1
0
Fork 0
mirror of https://github.com/deepfakes/faceswap synced 2025-06-07 10:43:27 -04:00
faceswap/lib/gui/display_analysis.py
torzdf cd00859c40
model_refactor (#571) (#572)
* model_refactor (#571)

* original model to new structure

* IAE model to new structure

* OriginalHiRes to new structure

* Fix trainer for different resolutions

* Initial config implementation

* Configparse library added

* improved training data loader

* dfaker model working

* Add logging to training functions

* Non blocking input for cli training

* Add error handling to threads. Add non-mp queues to queue_handler

* Improved Model Building and NNMeta

* refactor lib/models

* training refactor. DFL H128 model Implementation

* Dfaker - use hashes

* Move timelapse. Remove perceptual loss arg

* Update INSTALL.md. Add logger formatting. Update Dfaker training

* DFL h128 partially ported

* Add mask to dfaker (#573)

* Remove old models. Add mask to dfaker

* dfl mask. Make masks selectable in config (#575)

* DFL H128 Mask. Mask type selectable in config.

* remove gan_v2_2

* Creating Input Size config for models

Creating Input Size config for models

Will be used downstream in converters.

Also name change of image_shape to input_shape to clarify ( for future models with potentially different output_shapes)

* Add mask loss options to config

* MTCNN options to config.ini. Remove GAN config. Update USAGE.md

* Add sliders for numerical values in GUI

* Add config plugins menu to gui. Validate config

* Only backup model if loss has dropped. Get training working again

* bugfixes

* Standardise loss printing

* GUI idle cpu fixes. Graph loss fix.

* mutli-gpu logging bugfix

* Merge branch 'staging' into train_refactor

* backup state file

* Crash protection: Only backup if both total losses have dropped

* Port OriginalHiRes_RC4 to train_refactor (OriginalHiRes)

* Load and save model structure with weights

* Slight code update

* Improve config loader. Add subpixel opt to all models. Config to state

* Show samples... wrong input

* Remove AE topology. Add input/output shapes to State

* Port original_villain (birb/VillainGuy) model to faceswap

* Add plugin info to GUI config pages

* Load input shape from state. IAE Config options.

* Fix transform_kwargs.
Coverage to ratio.
Bugfix mask detection

* Suppress keras userwarnings.
Automate zoom.
Coverage_ratio to model def.

* Consolidation of converters & refactor (#574)

* Consolidation of converters & refactor

Initial Upload of alpha

Items
- consolidate convert_mased & convert_adjust into one converter
-add average color adjust to convert_masked
-allow mask transition blur size to be a fixed integer of pixels and a fraction of the facial mask size
-allow erosion/dilation size to be a fixed integer of pixels and a fraction of the facial mask size
-eliminate redundant type conversions to avoid multiple round-off errors
-refactor loops for vectorization/speed
-reorganize for clarity & style changes

TODO
- bug/issues with warping the new face onto a transparent old image...use a cleanup mask for now
- issues with mask border giving black ring at zero erosion .. investigate
- remove GAN ??
- test enlargment factors of umeyama standard face .. match to coverage factor
- make enlargment factor a model parameter
- remove convert_adjusted and referencing code when finished

* Update Convert_Masked.py

default blur size of 2 to match original...
description of enlargement tests
breakout matrxi scaling into def

* Enlargment scale as a cli parameter

* Update cli.py

* dynamic interpolation algorithm

Compute x & y scale factors from the affine matrix on the fly by QR decomp.
Choose interpolation alogrithm for the affine warp based on an upsample or downsample for each image

* input size
input size from config

* fix issues with <1.0 erosion

* Update convert.py

* Update Convert_Adjust.py

more work on the way to merginf

* Clean up help note on sharpen

* cleanup seamless

* Delete Convert_Adjust.py

* Update umeyama.py

* Update training_data.py

* swapping

* segmentation stub

* changes to convert.str

* Update masked.py

* Backwards compatibility fix for models
Get converter running

* Convert:
Move masks to class.
bugfix blur_size
some linting

* mask fix

* convert fixes

- missing facehull_rect re-added
- coverage to %
- corrected coverage logic
- cleanup of gui option ordering

* Update cli.py

* default for blur

* Update masked.py

* added preliminary low_mem version of OriginalHighRes model plugin

* Code cleanup, minor fixes

* Update masked.py

* Update masked.py

* Add dfl mask to convert

* histogram fix & seamless location

* update

* revert

* bugfix: Load actual configuration in gui

* Standardize nn_blocks

* Update cli.py

* Minor code amends

* Fix Original HiRes model

* Add masks to preview output for mask trainers
refactor trainer.__base.py

* Masked trainers converter support

* convert bugfix

* Bugfix: Converter for masked (dfl/dfaker) trainers

* Additional Losses (#592)

* initial upload

* Delete blur.py

* default initializer = He instead of Glorot (#588)

* Allow kernel_initializer to be overridable

* Add ICNR Initializer option for upscale on all models.

* Hopefully fixes RSoDs with original-highres model plugin

* remove debug line

* Original-HighRes model plugin Red Screen of Death fix, take #2

* Move global options to _base. Rename Villain model

* clipnorm and res block biases

* scale the end of res block

* res block

* dfaker pre-activation res

* OHRES pre-activation

* villain pre-activation

* tabs/space in nn_blocks

* fix for histogram with mask all set to zero

* fix to prevent two networks with same name

* GUI: Wider tooltips. Improve TQDM capture

* Fix regex bug

* Convert padding=48 to ratio of image size

* Add size option to alignments tool extract

* Pass through training image size to convert from model

* Convert: Pull training coverage from model

* convert: coverage, blur and erode to percent

* simplify matrix scaling

* ordering of sliders in train

* Add matrix scaling to utils. Use interpolation in lib.aligner transform

* masked.py Import get_matrix_scaling from utils

* fix circular import

* Update masked.py

* quick fix for matrix scaling

* testing thus for now

* tqdm regex capture bugfix

* Minor ammends

* blur size cleanup

* Remove coverage option from convert (Now cascades from model)

* Implement convert for all model types

* Add mask option and coverage option to all existing models

* bugfix for model loading on convert

* debug print removal

* Bugfix for masks in dfl_h128 and iae

* Update preview display. Add preview scaling to cli

* mask notes

* Delete training_data_v2.py

errant file

* training data variables

* Fix timelapse function

* Add new config items to state file for legacy purposes

* Slight GUI tweak

* Raise exception if problem with loaded model

* Add Tensorboard support (Logs stored in model directory)

* ICNR fix

* loss bugfix

* convert bugfix

* Move ini files to config folder. Make TensorBoard optional

* Fix training data for unbalanced inputs/outputs

* Fix config "none" test

* Keep helptext in .ini files when saving config from GUI

* Remove frame_dims from alignments

* Add no-flip and warp-to-landmarks cli options

* Revert OHR to RC4_fix version

* Fix lowmem mode on OHR model

* padding to variable

* Save models in parallel threads

* Speed-up of res_block stability

* Automated Reflection Padding

* Reflect Padding as a training option

Includes auto-calculation of proper padding shapes, input_shapes, output_shapes

Flag included in config now

* rest of reflect padding

* Move TB logging to cli. Session info to state file

* Add session iterations to state file

* Add recent files to menu. GUI code tidy up

* [GUI] Fix recent file list update issue

* Add correct loss names to TensorBoard logs

* Update live graph to use TensorBoard and remove animation

* Fix analysis tab. GUI optimizations

* Analysis Graph popup to Tensorboard Logs

* [GUI] Bug fix for graphing for models with hypens in name

* [GUI] Correctly split loss to tabs during training

* [GUI] Add loss type selection to analysis graph

* Fix store command name in recent files. Switch to correct tab on open

* [GUI] Disable training graph when 'no-logs' is selected

* Fix graphing race condition

* rename original_hires model to unbalanced
2019-02-09 18:35:12 +00:00

638 lines
24 KiB
Python

#!/usr/bin python3
""" Analysis tab of Display Frame of the Faceswap GUI """
import csv
import logging
import os
import tkinter as tk
from tkinter import ttk
from .display_graph import SessionGraph
from .display_page import DisplayPage
from .stats import Calculations, Session
from .tooltip import Tooltip
from .utils import FileHandler, get_config, get_images
logger = logging.getLogger(__name__) # pylint: disable=invalid-name
class Analysis(DisplayPage): # pylint: disable=too-many-ancestors
""" Session analysis tab """
def __init__(self, parent, tabname, helptext):
logger.debug("Initializing: %s: (parent, %s, tabname: '%s', helptext: '%s')",
self.__class__.__name__, parent, tabname, helptext)
super().__init__(parent, tabname, helptext)
self.summary = None
self.session = None
self.add_options()
self.add_main_frame()
logger.debug("Initialized: %s", self.__class__.__name__)
def set_vars(self):
""" Analysis specific vars """
selected_id = tk.StringVar()
return {"selected_id": selected_id}
def add_main_frame(self):
""" Add the main frame to the subnotebook
to hold stats and session data """
logger.debug("Adding main frame")
mainframe = self.subnotebook_add_page("stats")
self.stats = StatsData(mainframe,
self.vars["selected_id"],
self.helptext["stats"])
logger.debug("Added main frame")
def add_options(self):
""" Add the options bar """
logger.debug("Adding options")
self.reset_session_info()
options = Options(self)
options.add_options()
logger.debug("Added options")
def reset_session_info(self):
""" Reset the session info status to default """
logger.debug("Resetting session info")
self.set_info("No session data loaded")
def load_session(self):
""" Load previously saved sessions """
logger.debug("Loading session")
self.clear_session()
fullpath = FileHandler("filename", "state").retfile
if not fullpath:
return
logger.debug("state_file: '%s'", fullpath)
model_dir, state_file = os.path.split(fullpath)
logger.debug("model_dir: '%s'", model_dir)
model_name = self.get_model_name(model_dir, state_file)
if not model_name:
return
self.session = Session(model_dir=model_dir, model_name=model_name)
self.session.initialize_session(is_training=False)
msg = os.path.split(state_file)[0]
if len(msg) > 70:
msg = "...{}".format(msg[-70:])
self.set_session_summary(msg)
@staticmethod
def get_model_name(model_dir, state_file):
""" Get the state file from the model directory """
logger.debug("Getting model name")
model_name = state_file.replace("_state.json", "")
logger.debug("model_name: %s", model_name)
logs_dir = os.path.join(model_dir, "{}_logs".format(model_name))
if not os.path.isdir(logs_dir):
logger.warning("No logs folder found in folder: '%s'", logs_dir)
return None
return model_name
def reset_session(self):
""" Reset currently training sessions """
logger.debug("Reset current training session")
self.clear_session()
session = get_config().session
if not session.initialized:
logger.debug("Training not running")
print("Training not running")
return
msg = "Currently running training session"
self.session = session
self.set_session_summary(msg)
def set_session_summary(self, message):
""" Set the summary data and info message """
logger.debug("Setting session summary. (message: '%s')", message)
self.summary = self.session.full_summary
self.set_info("Session: {}".format(message))
self.stats.session = self.session
self.stats.tree_insert_data(self.summary)
def clear_session(self):
""" Clear sessions stats """
logger.debug("Clearing session")
self.summary = None
self.stats.session = None
self.stats.tree_clear()
self.reset_session_info()
def save_session(self):
""" Save sessions stats to csv """
logger.debug("Saving session")
if not self.summary:
logger.debug("No summary data loaded. Nothing to save")
print("No summary data loaded. Nothing to save")
return
savefile = FileHandler("save", "csv").retfile
if not savefile:
logger.debug("No save file. Returning")
return
write_dicts = [val for val in self.summary.values()]
fieldnames = sorted(key for key in write_dicts[0].keys())
logger.debug("Saving to: '%s'", savefile)
with savefile as outfile:
csvout = csv.DictWriter(outfile, fieldnames)
csvout.writeheader()
for row in write_dicts:
csvout.writerow(row)
class Options():
""" Options bar of Analysis tab """
def __init__(self, parent):
logger.debug("Initializing: %s", self.__class__.__name__)
self.optsframe = parent.optsframe
self.parent = parent
logger.debug("Initialized: %s", self.__class__.__name__)
def add_options(self):
""" Add the display tab options """
self.add_buttons()
def add_buttons(self):
""" Add the option buttons """
for btntype in ("reset", "clear", "save", "load"):
logger.debug("Adding button: '%s'", btntype)
cmd = getattr(self.parent, "{}_session".format(btntype))
btn = ttk.Button(self.optsframe,
image=get_images().icons[btntype],
command=cmd)
btn.pack(padx=2, side=tk.RIGHT)
hlp = self.set_help(btntype)
Tooltip(btn, text=hlp, wraplength=200)
@staticmethod
def set_help(btntype):
""" Set the helptext for option buttons """
logger.debug("Setting help")
hlp = ""
if btntype == "reset":
hlp = "Load/Refresh stats for the currently training session"
elif btntype == "clear":
hlp = "Clear currently displayed session stats"
elif btntype == "save":
hlp = "Save session stats to csv"
elif btntype == "load":
hlp = "Load saved session stats"
return hlp
class StatsData(ttk.Frame): # pylint: disable=too-many-ancestors
""" Stats frame of analysis tab """
def __init__(self, parent, selected_id, helptext):
logger.debug("Initializing: %s: (parent, %s, selected_id: %s, helptext: '%s')",
self.__class__.__name__, parent, selected_id, helptext)
super().__init__(parent)
self.pack(side=tk.TOP, padx=5, pady=5, expand=True, fill=tk.X, anchor=tk.N)
self.session = None # set when loading or clearing from parent
self.selected_id = selected_id
self.popup_positions = list()
self.add_label()
self.tree = ttk.Treeview(self, height=1, selectmode=tk.BROWSE)
self.scrollbar = ttk.Scrollbar(self,
orient="vertical",
command=self.tree.yview)
self.columns = self.tree_configure(helptext)
logger.debug("Initialized: %s", self.__class__.__name__)
def add_label(self):
""" Add Treeview Title """
logger.debug("Adding Treeview title")
lbl = ttk.Label(self, text="Session Stats", anchor=tk.CENTER)
lbl.pack(side=tk.TOP, expand=True, fill=tk.X, padx=5, pady=5)
def tree_configure(self, helptext):
""" Build a treeview widget to hold the sessions stats """
logger.debug("Configuring Treeview")
self.tree.configure(yscrollcommand=self.scrollbar.set)
self.tree.tag_configure("total",
background="black",
foreground="white")
self.tree.pack(side=tk.LEFT, expand=True, fill=tk.X)
self.scrollbar.pack(side=tk.RIGHT, fill=tk.Y)
self.tree.bind("<ButtonRelease-1>", self.select_item)
Tooltip(self.tree, text=helptext, wraplength=200)
return self.tree_columns()
def tree_columns(self):
""" Add the columns to the totals treeview """
logger.debug("Adding Treeview columns")
columns = (("session", 40, "#"),
("start", 130, None),
("end", 130, None),
("elapsed", 90, None),
("batch", 50, None),
("iterations", 90, None),
("rate", 60, "EGs/sec"))
self.tree["columns"] = [column[0] for column in columns]
for column in columns:
text = column[2] if column[2] else column[0].title()
logger.debug("Adding heading: '%s'", text)
self.tree.heading(column[0], text=text)
self.tree.column(column[0],
width=column[1],
anchor=tk.E,
minwidth=40)
self.tree.column("#0", width=40)
self.tree.heading("#0", text="Graphs")
return [column[0] for column in columns]
def tree_insert_data(self, sessions_summary):
""" Insert the data into the totals treeview """
logger.debug("Inserting treeview data")
self.tree.configure(height=len(sessions_summary))
for item in sessions_summary:
values = [item[column] for column in self.columns]
kwargs = {"values": values, "image": get_images().icons["graph"]}
if values[0] == "Total":
kwargs["tags"] = "total"
self.tree.insert("", "end", **kwargs)
def tree_clear(self):
""" Clear the totals tree """
logger.debug("Clearing treeview data")
self.tree.delete(* self.tree.get_children())
self.tree.configure(height=1)
def select_item(self, event):
""" Update the session summary info with
the selected item or launch graph """
region = self.tree.identify("region", event.x, event.y)
selection = self.tree.focus()
values = self.tree.item(selection, "values")
if values:
logger.debug("Selected values: %s", values)
self.selected_id.set(values[0])
if region == "tree":
self.data_popup()
def data_popup(self):
""" Pop up a window and control it's position """
logger.debug("Popping up data window")
scaling_factor = get_config().scaling_factor
toplevel = SessionPopUp(self.session.modeldir,
self.session.modelname,
self.selected_id.get())
toplevel.title(self.data_popup_title())
position = self.data_popup_get_position()
height = int(720 * scaling_factor)
width = int(400 * scaling_factor)
toplevel.geometry("{}x{}+{}+{}".format(str(height),
str(width),
str(position[0]),
str(position[1])))
toplevel.update()
def data_popup_title(self):
""" Set the data popup title """
logger.debug("Setting poup title")
selected_id = self.selected_id.get()
title = "All Sessions"
if selected_id != "Total":
title = "{} Model: Session #{}".format(self.session.modelname.title(), selected_id)
logger.debug("Title: '%s'", title)
return "{} - {}".format(title, self.session.modeldir)
def data_popup_get_position(self):
""" Get the position of the next window """
logger.debug("getting poup position")
init_pos = [120, 120]
pos = init_pos
while True:
if pos not in self.popup_positions:
self.popup_positions.append(pos)
break
pos = [item + 200 for item in pos]
init_pos, pos = self.data_popup_check_boundaries(init_pos, pos)
logger.debug("Position: %s", pos)
return pos
def data_popup_check_boundaries(self, initial_position, position):
""" Check that the popup remains within the screen boundaries """
logger.debug("Checking poup boundaries: (initial_position: %s, position: %s)",
initial_position, position)
boundary_x = self.winfo_screenwidth() - 120
boundary_y = self.winfo_screenheight() - 120
if position[0] >= boundary_x or position[1] >= boundary_y:
initial_position = [initial_position[0] + 50, initial_position[1]]
position = initial_position
logger.debug("Returning poup boundaries: (initial_position: %s, position: %s)",
initial_position, position)
return initial_position, position
class SessionPopUp(tk.Toplevel):
""" Pop up for detailed graph/stats for selected session """
def __init__(self, model_dir, model_name, session_id):
logger.debug("Initializing: %s: (model_dir: %s, model_name: %s, session_id: %s)",
self.__class__.__name__, model_dir, model_name, session_id)
super().__init__()
self.session_id = session_id
self.session = Session(model_dir=model_dir, model_name=model_name)
self.initialize_session()
self.graph = None
self.display_data = None
self.vars = dict()
self.graph_initialised = False
self.build()
logger.debug("Initialized: %s", self.__class__.__name__)
@property
def is_totals(self):
""" Return True if these are totals else False """
return bool(self.session_id == "Total")
def initialize_session(self):
""" Initialize the session """
logger.debug("Initializing session")
kwargs = dict(is_training=False)
if not self.is_totals:
kwargs["session_id"] = int(self.session_id)
logger.debug("Session kwargs: %s", kwargs)
self.session.initialize_session(**kwargs)
def build(self):
""" Build the popup window """
logger.debug("Building popup")
optsframe, graphframe = self.layout_frames()
self.opts_build(optsframe)
self.compile_display_data()
self.graph_build(graphframe)
logger.debug("Built popup")
def layout_frames(self):
""" Top level container frames """
logger.debug("Layout frames")
leftframe = ttk.Frame(self)
leftframe.pack(side=tk.LEFT, expand=False, fill=tk.BOTH, pady=5)
sep = ttk.Frame(self, width=2, relief=tk.RIDGE)
sep.pack(fill=tk.Y, side=tk.LEFT)
rightframe = ttk.Frame(self)
rightframe.pack(side=tk.RIGHT, fill=tk.BOTH, pady=5, expand=True)
logger.debug("Laid out frames")
return leftframe, rightframe
def opts_build(self, frame):
""" Build Options into the options frame """
logger.debug("Building Options")
self.opts_combobox(frame)
self.opts_checkbuttons(frame)
self.opts_loss_keys(frame)
self.opts_entry(frame)
self.opts_buttons(frame)
sep = ttk.Frame(frame, height=2, relief=tk.RIDGE)
sep.pack(fill=tk.X, pady=(5, 0), side=tk.BOTTOM)
logger.debug("Built Options")
def opts_combobox(self, frame):
""" Add the options combo boxes """
logger.debug("Building Combo boxes")
choices = {"Display": ("Loss", "Rate"),
"Scale": ("Linear", "Log")}
for item in ["Display", "Scale"]:
var = tk.StringVar()
cmd = self.optbtn_reset if item == "Display" else self.graph_scale
var.trace("w", cmd)
cmbframe = ttk.Frame(frame)
cmbframe.pack(fill=tk.X, pady=5, padx=5, side=tk.TOP)
lblcmb = ttk.Label(cmbframe,
text="{}:".format(item),
width=7,
anchor=tk.W)
lblcmb.pack(padx=(0, 2), side=tk.LEFT)
cmb = ttk.Combobox(cmbframe, textvariable=var, width=10)
cmb["values"] = choices[item]
cmb.current(0)
cmb.pack(fill=tk.X, side=tk.RIGHT)
self.vars[item.lower().strip()] = var
hlp = self.set_help(item)
Tooltip(cmbframe, text=hlp, wraplength=200)
logger.debug("Built Combo boxes")
def opts_checkbuttons(self, frame):
""" Add the options check buttons """
logger.debug("Building Check Buttons")
for item in ("raw", "trend", "avg", "outliers"):
if item == "avg":
text = "Show Rolling Average"
elif item == "outliers":
text = "Flatten Outliers"
else:
text = "Show {}".format(item.title())
var = tk.BooleanVar()
if item == "raw":
var.set(True)
var.trace("w", self.optbtn_reset)
self.vars[item] = var
ctl = ttk.Checkbutton(frame, variable=var, text=text)
ctl.pack(side=tk.TOP, padx=5, pady=5, anchor=tk.W)
hlp = self.set_help(item)
Tooltip(ctl, text=hlp, wraplength=200)
logger.debug("Built Check Buttons")
def opts_loss_keys(self, frame):
""" Add loss key selections """
logger.debug("Building Loss Key Check Buttons")
loss_keys = self.session.loss_keys
lk_vars = dict()
for loss_key in sorted(loss_keys):
text = loss_key.replace("_", " ").title()
helptext = "Display {}".format(text)
var = tk.BooleanVar()
var.set(True)
var.trace("w", self.optbtn_reset)
lk_vars[loss_key] = var
if len(loss_keys) == 1:
# Don't display if there's only one item
break
ctl = ttk.Checkbutton(frame, variable=var, text=text)
ctl.pack(side=tk.TOP, padx=5, pady=5, anchor=tk.W)
Tooltip(ctl, text=helptext, wraplength=200)
self.vars["loss_keys"] = lk_vars
logger.debug("Built Loss Key Check Buttons")
def opts_entry(self, frame):
""" Add the options entry boxes """
logger.debug("Building Entry Boxes")
for item in ("avgiterations", ):
if item == "avgiterations":
text = "Iterations to Average:"
default = "10"
entframe = ttk.Frame(frame)
entframe.pack(fill=tk.X, pady=5, padx=5, side=tk.TOP)
lbl = ttk.Label(entframe, text=text, anchor=tk.W)
lbl.pack(padx=(0, 2), side=tk.LEFT)
ctl = ttk.Entry(entframe, width=4, justify=tk.RIGHT)
ctl.pack(side=tk.RIGHT, anchor=tk.W)
ctl.insert(0, default)
hlp = self.set_help(item)
Tooltip(entframe, text=hlp, wraplength=200)
self.vars[item] = ctl
logger.debug("Built Entry Boxes")
def opts_buttons(self, frame):
""" Add the option buttons """
logger.debug("Building Buttons")
btnframe = ttk.Frame(frame)
btnframe.pack(fill=tk.X, pady=5, padx=5, side=tk.BOTTOM)
for btntype in ("reset", "save"):
cmd = getattr(self, "optbtn_{}".format(btntype))
btn = ttk.Button(btnframe,
image=get_images().icons[btntype],
command=cmd)
btn.pack(padx=2, side=tk.RIGHT)
hlp = self.set_help(btntype)
Tooltip(btn, text=hlp, wraplength=200)
logger.debug("Built Buttons")
def optbtn_save(self):
""" Action for save button press """
logger.debug("Saving File")
savefile = FileHandler("save", "csv").retfile
if not savefile:
logger.debug("Save Cancelled")
return
logger.debug("Saving to: %s", savefile)
save_data = self.display_data.stats
fieldnames = sorted(key for key in save_data.keys())
with savefile as outfile:
csvout = csv.writer(outfile, delimiter=",")
csvout.writerow(fieldnames)
csvout.writerows(zip(*[save_data[key] for key in fieldnames]))
def optbtn_reset(self, *args): # pylint: disable=unused-argument
""" Action for reset button press and checkbox changes"""
logger.debug("Refreshing Graph")
if not self.graph_initialised:
return
valid = self.compile_display_data()
if not valid:
logger.debug("Invalid data")
return
self.graph.refresh(self.display_data,
self.vars["display"].get(),
self.vars["scale"].get())
logger.debug("Refreshed Graph")
def graph_scale(self, *args): # pylint: disable=unused-argument
""" Action for changing graph scale """
if not self.graph_initialised:
return
self.graph.set_yscale_type(self.vars["scale"].get())
@staticmethod
def set_help(control):
""" Set the helptext for option buttons """
hlp = ""
control = control.lower()
if control == "reset":
hlp = "Refresh graph"
elif control == "save":
hlp = "Save display data to csv"
elif control == "avgiterations":
hlp = "Number of data points to sample for rolling average"
elif control == "outliers":
hlp = "Flatten data points that fall more than 1 standard " \
"deviation from the mean to the mean value."
elif control == "avg":
hlp = "Display rolling average of the data"
elif control == "raw":
hlp = "Display raw data"
elif control == "trend":
hlp = "Display polynormal data trend"
elif control == "display":
hlp = "Set the data to display"
elif control == "scale":
hlp = "Change y-axis scale"
return hlp
def compile_display_data(self):
""" Compile the data to be displayed """
logger.debug("Compiling Display Data")
loss_keys = [key for key, val in self.vars["loss_keys"].items()
if val.get()]
logger.debug("Selected loss_keys: %s", loss_keys)
selections = self.selections_to_list()
if not self.check_valid_selection(loss_keys, selections):
return False
self.display_data = Calculations(session=self.session,
display=self.vars["display"].get(),
loss_keys=loss_keys,
selections=selections,
avg_samples=self.vars["avgiterations"].get(),
flatten_outliers=self.vars["outliers"].get(),
is_totals=self.is_totals)
logger.debug("Compiled Display Data")
return True
def check_valid_selection(self, loss_keys, selections):
""" Check that there will be data to display """
display = self.vars["display"].get().lower()
logger.debug("Validating selection. (loss_keys: %s, selections: %s, display: %s)",
loss_keys, selections, display)
if not selections or (display == "loss" and not loss_keys):
msg = "No data to display. Not refreshing"
logger.debug(msg)
print(msg)
return False
return True
def selections_to_list(self):
""" Compile checkbox selections to list """
logger.debug("Compiling selections to list")
selections = list()
for key, val in self.vars.items():
if (isinstance(val, tk.BooleanVar)
and key != "outliers"
and val.get()):
selections.append(key)
logger.debug("Compiling selections to list: %s", selections)
return selections
def graph_build(self, frame):
""" Build the graph in the top right paned window """
logger.debug("Building Graph")
self.graph = SessionGraph(frame,
self.display_data,
self.vars["display"].get(),
self.vars["scale"].get())
self.graph.pack(expand=True, fill=tk.BOTH)
self.graph.build()
self.graph_initialised = True
logger.debug("Built Graph")