Add `.ui._pathops` module

Starts a module for grouping together all our `QPainterpath` related
generation and data format operations for creation of fast curve
graphics. To start, drops `FastAppendCurve.downsample()` and moves
it to a new `._pathops.xy_downsample()`.

piker/ui/_curve.py

@@ -34,10 +34,11 @@ from PyQt5.QtCore import (
 
 from .._profile import pg_profile_enabled, ms_slower_then
 from ._style import hcolor
-from ._compression import (
-    # ohlc_to_m4_line,
-    ds_m4,
-)
+# from ._compression import (
+#     # ohlc_to_m4_line,
+#     ds_m4,
+# )
+from ._pathops import xy_downsample
 from ..log import get_logger
 
 
@@ -174,32 +175,6 @@ class FastAppendCurve(pg.GraphicsObject):
             QLineF(lbar, 0, rbar, 0)
         ).length()
 
-    def downsample(
-        self,
-        x,
-        y,
-        px_width,
-        uppx,
-
-    ) -> tuple[np.ndarray, np.ndarray]:
-
-        # downsample whenever more then 1 pixels per datum can be shown.
-        # always refresh data bounds until we get diffing
-        # working properly, see above..
-        bins, x, y = ds_m4(
-            x,
-            y,
-            px_width=px_width,
-            uppx=uppx,
-            # log_scale=bool(uppx)
-        )
-        x = np.broadcast_to(x[:, None], y.shape)
-        # x = (x + np.array([-0.43, 0, 0, 0.43])).flatten()
-        x = (x + np.array([-0.5, 0, 0, 0.5])).flatten()
-        y = y.flatten()
-
-        return x, y
-
     def update_from_array(
         self,
 
@@ -396,7 +371,8 @@ class FastAppendCurve(pg.GraphicsObject):
                 self._in_ds = False
 
             elif should_ds and uppx and px_width > 1:
-                x_out, y_out = self.downsample(
+
+                x_out, y_out = xy_downsample(
                     x_out,
                     y_out,
                     px_width,
@@ -461,7 +437,7 @@ class FastAppendCurve(pg.GraphicsObject):
             )
 
             # if should_ds:
-            #     new_x, new_y = self.downsample(
+            #     new_x, new_y = xy_downsample(
             #         new_x,
             #         new_y,
             #         px_width,

piker/ui/_flows.py

@@ -789,37 +789,6 @@ class Flow(msgspec.Struct):  # , frozen=True):
         return graphics
 
 
-def xy_downsample(
-    x,
-    y,
-    px_width,
-    uppx,
-
-    x_spacer: float = 0.5,
-
-) -> tuple[np.ndarray, np.ndarray]:
-
-    # downsample whenever more then 1 pixels per datum can be shown.
-    # always refresh data bounds until we get diffing
-    # working properly, see above..
-    bins, x, y = ds_m4(
-        x,
-        y,
-        px_width=px_width,
-        uppx=uppx,
-        log_scale=bool(uppx)
-    )
-
-    # flatten output to 1d arrays suitable for path-graphics generation.
-    x = np.broadcast_to(x[:, None], y.shape)
-    x = (x + np.array(
-        [-x_spacer, 0, 0, x_spacer]
-    )).flatten()
-    y = y.flatten()
-
-    return x, y
-
-
 class Renderer(msgspec.Struct):
 
     flow: Flow

piker/ui/_pathops.py

@@ -0,0 +1,61 @@
+# piker: trading gear for hackers
+# Copyright (C) 2018-present  Tyler Goodlet (in stewardship of piker0)
+
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU Affero General Public License as published by
+# the Free Software Foundation, either version 3 of the License, or
+# (at your option) any later version.
+
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU Affero General Public License for more details.
+
+# You should have received a copy of the GNU Affero General Public License
+# along with this program.  If not, see <https://www.gnu.org/licenses/>.
+"""
+Super fast ``QPainterPath`` generation related operator routines.
+
+"""
+
+import numpy as np
+# from numba import njit, float64, int64  # , optional
+# import pyqtgraph as pg
+# from PyQt5 import QtCore, QtGui, QtWidgets
+# from PyQt5.QtCore import QLineF, QPointF
+
+from ._compression import (
+    # ohlc_flatten,
+    ds_m4,
+)
+
+
+def xy_downsample(
+    x,
+    y,
+    px_width,
+    uppx,
+
+    x_spacer: float = 0.5,
+
+) -> tuple[np.ndarray, np.ndarray]:
+
+    # downsample whenever more then 1 pixels per datum can be shown.
+    # always refresh data bounds until we get diffing
+    # working properly, see above..
+    bins, x, y = ds_m4(
+        x,
+        y,
+        px_width=px_width,
+        uppx=uppx,
+        # log_scale=bool(uppx)
+    )
+
+    # flatten output to 1d arrays suitable for path-graphics generation.
+    x = np.broadcast_to(x[:, None], y.shape)
+    x = (x + np.array(
+        [-x_spacer, 0, 0, x_spacer]
+    )).flatten()
+    y = y.flatten()
+
+    return x, y