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Removed useless recomputing of yticks #890

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Aug 8, 2024
Merged

Removed useless recomputing of yticks #890

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33 changes: 13 additions & 20 deletions bioptim/gui/plot.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@
import numpy as np
from casadi import DM
from matplotlib import pyplot as plt, lines
from matplotlib.ticker import StrMethodFormatter
from matplotlib.ticker import FuncFormatter

from .serializable_class import OcpSerializable
from ..dynamics.ode_solver import OdeSolver
Expand Down Expand Up @@ -180,9 +180,9 @@ class PlotOcp:
-------
_update_time_vector(self)
Setup the time and time integrated vector, which is the x-axes of the graphs
__create_plots(self)
_create_plots(self)
Setup the plots
__add_new_axis(self, variable: str, nb: int, n_rows: int, n_cols: int)
_add_new_axis(self, variable: str, nb: int, n_rows: int, n_cols: int)
Add a new axis to the axes pool
_organize_windows(self, n_windows: int)
Automatically organize the figure across the screen.
Expand All @@ -192,11 +192,11 @@ class PlotOcp:
Force the show of the graphs. This is a blocking function
update_data(self, v: dict)
Update ydata from the variable a solution structure
__update_xdata(self)
_update_xdata(self)
Update of the time axes in plots
__update_axes(self)
_update_axes(self)
Update the plotted data from ydata
__compute_ylim(min_val: np.ndarray | DM, max_val: np.ndarray | DM, factor: float) -> tuple:
_compute_ylim(min_val: np.ndarray | DM, max_val: np.ndarray | DM, factor: float) -> tuple:
Dynamically find the ylim
_generate_windows_size(nb: int) -> tuple[int, int]
Defines the number of column and rows of subplots from the number of variables to plot.
Expand Down Expand Up @@ -492,7 +492,7 @@ def legend_without_duplicate_labels(ax):
if y_max.__array__()[0] > y_max_all[y_range_var_idx][mapping_to_first_index.index(ctr)]:
y_max_all[y_range_var_idx][mapping_to_first_index.index(ctr)] = y_max

y_range, _ = self.__compute_ylim(
y_range = self._compute_ylim(
y_min_all[y_range_var_idx][mapping_to_first_index.index(ctr)],
y_max_all[y_range_var_idx][mapping_to_first_index.index(ctr)],
1.25,
Expand Down Expand Up @@ -651,7 +651,8 @@ def _add_new_axis(self, variable: str, nb: int, n_rows: int, n_cols: int):

self.all_figures[-1].tight_layout()
for ax in axes:
ax.yaxis.set_major_formatter(StrMethodFormatter("{x:,.1f}")) # 1 decimal places
ax.yaxis.set_major_formatter(FuncFormatter(lambda value, tick_value: f"{value:.2f}"))

return axes

def _organize_windows(self, n_windows: int):
Expand Down Expand Up @@ -996,15 +997,8 @@ def _update_ydata(self, ydata):
if isinstance(p, lines.Line2D):
y_min = min(y_min, np.nanmin(p.get_ydata()))
y_max = max(y_max, np.nanmax(p.get_ydata()))
y_range, data_range = self.__compute_ylim(y_min, y_max, 1.25)
ax.set_ylim(y_range)
ax.set_yticks(
np.arange(
y_range[0],
y_range[1],
step=data_range / 4,
)
)
ax.set_ylim(self._compute_ylim(y_min, y_max, 1.25))

for p in self.plots_vertical_lines:
p.set_ydata((0, 1))

Expand All @@ -1013,7 +1007,7 @@ def _update_ydata(self, ydata):
# TODO: set_tight_layout function will be deprecated. Use set_layout_engine instead.

@staticmethod
def __compute_ylim(min_val: np.ndarray | DM, max_val: np.ndarray | DM, factor: float) -> tuple:
def _compute_ylim(min_val: np.ndarray | DM, max_val: np.ndarray | DM, factor: float) -> tuple:
"""
Dynamically find the ylim

Expand All @@ -1040,8 +1034,7 @@ def __compute_ylim(min_val: np.ndarray | DM, max_val: np.ndarray | DM, factor: f
if np.abs(data_range) < 0.8:
data_range = 0.8
y_range = (factor * data_range) / 2
y_range = data_mean - y_range, data_mean + y_range
return y_range, data_range
return data_mean - y_range, data_mean + y_range

@staticmethod
def _generate_windows_size(nb: int) -> tuple:
Expand Down
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