Files
Submissions-App/src/submissions/frontend/widgets/controls_chart.py

355 lines
15 KiB
Python

"""
Handles display of control charts
"""
import re
from datetime import timedelta
from typing import Tuple
from PyQt6.QtWebEngineWidgets import QWebEngineView
from PyQt6.QtWidgets import (
QWidget, QVBoxLayout, QComboBox, QHBoxLayout,
QDateEdit, QLabel, QSizePolicy
)
from PyQt6.QtCore import QSignalBlocker
from backend.db import ControlType, Control
from PyQt6.QtCore import QDate, QSize
import logging
from pandas import DataFrame
from tools import Report, Result, get_unique_values_in_df_column, Settings, report_result
# from backend.excel.reports import convert_data_list_to_df
from frontend.visualizations.control_charts import CustomFigure
logger = logging.getLogger(f"submissions.{__name__}")
class ControlsViewer(QWidget):
def __init__(self, parent: QWidget) -> None:
super().__init__(parent)
self.app = self.parent().parent()
# logger.debug(f"\n\n{self.app}\n\n")
self.report = Report()
self.datepicker = ControlsDatePicker()
self.webengineview = QWebEngineView()
# set tab2 layout
self.layout = QVBoxLayout(self)
self.control_typer = QComboBox()
# NOTE: fetch types of controls
con_types = [item.name for item in ControlType.query()]
self.control_typer.addItems(con_types)
# NOTE: create custom widget to get types of analysis
self.mode_typer = QComboBox()
mode_types = Control.get_modes()
self.mode_typer.addItems(mode_types)
# NOTE: create custom widget to get subtypes of analysis
self.sub_typer = QComboBox()
self.sub_typer.setEnabled(False)
# NOTE: add widgets to tab2 layout
self.layout.addWidget(self.datepicker)
self.layout.addWidget(self.control_typer)
self.layout.addWidget(self.mode_typer)
self.layout.addWidget(self.sub_typer)
self.layout.addWidget(self.webengineview)
self.setLayout(self.layout)
self.controls_getter()
self.control_typer.currentIndexChanged.connect(self.controls_getter)
self.mode_typer.currentIndexChanged.connect(self.controls_getter)
self.datepicker.start_date.dateChanged.connect(self.controls_getter)
self.datepicker.end_date.dateChanged.connect(self.controls_getter)
def controls_getter(self):
"""
Lookup controls from database and send to chartmaker
"""
self.controls_getter_function()
@report_result
def controls_getter_function(self):
"""
Get controls based on start/end dates
"""
report = Report()
# NOTE: subtype defaults to disabled
try:
self.sub_typer.disconnect()
except TypeError:
pass
# NOTE: correct start date being more recent than end date and rerun
if self.datepicker.start_date.date() > self.datepicker.end_date.date():
logger.warning("Start date after end date is not allowed!")
threemonthsago = self.datepicker.end_date.date().addDays(-60)
# NOTE: block signal that will rerun controls getter and set start date
# Without triggering this function again
with QSignalBlocker(self.datepicker.start_date) as blocker:
self.datepicker.start_date.setDate(threemonthsago)
self.controls_getter()
self.report.add_result(report)
return
# NOTE: convert to python useable date objects
self.start_date = self.datepicker.start_date.date().toPyDate()
self.end_date = self.datepicker.end_date.date().toPyDate()
self.con_type = self.control_typer.currentText()
self.mode = self.mode_typer.currentText()
self.sub_typer.clear()
# NOTE: lookup subtypes
try:
sub_types = ControlType.query(name=self.con_type).get_subtypes(mode=self.mode)
except AttributeError:
sub_types = []
if sub_types != []:
# NOTE: block signal that will rerun controls getter and update sub_typer
with QSignalBlocker(self.sub_typer) as blocker:
self.sub_typer.addItems(sub_types)
self.sub_typer.setEnabled(True)
self.sub_typer.currentTextChanged.connect(self.chart_maker)
else:
self.sub_typer.clear()
self.sub_typer.setEnabled(False)
self.chart_maker()
return report
def chart_maker(self):
"""
Creates plotly charts for webview
"""
self.chart_maker_function()
@report_result
def chart_maker_function(self):
"""
Create html chart for controls reporting
Args:
obj (QMainWindow): original app window
Returns:
Tuple[QMainWindow, dict]: Collection of new main app window and result dict
"""
report = Report()
# logger.debug(f"Control getter context: \n\tControl type: {self.con_type}\n\tMode: {self.mode}\n\tStart
# Date: {self.start_date}\n\tEnd Date: {self.end_date}") NOTE: set the subtype for kraken
if self.sub_typer.currentText() == "":
self.subtype = None
else:
self.subtype = self.sub_typer.currentText()
# logger.debug(f"Subtype: {self.subtype}")
# NOTE: query all controls using the type/start and end dates from the gui
controls = Control.query(control_type=self.con_type, start_date=self.start_date, end_date=self.end_date)
# NOTE: if no data found from query set fig to none for reporting in webview
if controls is None:
fig = None
else:
# NOTE: change each control to list of dictionaries
data = [control.convert_by_mode(mode=self.mode) for control in controls]
# NOTE: flatten data to one dimensional list
data = [item for sublist in data for item in sublist]
# logger.debug(f"Control objects going into df conversion: {type(data)}")
if not data:
report.add_result(Result(status="Critical", msg="No data found for controls in given date range."))
return
# NOTE send to dataframe creator
df = self.convert_data_list_to_df(input_df=data)
if self.subtype is None:
title = self.mode
else:
title = f"{self.mode} - {self.subtype}"
# NOTE: send dataframe to chart maker
df, modes = self.prep_df(ctx=self.app.ctx, df=df)
fig = CustomFigure(df=df, ytitle=title, modes=modes)
# logger.debug(f"Updating figure...")
# NOTE: construct html for webview
html = fig.to_html()
# logger.debug(f"The length of html code is: {len(html)}")
self.webengineview.setHtml(html)
self.webengineview.update()
# logger.debug("Figure updated... I hope.")
return report
def convert_data_list_to_df(self, input_df: list[dict]) -> DataFrame:
"""
Convert list of control records to dataframe
Args:
ctx (dict): settings passed from gui
input_df (list[dict]): list of dictionaries containing records
subtype (str | None, optional): sub_type of submission type. Defaults to None.
Returns:
DataFrame: dataframe of controls
"""
df = DataFrame.from_records(input_df)
safe = ['name', 'submitted_date', 'genus', 'target']
for column in df.columns:
if "percent" in column:
count_col = [item for item in df.columns if "count" in item][0]
# NOTE: The actual percentage from kraken was off due to exclusion of NaN, recalculating.
df[column] = 100 * df[count_col] / df.groupby('name')[count_col].transform('sum')
if column not in safe:
if self.subtype is not None and column != self.subtype:
del df[column]
# NOTE: move date of sample submitted on same date as previous ahead one.
df = self.displace_date(df=df)
# NOTE: ad hoc method to make data labels more accurate.
df = self.df_column_renamer(df=df)
return df
def df_column_renamer(self, df: DataFrame) -> DataFrame:
"""
Ad hoc function I created to clarify some fields
Args:
df (DataFrame): input dataframe
Returns:
DataFrame: dataframe with 'clarified' column names
"""
df = df[df.columns.drop(list(df.filter(regex='_hashes')))]
return df.rename(columns={
"contains_ratio": "contains_shared_hashes_ratio",
"matches_ratio": "matches_shared_hashes_ratio",
"kraken_count": "kraken2_read_count_(top_50)",
"kraken_percent": "kraken2_read_percent_(top_50)"
})
def displace_date(self, df: DataFrame) -> DataFrame:
"""
This function serves to split samples that were submitted on the same date by incrementing dates.
It will shift the date forward by one day if it is the same day as an existing date in a list.
Args:
df (DataFrame): input dataframe composed of control records
Returns:
DataFrame: output dataframe with dates incremented.
"""
# logger.debug(f"Unique items: {df['name'].unique()}")
# NOTE: get submitted dates for each control
dict_list = [dict(name=item, date=df[df.name == item].iloc[0]['submitted_date']) for item in
sorted(df['name'].unique())]
previous_dates = []
for _, item in enumerate(dict_list):
df, previous_dates = self.check_date(df=df, item=item, previous_dates=previous_dates)
return df
def check_date(self, df: DataFrame, item: dict, previous_dates: list) -> Tuple[DataFrame, list]:
"""
Checks if an items date is already present in df and adjusts df accordingly
Args:
df (DataFrame): input dataframe
item (dict): control for checking
previous_dates (list): list of dates found in previous controls
Returns:
Tuple[DataFrame, list]: Output dataframe and appended list of previous dates
"""
try:
check = item['date'] in previous_dates
except IndexError:
check = False
previous_dates.append(item['date'])
if check:
# logger.debug(f"We found one! Increment date!\n\t{item['date']} to {item['date'] + timedelta(days=1)}")
# NOTE: get df locations where name == item name
mask = df['name'] == item['name']
# NOTE: increment date in dataframe
df.loc[mask, 'submitted_date'] = df.loc[mask, 'submitted_date'].apply(lambda x: x + timedelta(days=1))
item['date'] += timedelta(days=1)
passed = False
else:
passed = True
# logger.debug(f"\n\tCurrent date: {item['date']}\n\tPrevious dates:{previous_dates}")
# logger.debug(f"DF: {type(df)}, previous_dates: {type(previous_dates)}")
# NOTE: if run didn't lead to changed date, return values
if passed:
# logger.debug(f"Date check passed, returning.")
return df, previous_dates
# NOTE: if date was changed, rerun with new date
else:
logger.warning(f"Date check failed, running recursion")
df, previous_dates = self.check_date(df, item, previous_dates)
return df, previous_dates
def prep_df(self, ctx: Settings, df: DataFrame) -> DataFrame:
"""
Constructs figures based on parsed pandas dataframe.
Args:
ctx (Settings): settings passed down from gui
df (pd.DataFrame): input dataframe
ytitle (str | None, optional): title for the y-axis. Defaults to None.
Returns:
Figure: Plotly figure
"""
# from backend.excel import drop_reruns_from_df
# converts starred genera to normal and splits off list of starred
genera = []
if df.empty:
return None
for item in df['genus'].to_list():
try:
if item[-1] == "*":
genera.append(item[-1])
else:
genera.append("")
except IndexError:
genera.append("")
df['genus'] = df['genus'].replace({'\*': ''}, regex=True).replace({"NaN": "Unknown"})
df['genera'] = genera
# NOTE: remove original runs, using reruns if applicable
df = self.drop_reruns_from_df(ctx=ctx, df=df)
# NOTE: sort by and exclude from
sorts = ['submitted_date', "target", "genus"]
exclude = ['name', 'genera']
modes = [item for item in df.columns if item not in sorts and item not in exclude] # and "_hashes" not in item]
# NOTE: Set descending for any columns that have "{mode}" in the header.
ascending = [False if item == "target" else True for item in sorts]
df = df.sort_values(by=sorts, ascending=ascending)
# logger.debug(df[df.isna().any(axis=1)])
# NOTE: actual chart construction is done by
return df, modes
def drop_reruns_from_df(self, ctx: Settings, df: DataFrame) -> DataFrame:
"""
Removes semi-duplicates from dataframe after finding sequencing repeats.
Args:
settings (dict): settings passed from gui
df (DataFrame): initial dataframe
Returns:
DataFrame: dataframe with originals removed in favour of repeats.
"""
if 'rerun_regex' in ctx:
sample_names = get_unique_values_in_df_column(df, column_name="name")
rerun_regex = re.compile(fr"{ctx.rerun_regex}")
for sample in sample_names:
if rerun_regex.search(sample):
first_run = re.sub(rerun_regex, "", sample)
df = df.drop(df[df.name == first_run].index)
return df
class ControlsDatePicker(QWidget):
"""
custom widget to pick start and end dates for controls graphs
"""
def __init__(self) -> None:
super().__init__()
self.start_date = QDateEdit(calendarPopup=True)
# NOTE: start date is two months prior to end date by default
twomonthsago = QDate.currentDate().addDays(-60)
self.start_date.setDate(twomonthsago)
self.end_date = QDateEdit(calendarPopup=True)
self.end_date.setDate(QDate.currentDate())
self.layout = QHBoxLayout()
self.layout.addWidget(QLabel("Start Date"))
self.layout.addWidget(self.start_date)
self.layout.addWidget(QLabel("End Date"))
self.layout.addWidget(self.end_date)
self.setLayout(self.layout)
self.setSizePolicy(QSizePolicy.Policy.Expanding, QSizePolicy.Policy.Fixed)
def sizeHint(self) -> QSize:
return QSize(80,20)