout = pd.DataFrame()
self._build_cur_workout_view = pd.DataFrame()
self._build_cur_lift = None
self._build_tgt_e1rm = -1
self._build_tabs = OrderedDict()
self._build_unsaved_changes = False
self._build_cur_model = DataFrameModel(self._build_cur_workout, copyDataFrame=False, show_index=False)
self._build_pre_model = DataFrameModel(dataFrame=None, copyDataFrame=False, show_index=False)
self._build_cur_model_view = DataFrameModel(dataFrame=None, copyDataFrame=False, show_index=False)
self.build_pre_workout.setModel(self._build_pre_model)
self._build_rpe_model = RpeTableModel(self.db)
self.build_RPE.setModel(self._build_rpe_model)
self._build_stats_model = StatsTableModel(self.db)
self.build_stats.setModel(self._build_stats_model)
self.build_date.setDate(QtCore.QDate.currentDate())
self.build_tree_populate()
self.build_search.textChanged.connect(self.build_filter)
self.build_lifts.itemDoubleClicked.connect(self.build_lift_selected)
self.build_previous_slider.valueChanged.connect(self.build_populate_previous_workout_table)
self.build_target.valueChanged.connect(self.build_populate_rpe_table)
self.build_btn_add.clicked.connect(self.build_add_btn_clicked)
self.build_RPE.clicked.connect(self.build_top_set_selected)
self.build_tabs.currentChanged.connect(self.build_lift_tab_changed)
self.build_accept.clicked.connect(self.build_accept_workout)
self.build_clear.clicked.connect(self.build_clear_workout)
self.build_btn_delete.clicked.connect(self.build_delete_row)
def __setup_analysis_tab(self):
self.an_data = {}
self._an_cur_analysis = None
self.an_type.setCurrentIndex(0)
self.an_update_values_box()
self.an_type.currentTextChanged.connect(self.an_update_values_box)
self.an_plots.itemSelectionChanged.connect(self.an_analysis_selected)
self.an_add.clicked.connect(self.an_add_analysis)
self.an_remove.clicked.connect(self.an_remove_analysis)
def __connect_update_slots_and_signals(self):
self.bw_data_changed.connect(self._bw_model.layoutChanged.emit)
self.bw_data_changed.connect(self.bw_plot_data)
self.bw_data_changed.connect(self.bw_update_stats)
self._bw_model.dataFrameChanged.connect(self.bw_data_changed.emit)
self._bw_model.dataChanged.connect(self.bw_data_changed.emit)
self.wl_data_changed.connect(self.log_data_changed.emit)
self.lt_data_changed.connect(self.an_update_values_box)
self.lt_data_changed.connect(self.build_tree_populate)
self.lt_data_changed.connect(self.log_populate_lifts_box)
self.build_data_changed.connect(self.build_update_previous_workout_stats)
self.build_data_changed.connect(self.build_update_current_workout_stats)
self.build_data_changed.connect(self.build_populate_previous_workout_table)
self.build_data_changed.connect(self.build_gen_workout_tables)
self.log_data_changed.connect(self.log_populate_table)
self.log_data_changed.connect(self.log_populate_stats)
self.log_data_changed.connect(partial(self.build_stats.model().update, db_modified=True))
self.analysis_data_changed.connect(self.an_plot_analysis)
self.analysis_data_changed.connect(self.an_update_values_box)
self.analysis_data_changed.connect(self.an_populate_plots_list)
# -----
# Body Weight Tab
# -----
def bw_add_entry(self):
high = None
low = None
bf = None
try:
date = pd.Timestamp(self.bw_date.text())
if self.bw_high.text() != '':
high = float(self.bw_high.text())
if self.bw_low.text() != '':
low = float(self.bw_low.text())
if self.bw_bf.text() != '':
bf = float(self.bw_bf.text()) / 100.0
comments = self.bw_comments.text()
self.db.add_bodyweight_entry(date, high, low, bf, comments)
except (ValueError, TypeError):
pass
self.bw_data_changed.emit()
@pyqtSlot()
def bw_plot_data(self):
# TODO: Make prettier
self.bw_plot.clear()
above_goal_data = np.maximum(self.db.weight_log.High, self.db.weight_log.Goal)
below_goal_data = np.minimum(self.db.weight_log.High, self.db.weight_log.Goal)
self.bw_plot.plot_ts(self.db.weight_log.Goal)
self.bw_plot.plot_ts(above_goal_data)
self.bw_plot.plot_ts(below_goal_data)
self.bw_plot.plot_ts(self.db.weight_log.Low)
above_goal_fill = pg.FillBetweenItem(self.bw_plot.plotItem.curves[0], self.bw_plot.plotItem.curves[1], 'r')
below_goal_fill = pg.FillBetweenItem(self.bw_plot.plotItem.curves[0], self.bw_plot.plotItem.curves[2], 'g')
self.bw_plot.getPlotItem().addItem(above_goal_fill)
self.bw_plot.getPlotItem().addItem(below_goal_fill)
ma_data = pd.rolling_mean(self.db.weight_log.High, 7, min_periods=1)
self.bw_plot.plot_ts(ma_data)
@pyqtSlot()
def bw_update_stats(self):
daily_diff = self.db.weight_log.Diff[self.db.weight_log.Diff.notnull()].iloc[-1]
daily_diff = round(daily_diff, 1)
self.bw_daily_diff.setText(str(daily_diff))
goal_diff = self.db.weight_log.Goal_Diff[self.db.weight_log.Goal_Diff.notnull()].iloc[-1]
goal_diff = round(goal_diff, 1)
self.bw_goal_diff.setText(str(goal_diff))
weekly_diff = self.db.weight_log.High.iloc[-7:].mean() - self.db.weight_log.High.iloc[-14:-7].mean()
weekly_diff = round(weekly_diff, 1)
self.bw_avg_week.setText(str(weekly_diff))
@pyqtSlot()
def bw_delete_row(self):
# self.bw_table.removeRow(triggered=True)
# self.bw_data_changed.emit()
pass
# -----
# Analysis Tab
# -----
def an_add_analysis(self):
data = self.db.workout_log
group = self.an_type.currentText()
val = self.an_value.currentText()
try:
if group == 'Slot':
data = data[data.Slot == val]
elif group == 'Category':
data = data[data.Category == val]
elif group == 'Lift':
data = data[data.Lift == val]
else:
return
except (ValueError, TypeError) as err:
log_err(err, "Invalid analysis type selected: {}, {}".format(group, val))
analysis_funcs = {'E1RMs': analysis.get_max_e1RM, 'Volume': analysis.get_volume,
'Norm V': analysis.calc_normalized_tonnage, 'Fatigue': analysis.get_fatigue}
selected_func = analysis_funcs[self.an_analysis.currentText()]
analyzed_data = selected_func(data)
title = '{}: {} -> {}'.format(self.an_analysis.currentText(), group, val)
if self.an_mov_avg.isChecked():
period = self.an_period.value()
if 'e1rm' in selected_func.__name__:
analyzed_data = analyzed_data.resample('1D', label='right', how=np.max)
elif 'vol' in selected_func.__name__ or 'fatigue' in selected_func.__name__:
analyzed_data = analyzed_data.resample('1D', label='right', how=np.sum)
analyzed_data = analyzed_data.fillna(0)
analyzed_data = pd.rolling_mean(analyzed_data, period, min_periods=1)
if 'fatigue' in selected_func.__name__:
analyzed_data *= 7.0
title += ' ({} day avg)'.format(period)
self.an_data[title] = analyzed_data
self.analysis_data_changed.emit()
@pyqtSlot()
def an_populate_plots_list(self):
self.an_plots.clear()
titles = [x for x in self.an_data.keys()]
self.an_plots.addItems(titles)
@pyqtSlot()
def an_analysis_selected(self, which=None):
if not which or not isinstance(which, str):
which = self.an_plots.currentItem().text()
self._an_cur_analysis = which
self.an_remove.setEnabled(True)
@pyqtSlot()
def an_plot_analysis(self):
self.an_plot.plot_with_shared_axes(self.an_data)
@pyqtSlot()
def an_remove_analysis(self, which):
if which:
if isinstance(which, QTreeWidgetItem):
which = which.text(0)
elif isinstance(which, str):
pass
else:
return
elif pd.notnull(self._an_cur_analysis):
which = self._an_cur_analysis
if which in self.an_data:
self.an_data.pop(which)
self.analysis_data_changed.emit()
if len(self.an_data) > 1:
self.an_remove.setEnabled(False)
@pyqtSlot(str, str)
def an_update_values_box(self):
self.an_value.clear()
type = self.an_type.currentText()
vals = self.db.lift_types[type].unique()
self.an_value.addItems(vals)
# -----
# Log Tab
# -----
@pyqtSlot()
def log_populate_table(self, date=None, lift=None):
if lift and date and isinstance(date, pd.Timestamp) and isinstance(lift, str):
if lift == self._log_cur_lift and date == self._log_date:
return
else:
self._log_cur_lift = lift
self._log_date = date
self._log_table_view = self.db.workout_log[self.db.workout_log.index == self._log_date].reset_index()
self._log_table_view = self._log_table_view[['Slot', 'Category', 'Lift', 'Weight', 'Reps', 'RPE', 'Comments']]
self._log_table_model.setDataFrame(self._log_table_view)
self._log_table_model.dataChanged.emit()
self._log_table_model.layoutChanged.emit()
@pyqtSlot()
def log_populate_stats(self, lift=None):
if pd.isnull(self.log_date) or self._log_table_view.empty:
return
self.log_tree.clear()
cur_wkt = self.db.workout_log[self.db.workout_log.index == self._log_date]
pre_30d = self.db.workout_log[self.db.workout_log.index >= self._log_date - pd.Timedelta(days=30)]
pre_30d = pre_30d[pre_30d.index < self._log_date]
e1RM_node = QTreeWidgetItem()
e1RM_node.setText(0, 'e1RMs:')
for lift, lift_data in cur_wkt.groupby('Lift'):
e1RM = max(analysis.get_max_e1RM(lift_data))
if pre_30d.Lift.isin([lift]).any():
e1RM_pre_30d = max(analysis.get_max_e1RM(pre_30d[pre_30d.Lift == lift]))
else:
e1RM_pre_30d = ''
child_node = QTreeWidgetItem()
child_node.setText(0, str(lift))
child_node.setText(1, str(e1RM))
child_node.setText(2, str(e1RM_pre_30d))
e1RM_node.addChild(child_node)
volume_node = QTreeWidgetItem()
volume_node.setText(0, 'Volume:')
for cat, cat_data in cur_wkt.groupby('Category'):
vol = sum(cat_data.Volume)
if pre_30d.Category.isin([cat]).any():
vol_pre_30d = round(pre_30d[pre_30d.Category == cat].resample('1d', how=np.sum).Volume.mean())
else:
vol_pre_30d = ''
child_node = QTreeWidgetItem()
child_node.setText(0, str(cat))
child_node.setText(1, str(vol))
child_node.setText(2, str(vol_pre_30d))
volume_node.addChild(child_node)
nt_node = QTreeWidgetItem()
nt_node.setText(0, 'Normalized Tonnage:')
for cat, cat_data in cur_wkt.groupby('Category'):
nt = round(analysis.calc_normalized_tonnage(cat_data).sum())
if pre_30d.Category.isin([cat]).any():
nt_pre_30d = round(analysis.calc_normalized_tonnage(
pre_30d[pre_30d.Category == cat]).resample('1d', how=np.sum).mean())
else:
nt_pre_30d = ''
child_node = QTreeWidgetItem()
child_node.setText(0, str(cat))
child_node.setText(1, str(nt))
child_node.setText(2, str(nt_pre_30d))
nt_node.addChild(child_node)
# TODO: Figure out why fatigue isn't being normalized to weekly average
fatigue_node = QTreeWidgetItem()
fatigue_node.setText(0, 'Fatigue:')
for slot, slot_data in cur_wkt.groupby('Slot'):
fatigue = analysis.get_fatigue(slot_data)
fatigue = fatigue.resample('1d', how=np.sum)
fatigue = fatigue.fillna(0).iloc[-7:].sum()
if pre_30d.Slot.isin([slot]).any():
fatigue_30d = analysis.get_fatigue(pre_30d[pre_30d.Slot == slot])
fatigue_30d = fatigue_30d.resample('1d', how=np.sum)
fatigue_30d = round(fatigue_30d.fillna(0).mean() * 7.0, 1)
else:
fatigue_30d = ''
child_node = QTreeWidgetItem()
child_node.setText(0, str(slot))
child_node.setText(1, str(fatigue))
child_node.setText(2, str(fatigue_30d))
fatigue_node.addChild(child_node)
self.log_tree.addTopLevelItems([e1RM_node, volume_node, fatigue_node, nt_node])
self.log_tree.expandAll()
@pyqtSlot()
def log_add_entry(self):
try:
date = pd.Timestamp(self.log_date.date().toPyDate())
lift = self.log_lift.currentText()
if not self.db.is_valid_lift(lift):
raise ValueError('{} is not a valid lift'.format(lift))
raw_sets = self.log_sets.text().split(',')
parsed_sets = []
for set in raw_sets:
parsed_sets.extend(analysis.parse_sets(set.strip()))
comments = self.log_comments.text()
for set in parsed_sets:
weight, reps, rpe = set
self.db.add_set(date, lift, weight, reps, rpe, comments)
self.db.calc_workout_data()
self.log_date_changed(date - pd.Timedelta(days=1))
self.log_date_changed(date)
self.wl_data_changed.emit()
self.log_lift.setCurrentText('')
self.log_sets.setText('')
except (ValueError, TypeError) as err:
log_err(err, "Couldn't parse log entry")
@pyqtSlot()
def log_del_row(self):
selection = self.log_table.selectedIndexes()
rows = [index.row() for index in selection]
# TODO: add enable/disable toggle for delete button based on selection status
if rows and len(rows) > 0:
abs_rows = [self.log_get_absolute_index(self._log_date, rel_row) for rel_row in rows]
self.db.workout_log.reset_index(inplace=True)
self.db.workout_log.drop(self.db.workout_log.index[abs_rows], inplace=True)
self.db.workout_log.set_index('Date', inplace=True)
self.log_table.model().removeDataFrameRows(rows)
self._log_unsynced_changes = True
self._log_unsaved_changes = True
@pyqtSlot()
def log_values_changed(self):
table_data = self._log_table_model.dataFrame()
idx = table_data.index
abs_idx = self.log_get_absolute_index(self._log_date, idx)
if not table_data.empty:
filtered_master = self.db.workout_log.iloc[abs_idx].reset_index()[table_data.keys()]
if not table_data.equals(filtered_master):
self._log_unsynced_changes = True
self._log_unsaved_changes = True
return True
else:
return False
else:
return False
@pyqtSlot()
def log_sync_changes(self, dont_prompt=False):
if self._log_unsynced_changes and (self.prompt_save_changes() or dont_prompt):
new_data = self._log_table_model.dataFrame()
self.db.merge_workout_data(new_data, self._log_date)
self._log_unsynced_changes = False
@pyqtSlot()
def log_save_changes(self):
if self._log_unsaved_changes and self.dialog_save():
if self._log_unsynced_changes:
self.log_sync_changes(dont_prompt=True)
self.db.save_to_disk()
self._log_unsaved_changes = False
@pyqtSlot()
def log_import(self):
pass
@pyqtSlot()
def log_date_changed(self, date):
if self._log_unsynced_changes:
self.log_sync_changes()
if isinstance(date, pd.Timestamp) and pd.notnull(date) and self._log_date != date:
self._log_date = date
if self.log_date.date().toPyDate() != date.to_pydatetime():
self.log_date.setDate(QDate(date.to_datetime()))
if self.log_cal.selectedDate().toPyDate() != date.to_pydatetime():
self.log_cal.setSelectedDate(QDate(date.to_datetime()))
self.log_data_changed.emit()
@pyqtSlot()
def log_date_selection_changed(self):
try:
date = pd.Timestamp(self.log_date.date().toPyDate())
self.log_date_changed(date)
except (ValueError, TypeError) as err:
log_err(err, "Couldn't convert log_date's value to a date... skipping")
@pyqtSlot()
def log_cal_selection_changed(self):
try:
date = pd.Timestamp(self.log_cal.selectedDate().toPyDate())
self.log_date_changed(date)
except (ValueError, TypeError) as err:
log_err(err, "Couldn't convert log_cal's value to a date... skipping")
@pyqtSlot()
def log_populate_lifts_box(self):
lifts = [str(lift) for lift in self.db.lift_types.Lift]
self.log_lift.addItems(lifts)
def log_get_absolute_index(self, date, offset):
dat = self.db.workout_log.reset_index()
dat = dat[dat.Date == date]
if not dat.empty:
return dat.index[offset]
else:
return []
@pyqtSlot()
def log_tab_gain_focus(self):
self.log_data_changed.emit()
@pyqtSlot()
def log_tab_lose_focus(self):
self.log_save_changes()
# -----
# Build Tab
# -----
# TODO: recalc e1RM in log table after value changed, also recalc curr workout stats
# TODO: e1RM Calculator button
# TODO: Clear button only clears current build_tab and deletes tab
# TODO: test/implement delete button
# TODO: Quick add button
def build_filter(self):
filter_string = self.build_search.text()
if not filter_string:
filter_string = ''
matching_indices = self.db.lift_types.Lift.map(lambda val: filter_string.lower() in val.lower())
dat = self.db.lift_types[matching_indices]
self.build_tree_populate(dat)
@pyqtSlot()
def build_tree_populate(self, data=None):
self.build_lifts.clear()
if not isinstance(data, pd.DataFrame):
data = self.db.lift_types
dat = data.reset_index()
root_children = []
for cat, cat_group in dat.groupby('Category', as_index=True, sort=False):
root_child = QTreeWidgetItem()
root_child.setText(0, cat)
root_child.setBackground(0, Theme.gray_brush)
root_child.setBackground(1, Theme.gray_brush)
lift_children = []
for lift, _ in cat_group.groupby('Lift'):
lift_child = QTreeWidgetItem()
lift_child.setText(1, lift)
lift_children.append(lift_child)
root_child.insertChildren(1, lift_children)
root_children.append(root_child)
self.build_lifts.setColumnCount(2)
self.build_lifts.insertTopLevelItems(0, root_children)
self.build_lifts.expandAll()
@pyqtSlot(str)
def build_lift_selected(self, lift=None):
# TODO: Clean this mess up and make it pretty
# TODO: Clear current workout stats
if lift:
if isinstance(lift, QtWidgets.QTreeWidgetItem):
txt = lift.text(1)
elif isinstance(lift, str):
txt = lift
else:
txt = ''
else:
txt = self.build_lifts.currentItem().text(1)
if txt:
if txt == self._build_cur_lift:
return
else:
self._build_cur_lift = txt
else:
return
pre_workouts = analysis.get_max_e1RM(self.db.workout_log[self.db.workout_log.Lift == self._build_cur_lift])
pre_e1RM = pre_workouts[pre_workouts.notnull()][-1]
self._build_tgt_e1rm = pre_e1RM
self.build_populate_rpe_table()
self.build_target.setValue(int(self._build_tgt_e1rm))
self.build_btn_add.setEnabled(True)
self.build_workout_switch_tables()
self.build_data_changed.emit()
@pyqtSlot(int)
def build_populate_rpe_table(self, tgt_e1rm=None):
if tgt_e1rm:
if not isinstance(tgt_e1rm, Number):
if issubclass(tgt_e1rm, QtWidgets.QWidget):
tgt_e1rm = tgt_e1rm.text()
tgt_e1rm = int(tgt_e1rm)
if self._build_tgt_e1rm == tgt_e1rm:
return
self._build_tgt_e1rm = tgt_e1rm
elif self._build_tgt_e1rm:
tgt_e1rm = self._build_tgt_e1rm
else:
tgt_e1rm = None
self.build_RPE.model().update(e1rm=tgt_e1rm)
self.build_RPE.model().layoutChanged.emit()
@pyqtSlot(int)
def build_populate_previous_workout_table(self, lookback=None):
# TODO: Concatenate current workout onto previous ones to allow more accurate stats
if not self._build_cur_lift or not self.db.is_valid_lift(self._build_cur_lift):
return
elif not lookback:
lookback = self.build_previous_slider.maximum()
lift_workouts = self.db.workout_log[self.db.workout_log.Lift == self._build_cur_lift]
idx_lookback = -1 * (int(self.build_previous_slider.maximum()) + 1) + lookback
date_idx = sorted(lift_workouts.index.unique())[idx_lookback]
workout = lift_workouts[lift_workouts.index == date_idx].reset_index()
workout = workout[['Lift', 'Weight', 'Reps', 'RPE', 'e1RM']]
self._build_pre_model.setDataFrame(workout, copyDataFrame=False)
self.build_pre_workout.scrollToBottom()
@pyqtSlot()
def build_update_current_workout_stats(self):
# TODO: Make this reflect changes that are manually entered into the workout table
if self._build_cur_workout.empty or not self._build_cur_lift or not self.db.is_valid_lift(self._build_cur_lift):
self.build_stats.model().clear(what='current')
else:
self.build_stats.model().update(self._build_cur_workout, self._build_cur_lift)
@pyqtSlot()
def build_update_previous_workout_stats(self):
if not self._build_cur_lift or not self.db.is_valid_lift(self._build_cur_lift):
self.build_stats.model().clear(what='all')
else:
self.build_stats.model().update(cur_lift=self._build_cur_lift)
@pyqtSlot()
def build_top_set_selected(self, index):
if not index.isValid():
return
try:
top_set = index.data().split('(')[0].strip()
self.build_top_set.setText(top_set)
except (ValueError, AttributeError):
pass
@pyqtSlot()
def build_add_btn_clicked(self):
date = pd.Timestamp(self.build_date.text())
sets = []
# Warmup sets
if self.build_warmup.text() == '': # Auto-calculate warmup if no text present
warmup = analysis.calc_warmup(self._build_tgt_e1rm, self._build_cur_lift)
sets.extend(warmup)
else:
for set in self.build_warmup.text().split(','):
parsed = analysis.parse_sets(set.strip(), self._build_tgt_e1rm)
sets.extend(parsed)
# Main/Drop sets
if self.build_top_set.text() != '':
top_set = analysis.parse_sets(self.build_top_set.text())
sets.extend(top_set)
top_weight, top_reps, top_rpe = top_set[-1]
top_e1rm = analysis.calc_e1RM(self._build_cur_lift, top_weight, top_reps, top_rpe)
fatigue = self.build_fatigue.value()
self._build_cur_workout = self.db.make_workout(self._build_cur_lift, sets, date)
drop_sets = self.build_get_drop_sets(top_set[-1], top_e1rm, fatigue, date)
self._build_cur_workout = pd.concat((self._build_cur_workout, drop_sets), ignore_index=True)
# Perform housekeeping
self.build_clear.setEnabled(True)
self.build_data_changed.emit()
self.build_accept.setEnabled(True)
self._log_unsaved_changes = True
def build_get_drop_sets(self, top_set, e1RM, fatigue, date):
dialog = QtWidgets.QDialog()
dialog.ui = DialogDrop(self.db, top_set, e1RM, date, self._build_cur_lift, fatigue, self._build_cur_workout)
dialog.ui.setupUi(dialog)
dialog.exec_()
dialog.show()
if bool(dialog.result()):
return dialog.ui.drop_sets
else:
return pd.DataFrame()
def build_gen_workout_tables(self):
if self._build_cur_workout.empty:
return
for lift in self._build_cur_workout.Lift.unique():
if lift not in self._build_tabs:
if len(self._build_tabs) == 0:
self.build_tabs.removeTab(0)
tab = QtWidgets.QWidget()
tab.setObjectName(lift)
self.build_tabs.addTab(tab, lift)
tab_table = QtWidgets.QTableView()
self._build_cur_model_view.setDataFrame(self._build_cur_workout_view)
tab_table.setModel(self._build_cur_model_view)
tab_table.horizontalHeader().setDefaultSectionSize(93)
tab_table.clicked.connect(self.build_workout_cell_clicked)
layout = QtWidgets.QVBoxLayout(tab)
layout.addWidget(tab_table)
self._build_tabs[lift] = tab_table
self.build_workout_switch_tables()
@pyqtSlot()
def build_workout_switch_tables(self):
if self._build_cur_workout.empty or len(self._build_tabs) == 0:
return
lift_name_tab = -1
for lift_name in self._build_tabs.keys():
lift_name_tab += 1
if lift_name == self._build_cur_lift:
break
if lift_name_tab == -1:
return
self.build_tabs.setCurrentIndex(lift_name_tab)
if self._build_cur_lift in self._build_tabs:
try:
model = self._build_tabs[self._build_cur_lift].model()
self.build_save_changes(model.dataFrame())
self._build_cur_workout_view = self._build_cur_workout[self._build_cur_workout.Lift == self._build_cur_lift]
self._build_cur_workout_view = self._build_cur_workout_view[['Lift', 'Weight', 'Reps', 'RPE', 'e1RM']]
model.setDataFrame(self._build_cur_workout_view)
model.enableEditing(True)
model.dataChanged.emit()
model.layoutChanged.emit()
except Exception as err:
log_err(err, "Couldn't emit datachanged signals to table model for {}".format(self._build_cur_lift))
@pyqtSlot()
def build_lift_tab_changed(self, name):
if self.build_tabs.currentWidget():
try:
lift_name = self.build_tabs.currentWidget().objectName()
self.build_lift_selected(lift_name)
except Exception:
pass
@pyqtSlot()
def build_workout_cell_clicked(self):
self.build_btn_delete.setEnabled(True)
# TODO: Tap dataChanged to update e1RM col and workout stats
@pyqtSlot()
def build_save_changes(self, data):
if not data.empty:
lift = data.Lift.unique()[0]
self._build_cur_workout = self._build_cur_workout[self._build_cur_workout.Lift != lift]
for row in self._build_cur_workout_view.itertuples():
new_set = self.db.make_set(lift, row.Weight, row.Reps, self._build_cur_workout.Date.iloc[0], row.RPE)
self._build_cur_workout = self._build_cur_workout.append(new_set, ignore_index=True)
@pyqtSlot()
def build_accept_workout(self):
if not self._build_cur_workout.empty:
self._build_cur_workout = self._build_cur_workout.set_index('Date')
self.db.workout_log = self.db.workout_log.append(self._build_cur_workout)
self.build_clear_workout()
self.wl_data_changed.emit()
@pyqtSlot()
def build_delete_row(self):
curr_lift_table = self._build_tabs[self._build_cur_lift]
rows = [index.row for index in curr_lift_table.currentSelection()]
self._build_cur_model_view.removeDataFrameRows(rows)
self.build_btn_delete.setEnabled(False)
@pyqtSlot()
def build_clear_workout(self):
self._build_cur_lift = None
self._build_cur_workout = pd.DataFrame()
self.build_tabs.clear()
self._build_tabs.clear()
self.build_accept.setEnabled(False)
self.build_clear.setEnabled(False)
self.build_stats.model().clear(what='all')
self.build_RPE.model().clear()
self.build_pre_workout.model().dataChanged.emit()
self.build_pre_workout.model().layoutChanged.emit()
self.build_data_changed.emit()
# -----
# Administrative
# -----
@pyqtSlot(int)
def switching_main_tabs_event(self, new_idx=None):
old_idx = self.tabs.currentIndex()
self.main_tab_losing_focus_event(old_idx)
self.main_tab_gaining_focus_event(new_idx)
def main_tab_losing_focus_event(self, idx_of):
if idx_of == -1:
return
elif idx_of == self.tabs.indexOf(self.dash):
pass
elif idx_of == self.tabs.indexOf(self.bw):
pass
elif idx_of == self.tabs.indexOf(self.analysis):
pass
elif idx_of == self.tabs.indexOf(self.workout_log):
self.log_tab_lose_focus()
elif idx_of == self.tabs.indexOf(self.builder):
pass
def main_tab_gaining_focus_event(self, idx_of):
if idx_of == -1:
return
elif idx_of == self.tabs.indexOf(self.dash):
pass
elif idx_of == self.tabs.indexOf(self.bw):
pass
elif idx_of == self.tabs.indexOf(self.analysis):
pass
elif idx_of == self.tabs.indexOf(self.workout_log):
self.log_tab_gain_focus()
elif idx_of == self.tabs.indexOf(self.builder):
pass
@pyqtSlot()
def prompt_save_changes(self, selected_tab=None):
dialog = QtWidgets.QDialog()
dialog.ui = DialogUnsaved()
dialog.ui.setupUi(dialog)
dialog.exec_()
dialog.show()
return bool(dialog.result())
def save_logs(self):
print('Saving')
do_save = self.dialog_save()
if do_save:
self.db.save_to_disk()
self._log_unsynced_changes = False
def revert_from_temp(self):
do_revert, which_log, which_bak = self.dialog_revert()
if do_revert:
self.db.restore_from_temp(which_log, which_bak)
@staticmethod
def dialog_save():
dialog = QtWidgets.QDialog()
dialog.ui = DialogSave()
dialog.ui.setupUi(dialog)
dialog.exec_()
dialog.show()
return bool(dialog.result())
def dialog_revert(self):
dialog = QtWidgets.QDialog()
dialog.ui = DialogRevert(dialog, self.db)
dialog.exec_()
dialog.show()
which_log = dialog.ui.revert_to_log
which_file = dialog.ui.revert_to_file
return bool(dialog.result()), which_log, which_file