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Merged
msrosenberg merged 4 commits into from
Jun 27, 2023
Merged

Figure refactor #26

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a3d1f7c
Simplification of graphics code
msrosenberg Jun 23, 2023
b1d27fb
Update test_metawin.py
msrosenberg Jun 23, 2023
d58c7f3
fixing tests
msrosenberg Jun 23, 2023
b176d19
cleaning
msrosenberg Jun 23, 2023
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30 changes: 13 additions & 17 deletions src/MetaWinAnalysis.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1798,62 +1798,58 @@ def do_meta_analysis(data, options, decimal_places: int = 4, alpha: float = 0.05
output, all_citations = options.report_choices()
output_blocks.extend(output)
if options.structure == SIMPLE_MA:
(output, figure, chart_data, analysis_values,
(output, chart_data, analysis_values,
citations) = MetaWinAnalysisFunctions.simple_meta_analysis(data, options, decimal_places, alpha, norm_ci,
sender=sender)
elif options.structure == GROUPED_MA:
(output, figure, chart_data, analysis_values,
(output, chart_data, analysis_values,
citations) = MetaWinAnalysisFunctions.grouped_meta_analysis(data, options, decimal_places, alpha, norm_ci,
sender=sender)
elif options.structure == CUMULATIVE_MA:
output, figure, chart_data = MetaWinAnalysisFunctions.cumulative_meta_analysis(data, options, decimal_places,
alpha, norm_ci, sender=sender)
output, chart_data = MetaWinAnalysisFunctions.cumulative_meta_analysis(data, options, decimal_places, alpha,
norm_ci, sender=sender)
analysis_values = None
citations = []
elif options.structure == REGRESSION_MA:
(output, figure, chart_data, analysis_values,
(output, chart_data, analysis_values,
citations) = MetaWinAnalysisFunctions.regression_meta_analysis(data, options, decimal_places, alpha, norm_ci,
sender=sender)
elif options.structure == COMPLEX_MA:
output, analysis_values, citations = MetaWinAnalysisFunctions.complex_meta_analysis(data, options,
decimal_places, alpha,
norm_ci, sender=sender)
figure = None
chart_data = None
elif options.structure == NESTED_MA:
(output, figure, chart_data, analysis_values,
(output, chart_data, analysis_values,
citations) = MetaWinAnalysisFunctions.nested_meta_analysis(data, options, decimal_places, alpha, norm_ci,
sender=sender)
elif options.structure == TRIM_FILL:
(output, figure, chart_data, analysis_values,
(output, chart_data, analysis_values,
citations) = MetaWinAnalysisFunctions.trim_and_fill_analysis(data, options, decimal_places, alpha, norm_ci)
elif options.structure == JACKKNIFE:
(output, figure, chart_data,
(output, chart_data,
citations) = MetaWinAnalysisFunctions.jackknife_meta_analysis(data, options, decimal_places, alpha, norm_ci,
sender=sender)
analysis_values = None
elif options.structure == PHYLOGENETIC_MA:
output, citations = MetaWinAnalysisFunctions.phylogenetic_meta_analysis(data, options, tree, decimal_places,
alpha, norm_ci, sender=sender)
analysis_values = None
figure = None
chart_data = None
elif options.structure == RANKCOR:
output, citations = MetaWinAnalysisFunctions.rank_correlation_analysis(data, options, decimal_places,
sender=sender)
figure = None
chart_data = None
analysis_values = None
else:
output = []
analysis_values = None
figure = None
chart_data = None
citations = []
all_citations.extend(citations)
output_blocks.extend(output)
output_blocks.extend(create_reference_list(all_citations))
return output_blocks, figure, chart_data, analysis_values
return output_blocks, chart_data, analysis_values


def meta_analysis(sender, data, last_effect, last_var, decimal_places: int = 4, alpha: float = 0.05,
Expand Down Expand Up @@ -1909,9 +1905,9 @@ def meta_analysis(sender, data, last_effect, last_var, decimal_places: int = 4,
meta_analysis_options.structure = None

if meta_analysis_options.structure is not None:
output, figure, chart_data, _ = do_meta_analysis(data, meta_analysis_options, decimal_places, alpha, tree,
norm_ci, sender=sender)
output, chart_data, _ = do_meta_analysis(data, meta_analysis_options, decimal_places, alpha, tree, norm_ci,
sender=sender)
sender.last_effect = meta_analysis_options.effect_data
sender.last_var = meta_analysis_options.effect_vars
return output, figure, chart_data
return None, None, None
return output, chart_data
return None, None
54 changes: 22 additions & 32 deletions src/MetaWinAnalysisFunctions.py
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Original file line number Diff line number Diff line change
Expand Up @@ -601,7 +601,6 @@ def simple_meta_analysis(data, options, decimal_places: int = 4, alpha: float =

output_blocks = output_filtered_bad(filtered, bad_data)

figure = None
chart_data = None
n = len(e_data)
citations = []
Expand Down Expand Up @@ -670,15 +669,15 @@ def simple_meta_analysis(data, options, decimal_places: int = 4, alpha: float =
citations.extend(new_cites)

if options.create_graph:
figure, chart_data = MetaWinCharts.chart_forest_plot("basic analysis", effect_sizes.label, forest_data,
alpha, options.bootstrap_mean, normal_ci=norm_ci)
chart_data = MetaWinCharts.chart_forest_plot("basic analysis", effect_sizes.label, forest_data,
alpha, options.bootstrap_mean, normal_ci=norm_ci)

else:
output_blocks.append([get_text("Fewer than two studies were valid for analysis")])
qt, df, p, pooled_var, i2 = None, None, None, None, None
mean_data = None

return output_blocks, figure, chart_data, simple_ma_values(mean_data, pooled_var, qt, df, p, i2), citations
return output_blocks, chart_data, simple_ma_values(mean_data, pooled_var, qt, df, p, i2), citations


# ---------- grouped meta-analysis ----------
Expand Down Expand Up @@ -740,7 +739,6 @@ def grouped_meta_analysis(data, options, decimal_places: int = 4, alpha: float =

output_blocks = output_filtered_bad(filtered, bad_data)

figure = None
chart_data = None
n = len(e_data)
g_cnt = len(group_names)
Expand Down Expand Up @@ -905,9 +903,8 @@ def grouped_meta_analysis(data, options, decimal_places: int = 4, alpha: float =
citations.extend(new_cites)

if options.create_graph:
figure, chart_data = MetaWinCharts.chart_forest_plot("grouped analysis", effect_sizes.label, forest_data,
alpha, options.bootstrap_mean, groups.label,
normal_ci=norm_ci)
chart_data = MetaWinCharts.chart_forest_plot("grouped analysis", effect_sizes.label, forest_data, alpha,
options.bootstrap_mean, groups.label, normal_ci=norm_ci)

global_values = simple_ma_values(global_mean_data, pooled_var, qt, df, pqt, i2)
else:
Expand All @@ -917,7 +914,7 @@ def grouped_meta_analysis(data, options, decimal_places: int = 4, alpha: float =
model_het = None
error_het = None

return (output_blocks, figure, chart_data,
return (output_blocks, chart_data,
group_ma_values(global_values, group_mean_values, group_het_values, model_het, error_het), citations)


Expand Down Expand Up @@ -945,7 +942,6 @@ def cumulative_meta_analysis(data, options, decimal_places: int = 4, alpha: floa

output_blocks = output_filtered_bad(filtered, bad_data)

figure = None
chart_data = None
n = len(tmp_data)
if n > 1:
Expand Down Expand Up @@ -1016,14 +1012,14 @@ def cumulative_meta_analysis(data, options, decimal_places: int = 4, alpha: floa
decimal_places, alpha, options.log_transformed))

if options.create_graph:
figure, chart_data = MetaWinCharts.chart_forest_plot("cumulative analysis", effect_sizes.label,
cumulative_means, alpha, options.bootstrap_mean,
order.label, normal_ci=norm_ci)
chart_data = MetaWinCharts.chart_forest_plot("cumulative analysis", effect_sizes.label,
cumulative_means, alpha, options.bootstrap_mean, order.label,
normal_ci=norm_ci)

else:
output_blocks.append([get_text("Fewer than two studies were valid for analysis")])

return output_blocks, figure, chart_data
return output_blocks, chart_data


# ---------- simple regression meta-analysis ----------
Expand Down Expand Up @@ -1076,7 +1072,6 @@ def regression_meta_analysis(data, options, decimal_places: int = 4, alpha: floa

output_blocks = output_filtered_bad(filtered, bad_data)

figure = None
chart_data = None
model_het = None
error_het = None
Expand Down Expand Up @@ -1205,14 +1200,13 @@ def regression_meta_analysis(data, options, decimal_places: int = 4, alpha: floa
get_citation("Greenland_1987"))
model = get_text("fixed effects")
fig_citations = ["Hedges_Olkin_1985", "Greenland_1987"]
figure, chart_data = MetaWinCharts.chart_regression(options.independent_variable.label, effect_sizes.label,
x_data, e_data, b1_slope, b0_intercept, model,
ref_list, fig_citations)
chart_data = MetaWinCharts.chart_regression(options.independent_variable.label, effect_sizes.label, x_data,
e_data, b1_slope, b0_intercept, model, ref_list, fig_citations)

else:
output_blocks.append([get_text("Fewer than two studies were valid for analysis")])

return output_blocks, figure, chart_data, reg_ma_values(global_values, model_het, error_het, predictors), citations
return output_blocks, chart_data, reg_ma_values(global_values, model_het, error_het, predictors), citations


# ---------- complex (glm) meta-analysis ----------
Expand Down Expand Up @@ -1665,7 +1659,6 @@ def nested_meta_analysis(data, options, decimal_places: int = 4, alpha: float =

n = len(e_data)

figure = None
chart_data = None
group_het_values = None
group_mean_values = None
Expand Down Expand Up @@ -1810,11 +1803,11 @@ def nested_meta_analysis(data, options, decimal_places: int = 4, alpha: float =
citations.extend(new_cites)

if options.create_graph:
figure, chart_data = MetaWinCharts.chart_forest_plot("nested analysis", effect_sizes.label, forest_data,
alpha, options.bootstrap_mean, normal_ci=norm_ci)
chart_data = MetaWinCharts.chart_forest_plot("nested analysis", effect_sizes.label, forest_data, alpha,
options.bootstrap_mean, normal_ci=norm_ci)

return (output_blocks, figure, chart_data, group_ma_values(global_values, group_mean_values, group_het_values,
model_het_values, error_het_values), citations)
return (output_blocks, chart_data, group_ma_values(global_values, group_mean_values, group_het_values,
model_het_values, error_het_values), citations)


# ---------- trim-and-fill analysis ----------
Expand Down Expand Up @@ -1847,7 +1840,6 @@ def trim_and_fill_analysis(data, options, decimal_places: int = 4, alpha: float

output_blocks = output_filtered_bad(filtered, bad_data)

figure = None
chart_data = None
n = len(e_data)
citations = []
Expand Down Expand Up @@ -1969,13 +1961,12 @@ def trim_and_fill_analysis(data, options, decimal_places: int = 4, alpha: float
decimal_places, alpha, options.log_transformed))

if options.create_graph:
figure, chart_data = MetaWinCharts.chart_trim_fill_plot(effect_sizes.label, tmp_data, n, original_mean,
mean_e)
chart_data = MetaWinCharts.chart_trim_fill_plot(effect_sizes.label, tmp_data, n, original_mean, mean_e)

else:
output_blocks.append([get_text("Fewer than two studies were valid for analysis")])

return output_blocks, figure, chart_data, None, citations
return output_blocks, chart_data, None, citations


# ---------- phylogenetic meta-analysis ----------
Expand Down Expand Up @@ -2275,7 +2266,6 @@ def jackknife_meta_analysis(data, options, decimal_places: int = 4, alpha: float

output_blocks = output_filtered_bad(filtered, bad_data)

figure = None
chart_data = None
n = len(e_data)
citations = []
Expand Down Expand Up @@ -2380,12 +2370,12 @@ def jackknife_meta_analysis(data, options, decimal_places: int = 4, alpha: float
citations.extend(new_cites)

if options.create_graph:
figure, chart_data = MetaWinCharts.chart_forest_plot("jackknife analysis", effect_sizes.label, forest_data,
alpha, options.bootstrap_mean, normal_ci=norm_ci)
chart_data = MetaWinCharts.chart_forest_plot("jackknife analysis", effect_sizes.label, forest_data, alpha,
options.bootstrap_mean, normal_ci=norm_ci)
else:
output_blocks.append([get_text("Fewer than two studies were valid for analysis")])

return output_blocks, figure, chart_data, citations
return output_blocks, chart_data, citations


# ---------- rank correlation analysis ----------
Expand Down
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