Ejemplo n.º 1
0
    def update(self):
        make_similar(self.old, self.new)
        self.deleted = h.diff(self.old, self.new.id)
        self.modified = h.intersection(self.old, self.new,
                                       "id").sort_values("id")
        added = h.diff(self.new, self.old.id)
        added[self.form_complete] = 1
        added["common_complete"] = 1
        make_similar(added, self.redcap_df)
        added = h.diff(added, self.redcap_df)
        self.added = added

        if added is not None and not added.empty:
            self.merged = self.redcap_df.append(added, sort=False)
        else:
            self.merged = self.redcap_df
Ejemplo n.º 2
0
def test_diff_subtracting_conflicting_rows_but_using_id_rows(A, B2):
    """Since now matching on B[0], only the first column should be used for matching."""
    result = h.diff(A, B2[0])
    expected = pd.DataFrame(
        [
            (1, 1),
            (3, 9),
        ]
    )
    assert result.equals(expected)
Ejemplo n.º 3
0
def test_diff_subtracting_nonconflicting_rows(A, B):
    """The two rows that match perfectly should be removed from result"""
    result = h.diff(A, B)
    expected = pd.DataFrame(
        [
            (1, 1),
            (3, 9),
        ]
    )
    assert result.equals(expected)
Ejemplo n.º 4
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    def show_missing_subjects(self):
        form, added, deleted, modified = self.form, self.added, self.deleted, self.modified
        df = self.merged.copy()
        df["subject"] = df["patientid"].str.split("_", 1,
                                                  expand=True)[0].str.strip()
        missing = h.diff(studydata, df.subject)

        # missing = h.difference(studydata, df.subject).copy()
        missing = missing[missing.flagged.isnull()]
        missing = missing[missing.interview_date < "2019-05-01"]
        missing = missing[missing.study != "hcpa"]
        missing["reason"] = "Missing in Box"
        self.warn_missing(missing, self.form)
        display(missing)
        return missing
Ejemplo n.º 5
0
        def on_update(btn):
            df = ipysheet.to_dataframe(sheet)
            df = df.replace("nan", np.nan)

            # delta  of changes
            z = h.diff(df, not_in_redcap)

            updates = z[~z.delete].iloc[:, 1:]
            if not updates.empty:
                r = table.send_frame(updates)
                print("Updates: ", r.status_code, r.content)

            delete = z[z.delete].id.tolist()
            if delete:
                r = table.delete_records(delete)
                print("Delete Records: ", r.status_code, r.content)
Ejemplo n.º 6
0
# modified = h.conflict(current_redcap, ksads, intersect_on="id", sources=("redcap", "ksads.net"))
#
# print(ksads.shape, added.shape, deleted.shape, modified.shape)

# %%
import changes.accepted
df = ksads.set_index('id')
changes.accepted.execute(df)   # ACTION!
ksads = df.reset_index()

# %% [markdown]
# # Capture Changes

# %%
# print new shapes
added = h.diff(ksads, current_redcap.id)
deleted = h.diff(current_redcap, ksads.id)
modified = h.conflict(current_redcap, ksads, intersect_on="id", sources=("redcap", "ksads.net"))

print(ksads.shape, added.shape, deleted.shape, modified.shape)

# %%
# deleted is always empty, if not throw error
assert deleted.empty, "KSADS.net data has been deleted, take a look at `deleted` dataframe and figure out whether to delete those rows from redcap, Invalidate, mark a flag, or notify users etc."
deleted


file = open("changes/to_review.py", "w")
file.write("from changes.utils import block, modify\n\n\ndef execute(df):\n    pass\n")
# %%
def generate_blocking_code_for_added_rows(added):
Ejemplo n.º 7
0
    def show_not_in_redcap(self):
        form, added, deleted, modified = self.form, self.added, self.deleted, self.modified
        df = self.merged.copy()
        df["subject"] = df["patientid"].str.split("_", 1,
                                                  expand=True)[0].str.strip()
        not_in_redcap = h.diff(df, studyids.subject).iloc[:, :-1]
        h.asInt(not_in_redcap, "id", "common_complete", self.form_complete)
        not_in_redcap.insert(0, "delete", False)
        not_in_redcap.insert(1, "link", "view")

        sheet = ipysheet.sheet(ipysheet.from_dataframe(not_in_redcap))

        spaced = wg.Layout(margin="30px 0 20px 0")

        save_btn = wg.Button(description="Update", icon="save")
        reset_btn = wg.Button(description="Reset", icon="trash")
        btns = wg.HBox([save_btn, reset_btn], layout=spaced)

        def on_reset(btn):
            sheet.cells = ipysheet.from_dataframe(not_in_redcap).cells

        #     sheet = ipysheet.sheet(ipysheet.from_dataframe(not_in_redcap))

        reset_btn.on_click(on_reset)

        def on_update(btn):
            df = ipysheet.to_dataframe(sheet)
            df = df.replace("nan", np.nan)

            # delta  of changes
            z = h.diff(df, not_in_redcap)

            updates = z[~z.delete].iloc[:, 1:]
            if not updates.empty:
                r = table.send_frame(updates)
                print("Updates: ", r.status_code, r.content)

            delete = z[z.delete].id.tolist()
            if delete:
                r = table.delete_records(delete)
                print("Delete Records: ", r.status_code, r.content)

        save_btn.on_click(on_update)

        fancy_widget = wg.VBox([sheet, btns])

        def convert_to_links():
            values = [
                wg.HTML(
                    '<a target="_blank" href="https://redcap.wustl.edu/redcap/redcap_v8.11.0/DataEntry/record_home.php?pid=3355&arm=1&id=%s">view</a>'
                    % x) for x in sheet.cells[2].value
            ]
            ipysheet.column(1, values)

        convert_to_links()
        if not not_in_redcap.empty:
            display(
                HTML(
                    "<H3>Subject IDs not in Redcap</H3><SMALL>Please either change patientid to match an ID in redcap or delete the row.</SMALL>"
                ))
            display(fancy_widget)
Ejemplo n.º 8
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def test_diff_subtracting_conflicting_rows(A, B2):
    """Since no row in B matches perfectly, the result should be A unmodified"""
    result = h.diff(A, B2)
    expected = A
    assert result.equals(expected)
Ejemplo n.º 9
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def test_diff_from_same(A, B):
    """Subtracting a dataframe from itself should result in an empty df"""
    assert h.diff(A, A).empty
    assert h.diff(B, B).empty