def test_build_dandelion_graph(word_doc_landscape, ipdc_data, master):
# m = Master(*d["data"], **d["op_args"]) # currently necessary for cdg and top35 data
# dl_data = DandelionData(m, **d["op_args"])
dl_data = DandelionData(master, **ipdc_data["op_args"])
d_lion = make_a_dandelion_auto(dl_data, **ipdc_data["op_args"])
put_matplotlib_fig_into_word(word_doc_landscape, d_lion, size=7)
word_doc_landscape.save(ipdc_data["docx_save_path"].format("ipdc_d_graph"))
def test_matplotlib_chart_into_word(word_doc, master):
costs = CostData(master, group=[F9], baseline=["standard"])
costs.get_cost_profile()
graph = cost_profile_graph(costs, master, chart=False)
change_word_doc_landscape(word_doc)
put_matplotlib_fig_into_word(word_doc, graph)
word_doc.save("resources/summary_temp_altered.docx")
def test_radar_chart(sp_data, master, word_doc):
chart = radar_chart(sp_data, master, chart=False)
put_matplotlib_fig_into_word(word_doc, chart, size=5)
word_doc.save("resources/test_radar.docx")
def test_build_dandelion_graph_manual(build_dandelion, word_doc_landscape):
dlion = make_a_dandelion_manual(build_dandelion)
put_matplotlib_fig_into_word(word_doc_landscape, dlion, size=7.5)
word_doc_landscape.save("resources/dlion_mpl.docx")