Updated imports in visual tests and axis label in point plotter

Show cross-section figure in UI
Return PMM data from main calculation function
Revert relative import changes and rename visual test files
Fix PMM field types

examples/conc_col_pmm/README.md

@@ -15,12 +15,12 @@ The `conc_col_pmm` folder is meant to be a standalone design tool. To get set up
 ## Designing a column
 The `conc_col_pmm/tests/visual_tests` folder has examples for running various parts of the concrete column tool including
 
-* `visual_test_document_wrapper.py` for viewing a complete calculation report
-* `visual_test_pmm_plotter_plotly.py` for viewing a 3D PMM plot
+* `visual_test_calculation_report.py` for viewing a complete calculation report
+* `visual_test_pmm.py` for viewing a 3D PMM plot
 * `visual_test_point_plotter.py` for viewing 2D PM plots for specific load cases
 
 These example files can be run and viewed with `python -m conc_col_pmm.tests.visual_tests.<file name>`. For example:
-`python -m conc_col_pmm.tests.visual_tests.visual_test_document_wrapper`
+`python -m conc_col_pmm.tests.visual_tests.visual_test_calculation_report`
 
 
 # Program Features

examples/conc_col_pmm/calc_document/calculation.py

@@ -6,8 +6,7 @@
 from ..pmm_search.load_combo import LoadCombination, is_yes
 from .column_inputs import ColumnInputs
 from .full_calc_document import calculation as full_calc
-
-# TODO: this should return all info needed to plot visual tests, possibly take input params for defaults
+from .plotting.get_pmm_data import get_pmm_data
 
 
 # this function accepts inputs from the user and passes them to "full_calc_document"
@@ -154,4 +153,6 @@ def calculation(
         e_c,
     )
 
-    full_calc(column, load_combos)
+    axial_limits = full_calc(column, load_combos)
+
+    return get_pmm_data(column, 36, 12, load_combos, axial_limits)

examples/conc_col_pmm/calc_document/full_calc_document.py

@@ -29,3 +29,5 @@ def calculation(
     dcr_results = calc_dcrs(load_combos, mesh, col, axial_limits)
 
     results_summarizer(load_combos, dcr_results)
+
+    return axial_limits

examples/conc_col_pmm/calc_document/plotting/PMM.py

@@ -1,10 +1,13 @@
-from ...pmm_search.load_combo import LoadCombination
 import dataclasses
 
+from numpy import ndarray
+
+from ...pmm_search.load_combo import LoadCombination
+
 
 @dataclasses.dataclass
-class PMM():
-    X: list[float]
-    Y: list[float]
-    Z: list[float]
-    load_combos: list[LoadCombination]
+class PMM:
+    X: ndarray
+    Y: ndarray
+    Z: ndarray
+    load_combos: list[LoadCombination]

examples/conc_col_pmm/calc_document/plotting/get_pmm_data.py

@@ -3,15 +3,15 @@
 from ...col.axial_limits import AxialLimits
 from ...col.column import Column
 from ...pmm_search.load_combo import LoadCombination
-from .pmm_mesh import get_mesh
 from .PMM import PMM
+from .pmm_mesh import get_mesh
 
-'''
+"""
 This function takes inputs for a column and creates a
 dataclass instance containing all the information for the 
 PMM diagram for the given column. That information is used
 for plotting the PMM diagram. 
-'''
+"""
 
 
 def get_pmm_data(
@@ -30,4 +30,4 @@ def get_pmm_data(
     Y = np.array(y)
     Z = np.array(z)
 
-    return PMM(X=X, Y=Y, Z=Z, load_combos=load_combos)
+    return PMM(X=X, Y=Y, Z=Z, load_combos=load_combos)

examples/conc_col_pmm/calc_document/plotting/pmm_mesh.py

@@ -6,16 +6,18 @@
 from ...pmm_search.load_search.point_search_load import search
 
 
-def get_mesh(col: Column, intervals, load_spaces, axial_limits: AxialLimits):
+def get_mesh(
+    col: Column, intervals, load_spaces, axial_limits: AxialLimits
+) -> tuple[list[list[int]], list[list[int]], list[list[int]], list[list[float]]]:
     # "intervals" is the number of spaces in the angle of eccentricity,
     # "load_spaces" is the number of vertical spaces in the PMM diagram
     # Returns a mesh containing all the points of the PMM diagram, plus
     # a quarter of that mesh
 
     # vectors containing the points to plot
-    x = []
-    y = []
-    z = []
+    x: list[list[int]] = []
+    y: list[list[int]] = []
+    z: list[list[int]] = []
 
     # the bottom point must be added intervals+1 times because each level of
     # the mesh needs intervals+1 points in order to form a closed surface

examples/conc_col_pmm/calc_document/plotting/pmm_plotter_plotly.py

@@ -1,12 +1,14 @@
 import numpy as np
 import plotly.graph_objects as go
 
+from .PMM import PMM
+
 """
 This function plots the factored load capacity diagram for the column
 """
 
 
-def plot(pmm_data):
+def plot(pmm_data: PMM):
     X = pmm_data.X
     Y = pmm_data.Y
     Z = pmm_data.Z

examples/conc_col_pmm/calc_document/plotting/point_plotter.py

@@ -60,13 +60,17 @@ def plot(capacity_pts, point: LoadCombination | None, only_Mx):
     ax.set_axisbelow(True)
 
     load_span = phi_Pn[-1] - phi_Pn[0]
-    label_offsets = (max(phi_Mn) * 0.008, load_span * 0.02)
+
+    # define offset distances for axis labels depending on point
+    label_offset_x = max(phi_Mn) * 0.008
+    label_offsets_y = -load_span * 0.05, load_span * 0.02
     # label the intersections with the y-axis
     for i in (0, pt_count - 1):
         pos = (phi_Mn[i], phi_Pn[i])
         label = str(round(phi_Pn[i], 1))
         plt.plot(pos[0], pos[1], marker="+", ms=12, mew=1.2, c="black", zorder=3)
-        plt.text(pos[0] + label_offsets[0], pos[1] + label_offsets[1], label, zorder=3)
+        label_offset_y = label_offsets_y[0] if i == 0 else label_offsets_y[1]
+        plt.text(pos[0] + label_offset_x, pos[1] + label_offset_y, label, zorder=3)
 
     if point:
         Muxy = math.sqrt(point.mx**2 + point.my**2)  # the biaxial moment
@@ -78,7 +82,8 @@ def plot(capacity_pts, point: LoadCombination | None, only_Mx):
         label = moment_label + "\n" + axial_label
 
         plt.plot(pos[0], pos[1], marker="+", ms=12, mew=1.2, c="red", zorder=4)
-        plt.text(pos[0] + label_offsets[0], pos[1] + label_offsets[1], label, zorder=5)
+        label_offset_y = label_offsets_y[0] if i == 0 else label_offsets_y[1]
+        plt.text(pos[0] + label_offset_x, pos[1] + label_offset_y, label, zorder=5)
 
         fig = ax.get_figure()
 

examples/conc_col_pmm/col/col_canvas/draw_column_with_dimensions.py

@@ -9,6 +9,7 @@
 
 def draw(col: Column, caption_input: str, unit: str = '"') -> Canvas:
     canvas = draw_base(col)
+    canvas.display_type = "report-input"
     canvas.caption = caption_input
     scale_factor = 0.37817187 * math.log((col.w + col.h) / 2) + 0.03808133
 

examples/conc_col_pmm/tests/test_pmm_plotter_plotly.py

@@ -1,20 +1,17 @@
+from ..calc_document.calculation import calculation
 from ..calc_document.plotting import get_pmm_data, pmm_plotter_plotly
 from ..col import assign_max_min
-from ..pmm_search.load_combo import LoadCombination
 
 
 # This test checks for runtime errors
-def test_pmm_plotter_plotly(example_col, loads):
-    axial_limits = assign_max_min.calculate_axial_load_limits(example_col)
-
+def test_pmm_plotter_plotly(example_col):
     # for each load case: P, Mx, My, and whether the calc should be shown
-    load_data = [
-        [300, 100, 200, True],
-        [-100, 50, -60, False],
-        [1500, 300, -300, False],
+    loads = [
+        [300, 100, 200, "yes"],
+        [-100, 50, -60, "no"],
+        [1500, 300, -300, "no"],
     ]
-    loads = [LoadCombination(i, *load) for i, load in enumerate(load_data)]
 
-    pmm_data = get_pmm_data.get_pmm_data(example_col, 36, 12, loads, axial_limits)
+    pmm_data = calculation(default_loads=loads, col=example_col)
 
     _ = pmm_plotter_plotly.plot(pmm_data)

examples/conc_col_pmm/tests/visual_tests/visual_test_document_wrapper.py → examples/conc_col_pmm/tests/visual_tests/visual_test_calculation_report.py

@@ -1,29 +1,24 @@
-import os
-import sys
-
 # Now you can import from conc_col_pmm
 from ...calc_document.document_wrapper import run
 
 # "w", "h", "bar_size", "bar_cover", "bars_x", "bars_y", "fc", "fy", "cover_type", "transverse_type",
-col_data = [24, 18, "#6", 2, 5, 2, 8000, 60, "Edge", "Spiral"]
+# col_data = [18, 24, "#6", 2, 5, 2, 8000, 60, "Edge", "Tied"]
 
 # for each load case: P, Mx, My, and whether the calc should be shown
 # Note that these load cases currently do not override the defaults
-loads = [
-    [300, 100, 200, "yes"],
-    [-100, 50, -60, "no"],
-    [11500, 300, -300, "no"],
-    [0, 200, 0, "yes"],
-    [0, 0, 200, "yes"],
-]
+# loads = [
+#     [500, 200, 100, "yes"],
+#     [-100, 50, -60, "no"],
+#     [11500, 300, -300, "no"],
+# ]
 
 # calc_report_example1
 # col_data = [24, 18, "#6", 1.5, 5, 4, 8000, 60, "Edge", "Tied"]
-# loads = [[1400, -300, 100, True]]
+# loads = [[1400, -300, 100, "yes"]]
 
 # calc_report_example2
-# col_data = [24, 36, "#8", 2, 6, 8, 8000, 60, "Edge", "Tied"]
-# loads = [[3000, -200, 100, True]]
+col_data = [24, 36, "#8", 2, 6, 8, 8000, 60, "Edge", "Tied"]
+loads = [[3000, -200, 100, "yes"]]
 
 if __name__ == "__main__":
     run(True, col_data, loads)

examples/conc_col_pmm/tests/visual_tests/visual_test_pmm_plotter_plotly.py → examples/conc_col_pmm/tests/visual_tests/visual_test_pmm.py

@@ -1,10 +1,9 @@
 from efficalc import Input
 
-from ...calc_document.plotting import get_pmm_data, pmm_plotter_plotly
-from ...col import assign_max_min
+from ...calc_document.calculation import calculation
+from ...calc_document.plotting import pmm_plotter_plotly
 from ...col.column import Column
 from ...constants.rebar_data import BarSize
-from ...pmm_search.load_combo import LoadCombination
 from ...tests.conftest import getCalculatedColumnProps
 
 # TODO: make this use the main calc callsite and get the plotly data from there
@@ -33,17 +32,15 @@ def example_col():
 
 if __name__ == "__main__":
     col = example_col()
-    axial_limits = assign_max_min.calculate_axial_load_limits(col)
 
     # for each load case: P, Mx, My, and whether the calc should be shown
     load_data = [
-        [300, 100, 200, True],
-        [-100, 50, -60, False],
-        [1500, 300, -300, False],
+        [300, 100, 200, "yes"],
+        [-100, 50, -60, "no"],
+        [1500, 300, -300, "no"],
     ]
-    loads = [LoadCombination(i, *load) for i, load in enumerate(load_data)]
 
-    pmm_data = get_pmm_data.get_pmm_data(col, 36, 12, loads, axial_limits)
+    pmm_data = calculation(default_loads=load_data, col=col)
 
     fig = pmm_plotter_plotly.plot(pmm_data)