145 lines
5.2 KiB
Python
145 lines
5.2 KiB
Python
'''
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Contains all operations for creating charts, graphs and visual effects.
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'''
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from datetime import timedelta, date
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from pathlib import Path
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from typing import Generator
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import plotly
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from PyQt6.QtWidgets import QWidget
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import pandas as pd, logging
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from plotly.graph_objects import Figure
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from tools import divide_chunks
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logger = logging.getLogger(f"submissions.{__name__}")
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class CustomFigure(Figure):
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df = None
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def __init__(self, df: pd.DataFrame, settings: dict, modes: list, ytitle: str | None = None, parent: QWidget | None = None):
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super().__init__()
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try:
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months = int(settings['months'])
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except KeyError:
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months = 6
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self.df = df
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self.update_xaxes(range=[settings['start_date'] - timedelta(days=1), settings['end_date']])
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self.generic_figure_markers(modes=modes, ytitle=ytitle, months=months)
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def generic_figure_markers(self, modes: list = [], ytitle: str | None = None, months: int = 6):
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"""
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Adds standard layout to figure.
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Args:
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fig (Figure): Input figure.
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modes (list, optional): List of modes included in figure. Defaults to [].
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ytitle (str, optional): Title for the y-axis. Defaults to None.
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Returns:
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Figure: Output figure with updated titles, rangeslider, buttons.
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"""
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if modes:
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ytitle = modes[0]
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self.update_layout(
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xaxis_title="Submitted Date (* - Date parsed from fastq file creation date)",
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yaxis_title=ytitle,
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showlegend=True,
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barmode='stack',
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updatemenus=[
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dict(
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type="buttons",
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direction="right",
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x=0.7,
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y=1.2,
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showactive=True,
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buttons=[button for button in self.make_pyqt_buttons(modes=modes)],
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)
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]
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)
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self.update_xaxes(
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rangeslider_visible=True,
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rangeselector=dict(
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buttons=[button for button in self.make_plotly_buttons(months=months)]
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)
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)
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assert isinstance(self, CustomFigure)
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@classmethod
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def make_plotly_buttons(cls, months: int = 6) -> Generator[dict, None, None]:
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"""
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Creates html buttons to zoom in on date areas
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Args:
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months (int, optional): Number of months of data given. Defaults to 6.
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Yields:
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Generator[dict, None, None]: Button details.
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"""
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rng = [1]
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if months > 2:
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rng += [iii for iii in range(3, months, 3)]
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buttons = [dict(count=iii, label=f"{iii}m", step="month", stepmode="backward") for iii in rng]
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if months > date.today().month:
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buttons += [dict(count=1, label="YTD", step="year", stepmode="todate")]
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buttons += [dict(step="all")]
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for button in buttons:
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yield button
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def make_pyqt_buttons(self, modes: list) -> Generator[dict, None, None]:
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"""
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Creates list of buttons with one for each mode to be used in showing/hiding mode traces.
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Args:
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modes (list): list of modes used by main parser.
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fig_len (int): number of traces in the figure
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Returns:
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Generator[dict, None, None]: list of buttons.
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"""
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fig_len = len(self.data)
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if len(modes) > 1:
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for ii, mode in enumerate(modes):
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# NOTE: What I need to do is create a list of bools with the same length as the fig.data
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mode_vis = [True] * fig_len
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# NOTE: And break it into {len(modes)} chunks
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mode_vis = list(divide_chunks(mode_vis, len(modes)))
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# NOTE: Then, for each chunk, if the chunk index isn't equal to the index of the current mode, set to false
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for jj, sublist in enumerate(mode_vis):
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if jj != ii:
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mode_vis[jj] = [not elem for elem in mode_vis[jj]]
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# NOTE: Finally, flatten list.
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mode_vis = [item for sublist in mode_vis for item in sublist]
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# NOTE: Now, yield button to add to list
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yield dict(label=mode, method="update", args=[
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{"visible": mode_vis},
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{"yaxis.title.text": mode},
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])
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@property
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def html(self) -> str:
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"""
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Creates final html code from plotly
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Returns:
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str: html string
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"""
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html = f'<html><body>'
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if self is not None:
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# NOTE: Just cannot get this load from string to freaking work.
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# html += self.to_html(include_plotlyjs='cdn', full_html=False)
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html += plotly.offline.plot(self, output_type='div', include_plotlyjs="cdn")
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else:
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html += "<h1>No data was retrieved for the given parameters.</h1>"
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html += '</body></html>'
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with open("test.html", "w", encoding="utf-8") as f:
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f.write(html)
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return html
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from .irida_charts import IridaFigure
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from .pcr_charts import PCRFigure
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from .concentrations_chart import ConcentrationsChart
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from .turnaround_chart import TurnaroundChart
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